research article vs research paper

Research Article vs. Research Paper

What's the difference.

A research article and a research paper are both scholarly documents that present the findings of a research study. However, there are some differences between the two. A research article is typically a shorter document that is published in a peer-reviewed journal. It focuses on a specific research question and provides a concise summary of the study's methodology, results, and conclusions. On the other hand, a research paper is usually a longer document that provides a more comprehensive analysis of a research topic. It often includes a literature review, detailed methodology, extensive data analysis, and a discussion of the implications of the findings. While both types of documents contribute to the scientific knowledge base, research papers tend to be more in-depth and provide a more thorough exploration of the research topic.

Attribute	Research Article	Research Paper
Definition	A written document that presents the findings of a research study or experiment.	A comprehensive written document that includes an in-depth analysis and interpretation of research findings.
Purpose	To communicate the results of a specific research study or experiment to the scientific community.	To provide a detailed analysis and interpretation of research findings, often including a literature review and methodology.
Length	Typically shorter, ranging from a few pages to around 20 pages.	Usually longer, ranging from 20 to hundreds of pages.
Structure	Usually follows a standard structure including sections such as abstract, introduction, methods, results, and conclusion.	May have a more flexible structure depending on the field and specific requirements, but often includes sections such as abstract, introduction, literature review, methodology, results, discussion, and conclusion.
Scope	Focuses on presenting the findings of a specific research study or experiment.	Explores a broader research topic or question, often including a literature review and analysis of multiple studies.
Publication	Can be published in academic journals, conference proceedings, or online platforms.	Can be published in academic journals, conference proceedings, or as part of a thesis or dissertation.
Peer Review	Research articles often undergo a peer review process before publication to ensure quality and validity.	Research papers may also undergo peer review, especially if published in academic journals.

Further Detail

Introduction.

Research articles and research papers are both essential components of academic and scientific discourse. They serve as vehicles for sharing knowledge, presenting findings, and contributing to the advancement of various fields of study. While the terms "research article" and "research paper" are often used interchangeably, there are subtle differences in their attributes and purposes. In this article, we will explore and compare the key characteristics of research articles and research papers.

Definition and Purpose

A research article is a concise and focused piece of scholarly writing that typically appears in academic journals. It presents original research, experiments, or studies conducted by the author(s) and aims to communicate the findings to the scientific community. Research articles often follow a specific structure, including an abstract, introduction, methodology, results, discussion, and conclusion.

On the other hand, a research paper is a broader term that encompasses various types of academic writing, including research articles. While research papers can also be published in journals, they can take other forms such as conference papers, dissertations, or theses. Research papers provide a more comprehensive exploration of a particular topic, often including a literature review, theoretical framework, and in-depth analysis of the research question.

Length and Depth

Research articles are typically shorter in length compared to research papers. They are usually limited to a specific word count, often ranging from 3000 to 8000 words, depending on the journal's guidelines. Due to their concise nature, research articles focus on presenting the core findings and their implications without delving extensively into background information or theoretical frameworks.

On the other hand, research papers tend to be longer and more comprehensive. They can range from 5000 to 20,000 words or more, depending on the scope of the research and the requirements of the academic institution or conference. Research papers provide a deeper analysis of the topic, including an extensive literature review, theoretical framework, and detailed methodology section.

Structure and Organization

Research articles follow a standardized structure to ensure clarity and consistency across different publications. They typically begin with an abstract, which provides a concise summary of the research question, methodology, results, and conclusions. The introduction section provides background information, states the research problem, and outlines the objectives of the study. The methodology section describes the research design, data collection methods, and statistical analysis techniques used. The results section presents the findings, often accompanied by tables, figures, or graphs. The discussion section interprets the results, compares them with previous studies, and discusses their implications. Finally, the conclusion summarizes the main findings and suggests future research directions.

Research papers, on the other hand, have a more flexible structure depending on the specific requirements of the academic institution or conference. While they may include similar sections as research articles, such as an abstract, introduction, methodology, results, discussion, and conclusion, research papers can also incorporate additional sections such as a literature review, theoretical framework, or appendices. The structure of a research paper is often determined by the depth and complexity of the research conducted.

Publication and Audience

Research articles are primarily published in academic journals, which serve as platforms for disseminating new knowledge within specific disciplines. These journals often have a rigorous peer-review process, where experts in the field evaluate the quality and validity of the research before publication. Research articles are targeted towards a specialized audience of researchers, scholars, and professionals in the respective field.

Research papers, on the other hand, can be published in various formats and venues. They can be presented at conferences, published as chapters in books, or submitted as dissertations or theses. While research papers can also undergo peer-review, they may have a broader audience, including researchers, students, and professionals interested in the topic. The publication of research papers allows for a wider dissemination of knowledge beyond the confines of academic journals.

In conclusion, research articles and research papers are both vital components of academic and scientific discourse. While research articles are concise and focused pieces of scholarly writing that present original research findings, research papers provide a more comprehensive exploration of a particular topic. Research articles follow a standardized structure and are primarily published in academic journals, targeting a specialized audience. On the other hand, research papers have a more flexible structure and can be published in various formats, allowing for a wider dissemination of knowledge. Understanding the attributes and purposes of research articles and research papers is crucial for researchers, scholars, and students alike, as it enables effective communication and contributes to the advancement of knowledge in various fields.

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Types of journal articles

It is helpful to familiarise yourself with the different types of articles published by journals. Although it may appear there are a large number of types of articles published due to the wide variety of names they are published under, most articles published are one of the following types; Original Research, Review Articles, Short reports or Letters, Case Studies, Methodologies.

Original Research:

This is the most common type of journal manuscript used to publish full reports of data from research. It may be called an Original Article, Research Article, Research, or just Article, depending on the journal. The Original Research format is suitable for many different fields and different types of studies. It includes full Introduction, Methods, Results, and Discussion sections.

Short reports or Letters:

These papers communicate brief reports of data from original research that editors believe will be interesting to many researchers, and that will likely stimulate further research in the field. As they are relatively short the format is useful for scientists with results that are time sensitive (for example, those in highly competitive or quickly-changing disciplines). This format often has strict length limits, so some experimental details may not be published until the authors write a full Original Research manuscript. These papers are also sometimes called Brief communications .

Review Articles:

Review Articles provide a comprehensive summary of research on a certain topic, and a perspective on the state of the field and where it is heading. They are often written by leaders in a particular discipline after invitation from the editors of a journal. Reviews are often widely read (for example, by researchers looking for a full introduction to a field) and highly cited. Reviews commonly cite approximately 100 primary research articles.

TIP: If you would like to write a Review but have not been invited by a journal, be sure to check the journal website as some journals to not consider unsolicited Reviews. If the website does not mention whether Reviews are commissioned it is wise to send a pre-submission enquiry letter to the journal editor to propose your Review manuscript before you spend time writing it.

Case Studies:

These articles report specific instances of interesting phenomena. A goal of Case Studies is to make other researchers aware of the possibility that a specific phenomenon might occur. This type of study is often used in medicine to report the occurrence of previously unknown or emerging pathologies.

Methodologies or Methods

These articles present a new experimental method, test or procedure. The method described may either be completely new, or may offer a better version of an existing method. The article should describe a demonstrable advance on what is currently available.

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Difference between Research Paper and Research Article

Research paper and research articles are bits of composing that require inquiry, critical analysis, demonstration and insight of few special abilities from understudies and researchers. This article endeavors to see whether the two terms are synonymous or there is any contrast between the two.

Research paper

Research can be said as activity which is specified much significance in scholastics. Be that as it may, research papers are not only these task papers composed by understudies as those composed by scholars and researchers and also published in different journals are additionally alluded to as research papers.

Research Article

Research article is a bit of composing that have original research thought with the pertinent data and discoveries. A research article is a composing or paper that advises individuals of a way breaking a finding or research with data to bolster the finding.

Research Paper VS Research Article

There is a pattern to allude to academic papers and term papers composed by understudies in schools as a research paper

The articles presented by researchers and scholars with their noteworthy examination are known as research articles.

Research papers composed by the students mostly not take in journals.

Research articles composed by researchers or scholars mostly published in prestigious scientific journals.

A research paper depends on the original research. The sort of research may fluctuate, contingent upon your field or topics that include survey, experiments, questionnaire, interview and so on; yet authors require gathering and investigating raw data and make an original and real study. The research paper will be founded on the investigation and understanding of this raw data.

A research article depends on other different published articles. It is usually not depend on original study. Research articles for the most part condense the current writing on a point trying to clarify the present condition of comprehension on topic.

A research paper can be said as the primary source that means, it studies the techniques and consequences of original study performed by the writers.

A research article can be said as secondary source that means it is composed about different articles, and does not studies actual research of its own.

Importance:

In research paper, every part of this has its own importance. A concise is important in light of the fact that it shows that the writers know about existing literature, and want to add to this presented research definitively. A methods part is usually detailed and it is important in a way that different analysts have the capacity to check and/or duplicate these strategies. A result segment depicts the results of the analysis.

Research articles can be considered very important because they describe upon different articles that they analyze to propose new research bearings, to give powerful support for presented theories or distinguish designs among presented research studies. For understudy analysts, these research articles give an excellent review of presented literature on that topic. In the event that you discover a literature review that can be fit in study, investigate its references/works referred to list for guide on other articles.

From the above article we can conclude that research paper is the primary source whereas research articles are secondary.

17 Comments Already

good article but which of them is more useful when we conduct a research

both. but research paper is more useful.

Nice explanation

There is a little difference but both are different.

Nice but i have a confusion that can a guys of Bachelors level can write Research Papers?

YEs they can if they do research project instead of development project and do something new in their project.

Thank you 😊

do you have something in your mind then please share with us. We will appreciate that.

Though it may be fairly easy to learn to speak English well enough to be understood, learning to write English correctly is very difficult, as this article so clearly illustrates. Though I greatly admire all those who are making an effort to learn another language, like English, as a non-native speaker, it is wrong for these same individuals to assume they can write English well enough to publish articles.

This article is so poorly written that I cannot understand most of it. For instance, the following phrases are utter nonsense: “A research paper can be said as the primary source that means,” — “A concise is important in light of the fact that it shows that . . .” — “A methods part is usually detailed” — “A result segment depicts the results . . .” — “they describe upon different articles that they analyze to propose new research bearings . . . or distinguish designs among presented . .. studies” — “to clarify the present condition of comprehension” — “Research papers and . . . articles require inquiry, critical analysis, demonstration and insight of few special abilities from . . .”

This article also states that “[a] research article . . . is usually not depend (sic) on original study,” then contradicts that in the next sentence with “[r]esearch articles . . . condense the current writing on a point . . .” Most studies these days are current. But, even if a study was conducted 50 years ago, it’s a cardinal rule that one should always use the original source of information rather than relying on the articles of other authors who may have misquoted something from the original study.

Articles like this one do a grave disservice to the viewing and researching public. To present this article as informative is disingenuous. To ask people who are seeking useful information to struggle with reading and trying to make sense of this poor English is so unkind and inconsiderate that I feel compelled to bring it to the author’s and publisher’s attention.

I would be honored to help anyone with their efforts to write English, but, please, be honest with yourselves about your lack of knowledge, so you will cease and desist the writing of anything online until your English skills have improved significantly. Thank you.

Thanks for such a detail input. Best wishes.

Yes you are saying right. So if you have the skills to deliver the answer in an efficient manner so kindly type it for me. Because I really want to know the difference between research paper and research article

Yes I agree with Martha. I myself found difficulty in going through the article. Although the topic is very important to be discussed because being the student of graduate, I must know the difference. But the way of delivering has dispirited me that now what other website should I visit to get accurate answer.

we need Published example of a scientific research article and another for a scientific research

how can I cite this?

“Difference between Research Paper and Research Article”, Reserachpedia.info, https://researchpedia.info/difference-between-research-paper-and-research-article/ , [27 December 2021].

I don’t understand anything. I am confused more than i came. Otehrwise, thank you for a trial. Simplify this communication.

Different types of research articles

A guide for early career researchers.

In scholarly literature, there are many different kinds of articles published every year. Original research articles are often the first thing you think of when you hear the words ‘journal article’. In reality, research work often results in a whole mixture of different outputs and it’s not just the final research article that can be published.

Finding a home to publish supporting work in different formats can help you start publishing sooner, allowing you to build your publication record and research profile.

But before you do, it’s very important that you check the instructions for authors and the aims and scope of the journal(s) you’d like to submit to. These will tell you whether they accept the type of article you’re thinking of writing and what requirements they have around it.

Understanding the different kind of articles

There’s a huge variety of different types of articles – some unique to individual journals – so it’s important to explore your options carefully. While it would be impossible to cover every single article type here, below you’ll find a guide to the most common research articles and outputs you could consider submitting for publication.

Book review

Many academic journals publish book reviews, which aim to provide insight and opinion on recently published scholarly books. Writing book reviews is often a good way to begin academic writing. It can help you get your name known in your field and give you valuable experience of publishing before you write a full-length article.

If you’re keen to write a book review, a good place to start is looking for journals that publish or advertise the books they have available for review. Then it’s just a matter of putting yourself forward for one of them.

You can check whether a journal publishes book reviews by browsing previous issues or by seeing if a book review editor is listed on the editorial board. In addition, some journals publish other types of reviews, such as film, product, or exhibition reviews, so it’s worth bearing those in mind as options as well.

Get familiar with instructions for authors

Be prepared, speed up your submission, and make sure nothing is forgotten by understanding a journal’s individual requirements.

Publishing tips, direct to your inbox

Expert tips and guidance on getting published and maximizing the impact of your research. Register now for weekly insights direct to your inbox.

Case report

A medical case report – also sometimes called a clinical case study – is an original short report that provides details of a single patient case.

Case reports include detailed information on the symptoms, signs, diagnosis, treatment, and follow-up of an individual patient. They remain one of the cornerstones of medical progress and provide many new ideas in medicine.

Depending on the journal, a case report doesn’t necessarily need to describe an especially novel or unusual case as there is benefit from collecting details of many standard cases.

Take a look at F1000Research’s guidance on case reports , to understand more about what’s required in them. And don’t forget that for all studies involving human participants, informed written consent to take part in the research must be obtained from the participants – find out more about consent to publish.

Clinical study

In medicine, a clinical study report is a type of article that provides in-depth detail on the methods and results of a clinical trial. They’re typically similar in length and format to original research articles.

Most journals now require that you register protocols for clinical trials you’re involved with in a publicly accessible registry. A list of eligible registries can be found on the WHO International Clinical Trials Registry Platform (ICTRP) . Trials can also be registered at clinicaltrials.gov or the EU Clinical Trials Register . Once registered, your trial will be assigned a clinical trial number (CTN).

Before you submit a clinical study, you’ll need to include clinical trial numbers and registration dates in the manuscript, usually in the abstract and methods sections.

Commentaries and letters to editors

Letters to editors, as well as ‘replies’ and ‘discussions’, are usually brief comments on topical issues of public and political interest (related to the research field of the journal), anecdotal material, or readers’ reactions to material published in the journal.

Commentaries are similar, though they may be slightly more in-depth, responding to articles recently published in the journal. There may be a ‘target article’ which various commentators are invited to respond to.

You’ll need to look through previous issues of any journal you’re interested in writing for and review the instructions for authors to see which types of these articles (if any) they accept.

Conference materials

Many of our medical journals accept conference material supplements. These are open access peer-reviewed, permanent, and citable publications within the journal. Conference material supplements record research around a common thread, as presented at a workshop, congress, or conference, for the scientific record. They can include the following types of articles:

Poster extracts

Conference abstracts

Presentation extracts

Find out more about submitting conference materials.

Data notes are a short peer-reviewed article type that concisely describe research data stored in a repository. Publishing a data note can help you to maximize the impact of your data and gain appropriate credit for your research.

Data notes promote the potential reuse of research data and include details of why and how the data were created. They do not include any analysis but they can be linked to a research article incorporating analysis of the published dataset, as well as the results and conclusions.

F1000Research enables you to publish your data note rapidly and openly via an author-centric platform. There is also a growing range of options for publishing data notes in Taylor & Francis journals, including in All Life and Big Earth Data .

Read our guide to data notes to find out more.

Letters or short reports

Letters or short reports (sometimes known as brief communications or rapid communications) are brief reports of data from original research.

Editors publish these reports where they believe the data will be interesting to many researchers and could stimulate further research in the field. There are even entire journals dedicated to publishing letters.

As they’re relatively short, the format is useful for researchers with results that are time sensitive (for example, those in highly competitive or quickly-changing disciplines). This format often has strict length limits, so some experimental details may not be published until the authors write a full original research article.

Brief reports (previously called Research Notes) are a type of short report published by F1000Research – part of the Taylor & Francis Group. To find out more about the requirements for a brief report, take a look at F1000Research’s guidance .

Vector illustration of a large open laptop, with four puzzle pieces that are blue and pink on the screen, and three characters stood around the laptop pointing at the puzzle pieces.

Method article

A method article is a medium length peer-reviewed, research-focused article type that aims to answer a specific question. It also describes an advancement or development of current methodological approaches and research procedures (akin to a research article), following the standard layout for research articles. This includes new study methods, substantive modifications to existing methods, or innovative applications of existing methods to new models or scientific questions. These should include adequate and appropriate validation to be considered, and any datasets associated with the paper must publish all experimental controls and make full datasets available.  

Posters and slides

With F1000Research, you can publish scholarly posters and slides covering basic scientific, translational, and clinical research within the life sciences and medicine. You can find out more about how to publish posters and slides on the F1000Research website .

Registered report

A Registered Report consists of two different kinds of articles: a study protocol and an original research article.

This is because the review process for Registered Reports is divided into two stages. In Stage 1, reviewers assess study protocols before data is collected. In Stage 2, reviewers consider the full published study as an original research article, including results and interpretation.

Taking this approach, you can get an in-principle acceptance of your research article before you start collecting data. We’ve got further guidance on Registered Reports here , and you can also read F1000Research’s guidance on preparing a Registered Report .

Research article

Original research articles are the most common type of journal article. They’re detailed studies reporting new work and are classified as primary literature.

You may find them referred to as original articles, research articles, research, or even just articles, depending on the journal.

Typically, especially in STEM subjects, these articles will include Abstract, Introduction, Methods, Results, Discussion, and Conclusion sections. However, you should always check the instructions for authors of your chosen journal to see whether it specifies how your article should be structured. If you’re planning to write an original research article, take a look at our guidance on writing a journal article .

Review article

Review articles provide critical and constructive analysis of existing published literature in a field. They’re usually structured to provide a summary of existing literature, analysis, and comparison. Often, they identify specific gaps or problems and provide recommendations for future research.

Unlike original research articles, review articles are considered as secondary literature. This means that they generally don’t present new data from the author’s experimental work, but instead provide analysis or interpretation of a body of primary research on a specific topic. Secondary literature is an important part of the academic ecosystem because it can help explain new or different positions and ideas about primary research, identify gaps in research around a topic, or spot important trends that one individual research article may not.

There are 3 main types of review article

Literature review

Presents the current knowledge including substantive findings as well as theoretical and methodological contributions to a particular topic.

Systematic review

Identifies, appraises and synthesizes all the empirical evidence that meets pre-specified eligibility criteria to answer a specific research question. Researchers conducting systematic reviews use explicit, systematic methods that are selected with a view aimed at minimizing bias, to produce more reliable findings to inform decision making.

Meta-analysis

A quantitative, formal, epidemiological study design used to systematically assess the results of previous research to derive conclusions about that body of research. Typically, but not necessarily, a meta-analysis study is based on randomized, controlled clinical trials.

Take a look at our guide to writing a review article for more guidance on what’s required.

Software tool articles

A software tool article – published by F1000Research – describes the rationale for the development of a new software tool and details of the code used for its construction.

The article should provide examples of suitable input data sets and include an example of the output that can be expected from the tool and how this output should be interpreted. Software tool articles submitted to F1000Research should be written in open access programming languages. Take a look at their guidance for more details on what’s required of a software tool article.

Further resources

Ready to write your article, but not sure where to start?

For more guidance on how to prepare and write an article for a journal you can download the Writing your paper eBook .

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Scholarly Journals and Popular Magazines
Differences in Research, Review, and Opinion Articles

Scholarly Journals and Popular Magazines: Differences in Research, Review, and Opinion Articles

Where Do I Start?
How Do I Find Peer-Reviewed Articles?
How Do I Compare Periodical Types?
Where Can I find More Information?

Research Articles, Reviews, and Opinion Pieces

Scholarly or research articles are written for experts in their fields. They are often peer-reviewed or reviewed by other experts in the field prior to publication. They often have terminology or jargon that is field specific. They are generally lengthy articles. Social science and science scholarly articles have similar structures as do arts and humanities scholarly articles. Not all items in a scholarly journal are peer reviewed. For example, an editorial opinion items can be published in a scholarly journal but the article itself is not scholarly. Scholarly journals may include book reviews or other content that have not been peer reviewed.

Empirical Study: (Original or Primary) based on observation, experimentation, or study. Clinical trials, clinical case studies, and most meta-analyses are empirical studies.

Review Article: (Secondary Sources) Article that summarizes the research in a particular subject, area, or topic. They often include a summary, an literature reviews, systematic reviews, and meta-analyses.

Clinical case study (Primary or Original sources): These articles provide real cases from medical or clinical practice. They often include symptoms and diagnosis.

Clinical trials ( Health Research): Th ese articles are often based on large groups of people. They often include methods and control studies. They tend to be lengthy articles.

Opinion Piece: An opinion piece often includes personal thoughts, beliefs, or feelings or a judgement or conclusion based on facts. The goal may be to persuade or influence the reader that their position on this topic is the best.

Book review: Recent review of books in the field. They may be several pages but tend to be fairly short.

Social Science and Science Research Articles

The majority of social science and physical science articles include

Journal Title and Author
Abstract
Introduction with a hypothesis or thesis
Literature Review
Methods/Methodology
Results/Findings

Arts and Humanities Research Articles

In the Arts and Humanities, scholarly articles tend to be less formatted than in the social sciences and sciences. In the humanities, scholars are not conducting the same kinds of research experiments, but they are still using evidence to draw logical conclusions. Common sections of these articles include:

an Introduction
Discussion/Conclusion
works cited/References/Bibliography

Research versus Review Articles

6 Article types that journals publish: A guide for early career researchers
INFOGRAPHIC: 5 Differences between a research paper and a review paper
Michigan State University. Empirical vs Review Articles
UC Merced Library. Empirical & Review Articles
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What are the main differences between an article and a research paper?

Insight from top 3 papers.

An article and a research paper have some key differences. A research paper is a verbal presentation of research findings, while an article focuses on sharing findings with a wider audience [1] [2] . Research papers follow a specific structure, typically using the IMRaD format (introduction, methods, results, and discussion) [3] . Articles, on the other hand, may have a more flexible structure, depending on the nature of the research and the target audience [2] . Research papers often include a literature review to survey earlier research and identify research gaps [1] . Articles may also include a literature review, but the emphasis is on presenting new insights and adding to the existing knowledge [2] . Research papers are typically more formal and rely on reasoning, data, examples, and interpretations to support the main point [1] . Articles may also use these elements, but they may also include visual elements and direct quotes to emphasize key results [2] .

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Q. What's the difference between a research article (or research study) and a review article?

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Answered By: Priscilla Coulter Last Updated: Jul 26, 2024 Views: 233914

A research paper is a primary source ...that is, it reports the methods and results of an original study performed by the authors . The kind of study may vary (it could have been an experiment, survey, interview, etc.), but in all cases, raw data have been collected and analyzed by the authors , and conclusions drawn from the results of that analysis.

Research papers follow a particular format. Look for:

A brief introduction will often include a review of the existing literature on the topic studied, and explain the rationale of the author's study. This is important because it demonstrates that the authors are aware of existing studies, and are planning to contribute to this existing body of research in a meaningful way (that is, they're not just doing what others have already done).
A methods section, where authors describe how they collected and analyzed data. Statistical analyses are included. This section is quite detailed, as it's important that other researchers be able to verify and/or replicate these methods.
A results section describes the outcomes of the data analysis. Charts and graphs illustrating the results are typically included.
In the discussion , authors will explain their interpretation of their results and theorize on their importance to existing and future research.
References or works cited are always included. These are the articles and books that the authors drew upon to plan their study and to support their discussion.

You can use the library's databases to search for research articles:

A research article will nearly always be published in a peer-reviewed journal; click here for instructions on limiting your searches to peer-reviewed articles .
If you have a particular type of study in mind, you can include keywords to describe it in your search . For instance, if you would like to see studies that used surveys to collect data, you can add "survey" to your topic in the database's search box. See this example search in our EBSCO databases: " bullying and survey ".
Several of our databases have special limiting options that allow you to select specific methodologies. See, for instance, the " Methodology " box in ProQuest's PsycARTICLES Advanced Search (scroll down a bit to see it). It includes options like "Empirical Study" and "Qualitative Study", among many others.

A review article is a secondary source ...it is written about other articles, and does not report original research of its own. Review articles are very important, as they draw upon the articles that they review to suggest new research directions, to strengthen support for existing theories and/or identify patterns among exising research studies. For student researchers, review articles provide a great overview of the existing literature on a topic. If you find a literature review that fits your topic, take a look at its references/works cited list for leads on other relevant articles and books!

You can use the library's article databases to find literature reviews as well! Click here for tips.

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Difference Between Research Article and Research Paper

This article will discuss both writings formats and discuss Difference Between Research Article and Research Paper.

Both types of writing are common techniques used by educators and businesses to get feedback from coworkers and students on a topic or subject. One must understand each form and how people use it in to differentiate between the two types of writing.

Research Article

What will a researcher or scientist do after they have found the answer to a question or made a discovery they wish to share with the world?

A research article, according to Simon Fraser University, is a piece of writing that is written about a specific topic. A research article written by an expert in a certain field is frequently written by another expert in the same field. Peer reviews are another term for this kind of writing.

Purpose of Research Article

A research article may be a significant source, making it a valuable resource for creating the thesis for the relevant topic. It includes a report on the methods and results of the researchers’ original research.

Format of Research Article

Create a title that is specific enough to summarize the entire article’s content while being understandable. The article’s title ought to be relevant for the target audience.

Other people have made significant contributions in writing the research article that is published, and as a result, they are considered authors. Before listing your mentor’s name as a co-author or author, you can get their permission.

Giving all the information in a single paragraph is not very simple. Start by including the overview of what you feel is vital to mention, and then gradually reduce the length by omitting the unimportant details while keeping the crucial information.

→INTRODUCTION

A two- to four-paragraph introduction is appropriate. Finish it up with a statement that clarifies the question.

If you have a complicated method, it can be beneficial to include diagrams, flowcharts, or tables to describe how you use it.

What pain-reduction measures would you adopt if you used animals?

Don’t discuss the outcomes or speculate as to why anything occurred. None of the information you discovered from research needs to be mentioned. Employ appropriate techniques to explain the data. Don’t try to distort your facts to make it appear that you have accomplished more than you have.

→TABLES AND GRAPHS

→discussion.

Provide reasons if the results are surprising.

→ACKNOWLEDGMENTS

→references, research paper.

When referring to research papers, Dr. Jane Simonsen, a history professor, once said, “The work and design are your own, but you can’t do it without relying on the efforts and wisdom of others.”

After gathering all necessary information from sources, a student’s work will be organized into the structure. Teachers frequently use this method to help students develop a balance in their writing abilities while promoting structural discipline and standard formatting.

Purpose of Research Paper

Format for research papers.

There is a set format for research papers.

Read More: Reliability vs Validity | Examples

References and citations can be added here. References are genuine books and articles that authors use to conduct their research and support their arguments.

Difference Between Research Paper and Research Article


Written by a student at a university or college	Written by a researcher, expert or scientist
Done under the supervision of a supervisor i.e. teacher or instructor	Done with other researchers known as co-authors.
Focused on Research questions and objectives	Broad in scope
Doesn’t contain extensive reference list	Contains extensive reference list
Exclusively written for college or university purposes and published in a conference and presented as an oral presentation	Gets published to periodicals, journals or magazines, peer-reviewed journal
Longer in length	Shorter in length
isn’t authored to present original research it shows empirical data	present original research
Used to educate a student on how to write clearly and effectively about a topic	Used to educate the reader on a subject or topic
Student’s name, class, date, and instructor all in the left corner of the paper, while the title is centered.	Title is at the top and center. The author/s names will be below, and the format will follow much as a journal article would.

3- A research paper isn’t published in any publication unless it’s a guideline on how to write one, whereas a research article is submitted to periodicals, magazines or peer-reviewed journal.

6- The title of the research paper will be centered, and the student’s name, class, date, and teacher will be in the left corner. Whereas the title will be top and centre in the research article. The names of the author(s) are listed below.

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Knowledge Base
Research paper

How to Write a Research Paper | A Beginner's Guide

A research paper is a piece of academic writing that provides analysis, interpretation, and argument based on in-depth independent research.

Research papers are similar to academic essays , but they are usually longer and more detailed assignments, designed to assess not only your writing skills but also your skills in scholarly research. Writing a research paper requires you to demonstrate a strong knowledge of your topic, engage with a variety of sources, and make an original contribution to the debate.

This step-by-step guide takes you through the entire writing process, from understanding your assignment to proofreading your final draft.

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Understand the assignment, choose a research paper topic, conduct preliminary research, develop a thesis statement, create a research paper outline, write a first draft of the research paper, write the introduction, write a compelling body of text, write the conclusion, the second draft, the revision process, research paper checklist, free lecture slides.

Completing a research paper successfully means accomplishing the specific tasks set out for you. Before you start, make sure you thoroughly understanding the assignment task sheet:

Read it carefully, looking for anything confusing you might need to clarify with your professor.
Identify the assignment goal, deadline, length specifications, formatting, and submission method.
Make a bulleted list of the key points, then go back and cross completed items off as you’re writing.

Carefully consider your timeframe and word limit: be realistic, and plan enough time to research, write, and edit.

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There are many ways to generate an idea for a research paper, from brainstorming with pen and paper to talking it through with a fellow student or professor.

You can try free writing, which involves taking a broad topic and writing continuously for two or three minutes to identify absolutely anything relevant that could be interesting.

You can also gain inspiration from other research. The discussion or recommendations sections of research papers often include ideas for other specific topics that require further examination.

Once you have a broad subject area, narrow it down to choose a topic that interests you, m eets the criteria of your assignment, and i s possible to research. Aim for ideas that are both original and specific:

A paper following the chronology of World War II would not be original or specific enough.
A paper on the experience of Danish citizens living close to the German border during World War II would be specific and could be original enough.

Note any discussions that seem important to the topic, and try to find an issue that you can focus your paper around. Use a variety of sources , including journals, books, and reliable websites, to ensure you do not miss anything glaring.

Do not only verify the ideas you have in mind, but look for sources that contradict your point of view.

Is there anything people seem to overlook in the sources you research?
Are there any heated debates you can address?
Do you have a unique take on your topic?
Have there been some recent developments that build on the extant research?

In this stage, you might find it helpful to formulate some research questions to help guide you. To write research questions, try to finish the following sentence: “I want to know how/what/why…”

A thesis statement is a statement of your central argument — it establishes the purpose and position of your paper. If you started with a research question, the thesis statement should answer it. It should also show what evidence and reasoning you’ll use to support that answer.

The thesis statement should be concise, contentious, and coherent. That means it should briefly summarize your argument in a sentence or two, make a claim that requires further evidence or analysis, and make a coherent point that relates to every part of the paper.

You will probably revise and refine the thesis statement as you do more research, but it can serve as a guide throughout the writing process. Every paragraph should aim to support and develop this central claim.

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A research paper outline is essentially a list of the key topics, arguments, and evidence you want to include, divided into sections with headings so that you know roughly what the paper will look like before you start writing.

A structure outline can help make the writing process much more efficient, so it’s worth dedicating some time to create one.

Your first draft won’t be perfect — you can polish later on. Your priorities at this stage are as follows:

Maintaining forward momentum — write now, perfect later.
Paying attention to clear organization and logical ordering of paragraphs and sentences, which will help when you come to the second draft.
Expressing your ideas as clearly as possible, so you know what you were trying to say when you come back to the text.

You do not need to start by writing the introduction. Begin where it feels most natural for you — some prefer to finish the most difficult sections first, while others choose to start with the easiest part. If you created an outline, use it as a map while you work.

Do not delete large sections of text. If you begin to dislike something you have written or find it doesn’t quite fit, move it to a different document, but don’t lose it completely — you never know if it might come in useful later.

Paragraph structure

Paragraphs are the basic building blocks of research papers. Each one should focus on a single claim or idea that helps to establish the overall argument or purpose of the paper.

Example paragraph

George Orwell’s 1946 essay “Politics and the English Language” has had an enduring impact on thought about the relationship between politics and language. This impact is particularly obvious in light of the various critical review articles that have recently referenced the essay. For example, consider Mark Falcoff’s 2009 article in The National Review Online, “The Perversion of Language; or, Orwell Revisited,” in which he analyzes several common words (“activist,” “civil-rights leader,” “diversity,” and more). Falcoff’s close analysis of the ambiguity built into political language intentionally mirrors Orwell’s own point-by-point analysis of the political language of his day. Even 63 years after its publication, Orwell’s essay is emulated by contemporary thinkers.

Citing sources

It’s also important to keep track of citations at this stage to avoid accidental plagiarism . Each time you use a source, make sure to take note of where the information came from.

You can use our free citation generators to automatically create citations and save your reference list as you go.

APA Citation Generator MLA Citation Generator

The research paper introduction should address three questions: What, why, and how? After finishing the introduction, the reader should know what the paper is about, why it is worth reading, and how you’ll build your arguments.

What? Be specific about the topic of the paper, introduce the background, and define key terms or concepts.

Why? This is the most important, but also the most difficult, part of the introduction. Try to provide brief answers to the following questions: What new material or insight are you offering? What important issues does your essay help define or answer?

How? To let the reader know what to expect from the rest of the paper, the introduction should include a “map” of what will be discussed, briefly presenting the key elements of the paper in chronological order.

The major struggle faced by most writers is how to organize the information presented in the paper, which is one reason an outline is so useful. However, remember that the outline is only a guide and, when writing, you can be flexible with the order in which the information and arguments are presented.

One way to stay on track is to use your thesis statement and topic sentences . Check:

topic sentences against the thesis statement;
topic sentences against each other, for similarities and logical ordering;
and each sentence against the topic sentence of that paragraph.

Be aware of paragraphs that seem to cover the same things. If two paragraphs discuss something similar, they must approach that topic in different ways. Aim to create smooth transitions between sentences, paragraphs, and sections.

The research paper conclusion is designed to help your reader out of the paper’s argument, giving them a sense of finality.

Trace the course of the paper, emphasizing how it all comes together to prove your thesis statement. Give the paper a sense of finality by making sure the reader understands how you’ve settled the issues raised in the introduction.

You might also discuss the more general consequences of the argument, outline what the paper offers to future students of the topic, and suggest any questions the paper’s argument raises but cannot or does not try to answer.

You should not :

Offer new arguments or essential information
Take up any more space than necessary
Begin with stock phrases that signal you are ending the paper (e.g. “In conclusion”)

There are four main considerations when it comes to the second draft.

Check how your vision of the paper lines up with the first draft and, more importantly, that your paper still answers the assignment.
Identify any assumptions that might require (more substantial) justification, keeping your reader’s perspective foremost in mind. Remove these points if you cannot substantiate them further.
Be open to rearranging your ideas. Check whether any sections feel out of place and whether your ideas could be better organized.
If you find that old ideas do not fit as well as you anticipated, you should cut them out or condense them. You might also find that new and well-suited ideas occurred to you during the writing of the first draft — now is the time to make them part of the paper.

The goal during the revision and proofreading process is to ensure you have completed all the necessary tasks and that the paper is as well-articulated as possible. You can speed up the proofreading process by using the AI proofreader .

Global concerns

Confirm that your paper completes every task specified in your assignment sheet.
Check for logical organization and flow of paragraphs.
Check paragraphs against the introduction and thesis statement.

Fine-grained details

Check the content of each paragraph, making sure that:

each sentence helps support the topic sentence.
no unnecessary or irrelevant information is present.
all technical terms your audience might not know are identified.

Next, think about sentence structure , grammatical errors, and formatting . Check that you have correctly used transition words and phrases to show the connections between your ideas. Look for typos, cut unnecessary words, and check for consistency in aspects such as heading formatting and spellings .

Finally, you need to make sure your paper is correctly formatted according to the rules of the citation style you are using. For example, you might need to include an MLA heading or create an APA title page .

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Checklist: Research paper

I have followed all instructions in the assignment sheet.

My introduction presents my topic in an engaging way and provides necessary background information.

My introduction presents a clear, focused research problem and/or thesis statement .

My paper is logically organized using paragraphs and (if relevant) section headings .

Each paragraph is clearly focused on one central idea, expressed in a clear topic sentence .

Each paragraph is relevant to my research problem or thesis statement.

I have used appropriate transitions to clarify the connections between sections, paragraphs, and sentences.

My conclusion provides a concise answer to the research question or emphasizes how the thesis has been supported.

My conclusion shows how my research has contributed to knowledge or understanding of my topic.

My conclusion does not present any new points or information essential to my argument.

I have provided an in-text citation every time I refer to ideas or information from a source.

I have included a reference list at the end of my paper, consistently formatted according to a specific citation style .

I have thoroughly revised my paper and addressed any feedback from my professor or supervisor.

I have followed all formatting guidelines (page numbers, headers, spacing, etc.).

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Types of research papers

Analytical research paper

Argumentative or persuasive paper, definition paper, compare and contrast paper, cause and effect paper, interpretative paper, experimental research paper, survey research paper, frequently asked questions about the different types of research papers, related articles.

There are multiple different types of research papers. It is important to know which type of research paper is required for your assignment, as each type of research paper requires different preparation. Below is a list of the most common types of research papers.

➡️ Read more: What is a research paper?

In an analytical research paper you:

pose a question
collect relevant data from other researchers
analyze their different viewpoints

You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic. It is important to stay neutral and not show your own negative or positive position on the matter.

The argumentative paper presents two sides of a controversial issue in one paper. It is aimed at getting the reader on the side of your point of view.

You should include and cite findings and arguments of different researchers on both sides of the issue, but then favor one side over the other and try to persuade the reader of your side. Your arguments should not be too emotional though, they still need to be supported with logical facts and statistical data.

Tip: Avoid expressing too much emotion in a persuasive paper.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information. You should include facts from a variety of sources, but leave those facts unanalyzed.

Compare and contrast papers are used to analyze the difference between two:

Make sure to sufficiently describe both sides in the paper, and then move on to comparing and contrasting both thesis and supporting one.

Cause and effect papers are usually the first types of research papers that high school and college students write. They trace probable or expected results from a specific action and answer the main questions "Why?" and "What?", which reflect effects and causes.

In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

An interpretative paper requires you to use knowledge that you have gained from a particular case study, for example a legal situation in law studies. You need to write the paper based on an established theoretical framework and use valid supporting data to back up your statement and conclusion.

This type of research paper basically describes a particular experiment in detail. It is common in fields like:

Experiments are aimed to explain a certain outcome or phenomenon with certain actions. You need to describe your experiment with supporting data and then analyze it sufficiently.

This research paper demands the conduction of a survey that includes asking questions to respondents. The conductor of the survey then collects all the information from the survey and analyzes it to present it in the research paper.

➡️ Ready to start your research paper? Take a look at our guide on how to start a research paper .

In an analytical research paper, you pose a question and then collect relevant data from other researchers to analyze their different viewpoints. You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information.

Cause and effect papers are usually the first types of research papers that high school and college students are confronted with. The answer questions like "Why?" and "What?", which reflect effects and causes. In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

This type of research paper describes a particular experiment in detail. It is common in fields like biology, chemistry or physics. Experiments are aimed to explain a certain outcome or phenomenon with certain actions.

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Expert Commentary

White papers, working papers, preprints, journal articles: What’s the difference?

In this updated piece, we explain the most common types of research papers journalists will encounter, noting their strengths and weaknesses.

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource February 25, 2022

This <a target="_blank" href="https://journalistsresource.org/media/working-papers-research-articles/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

This tip sheet, originally published in May 2018, has been updated to include preprint research, a type of research featured often in news coverage of the coronavirus pandemic.

Journalists rely most often on four types of research in their work. White papers, working papers, preprints and peer-reviewed journal articles.

How are they different? And which is best?

Below, we explain each, pointing out its strengths and weaknesses. As always, we urge journalists to use care in selecting any research to ground their coverage and fact-check claims.

Peer-reviewed article

Peer-reviewed research — the kind that appears in academic journals and that we highlight here at The Journalist’s Resource — has undergone a detailed critique by scholars with expertise in the field. While peer-reviewed research is generally the most reliable, journalists should keep in mind that publication in a prestigious journal is no guarantee of quality and that no single university or research organization always does the best research on a given topic.

It is safe to assume, however, that articles published in top-tier journals have been reviewed and given a stamp of approval by a number of accomplished scholars. For journalists who are uncertain, we’ve put together a list of 13 questions to ask to gauge the quality of a research article.

Keep in mind that not everything that appears in a scholarly journal has been peer reviewed. Journals publish various types of content, including book reviews, editorials, letters to the editor and, sometimes, even poetry.

Working paper

This broad category describes research papers that have not been peer reviewed or published in a journal. Working papers can be in various stages of completion. One might be ready for publication in a prestigious journal while another requires significant editing and other changes that could actually alter its main findings. Sometimes, working paper findings are so preliminary, authors will advise against citing their work .

Even so, working papers are a great way for journalists to gain access to new research quickly. The peer-review and publication process can take months to a year or longer, which means that by the time studies get published, their findings are sometimes not as useful or the data are old.

In choosing working papers, journalists should communicate with scholars about the progress of their research and how confident they are in their findings. It’s a good idea to seek corroboration from peer-reviewed research and to ask other researchers for help assessing a study.

A preprint is similar to a working paper in that it has not been vetted through a formal peer-review process. However, preprints tend to be more complete . Also, preprints submitted to public servers such as the Social Science Research Network and the health sciences server medRxiv get a cursory screening before they’re published online for public view.

Preprints, like academic journal articles, are assigned a Digital Object Identifier , or DOI, and become a permanent part of the scientific record.

White paper

A white paper is a report, often compiled by government agencies, businesses and nonprofit organizations, that outlines an issue and often explores possible solutions to a problem. For example, in November 2021, the federal Office of Community Oriented Policing Services released a white paper looking at factors that help or hinder law enforcement recruitment of Black Americans. Earlier in the year, the Advanced Technology Academic Research Center published a white paper on the American Rescue Plan ‘s widespread implications for government agencies.

In the business world, white papers also are used for marketing purposes — to describe a new product or approach, for instance, or diagnose a problem.

While a white paper can help journalists get up to speed quickly on an issue, it’s important to note some white papers advocate a specific position or policy change. Some rely on incomplete research or research that has not been peer reviewed.

Looking for more guidance on writing about research? Check out our tip sheets on covering biomedical research preprints amid the coronavirus and what journalists should know about peer review .

The Journalist’s Resource would like to thank Matthew Baum , the Marvin Kalb professor of global communications and professor of public policy at Harvard Kennedy School, for his help preparing this tip sheet.

About The Author

Denise-Marie Ordway

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Difference between Paper and Article for scientific writings

As I know, in most of situations (in scientific context) these two terms are used to point to same thing and even they are used interchangeably.

For example,

Theory of value with public goods: A survey article

A survey paper on cloud computing

Are there any major differences between them? and can we use them interchangeably in any context?

differences

1 See also: article vs paper – Martin Thoma Commented Nov 24, 2019 at 11:46

3 Answers 3

The following extract helps understand the difference between a research article and a research paper :

Research paper and research articles are pieces of writing that require critical analysis, inquiry, insight, and demonstration of some special skills from students and scientists. It is really overwhelming for students when their teachers ask them to write a research paper as a form of assignment. Students remain confused between a research paper and a research article because of their similarities. This article attempts to find out if the two terms are synonymous or there is any difference between the two.

Research Article

What do you do when you are a scientist or a scholar and have arrived at a solution to a problem or have made a discovery that you want to share with the world? Well, one of the best ways to let the world know about your piece of wisdom or knowledge is through a research article. This is a piece of writing that contains an original research idea with the relevant data and findings Research article is published in renowned scientific journals that are involved with works in the area to which the paper pertains. A research article is a paper or writing that informs people of a path breaking research or a finding with clinical data to support the finding.

Research Paper

Research is an activity that is given much importance in academics, and this is why assignments requiring research and technical writing start early in the school. Students are asked to submit a research paper as early as in High School, and they become used to the concept when they are pursuing higher studies in colleges. However, a research paper is not just these assignment papers written by students as those written by scholars and scientists and published in journals are also referred to as research papers.

What is the difference between Research Article and Research Paper?

• There is no difference as such between a research article and a research paper and both involve original research with findings. • There is a trend to refer to term papers and academic papers written by students in colleges as research papers whereas articles submitted by scholars and scientists with their groundbreaking research are termed as research articles. • Research articles are published in renowned scientific journals whereas papers written by students do not go to journals.

(www.differencebetween.com)

There is no definitive distinction between papers and articles that can be applied to all scientific disciplines. Usage varies between disciplines. and within disciplines it can vary depending on context.

Both the examples quoted refer to ‘writings’ that are surveys (in other areas often termed reviews) — one in the field of a social science (economics) and the other in a numerical science (computing). However the term science is also (and perhaps more) associated with the experimental sciences (physics, chemistry and biology), where the types of ‘writings’ are different and where different words are used to distinguish them.

Articles and papers in the Experimental Sciences

Let me illustrate this for the Biomolecular Sciences (biochemistry, molecular biology, molecular genetics and the like). As a practitioner in this area, when I hear these terms, e.g. talking to colleagues, I understand:

Paper : A report of a piece of experimental research work in which the original data presented by the authors was central to interpretation and conclusions regarding advancement of knowledge and understanding of the field. Article : A review or commentary in which the author was discussing the previously published work of others (perhaps including his own) in attempting to provide a perspective of the field or to present a new theory/model/interpretation by integrating such work.

However, despite this professional conversational use of the terms, if I go to any specific journal — here the US heavyweight, Journal of Biological Chemistry (JBC) — I would find a somewhat different usage:

JBC publishes several types of articles but only two of those can be submitted as an unsolicited manuscript: regular papers and accelerated communications.

Thus, JBC regards all the ‘writings’ it publishes as ‘articles’, in common with other journals such as The Journal of Biophysics , and this is consistent with general non-scientific usage — “I read an article in the Financial Times yesterday…”

The way JBC uses ‘regular paper’, is consistent with my specialist conversational definition (above), and although it doesn’t actually say what types of ‘article’ are unsolicited, but if you look at a table of contents of the journal , you would conclude that for this journal it is ‘minireviews’ and historical appraisals of the work of individual scientists.

The Journal of Biophysics only uses the term ‘paper’ in describing only one of its categories of ‘article’:

Comments to the Editor | Short commentaries on a paper published earlier in BJ.

Again using ‘paper’ rather in the sense I defined above.

To conclude, in the extended sense used by peer-reviewed journals in the experimental sciences, all published ‘papers’ can be referred to as articles, but not all articles would be referred to as ‘papers’. (One wouldn’t use ‘paper’ for an editorial, a news item and generally not for a review.) This is exactly the opposite conclusion reached by @1006a from his reading of the OED.

Conflict with the OED and non-experimental sciences

How can one resolve the conflict with the OED, mentioned above? I think the OED describes more traditional usage in the non-experimental sciences and the arts. It is pertinent, in this respect, to consider the phrase “reading a paper” .

As far as my area of science goes, this is just a rather outdated term for presenting one’s results orally at a conference. The talk in itself is transitory, the abstract unreviewed, and the information conveyed will most probably be published elsewhere.

However for colleagues in computing science the talk is likely to be based on a ‘paper’ that has been submitted to the conference organisers, selected after peer-review, and will be published as conference proceedings or in a journal associated with the conference. This is more in line with traditional non-scientific academic presentations, although in this case the ‘paper’ might never have been published.

The difference would seem to derive in part from whether the field of science is one in which original work is in the form of ideas or in the form of measurements and their interpretation.

The distinction I would make is that an article is formally published, generally in some kind of periodical. The relevant definition, from Oxford Dictionaries:

A piece of writing included with others in a newspaper, magazine, or other publication.

Scholarly/scientific/research articles are thus "pieces of writing included with others in" an appropriate publication, most often an academic journal (see Wikipedia).

A paper , on the other hand, may or may not be published anywhere; and if it is published, may be in some alternate venue like conference proceedings (though it can be published in a scholarly journal). Again from Oxford:

An essay or dissertation, especially one read at an academic lecture or seminar or published in an academic journal.

So you can generally call any scientific (research) article a paper, but not all papers are articles.

Edited to clarify the last sentence, to which I also added the parenthetical (research):

Of course, not all articles are scientific (or research ) articles; that distinction generally means that the article presents original research, and as I am using it, that it has met certain standards of whichever field it represents (usually some form of peer review) so that it can be published in a scientific/scholarly journal. A scientific (research) paper meets the first of these criteria, but not necessarily the second (it presents original research, but may or may not be published). There are other kinds of articles/papers, which would ordinarily get a different modifier, like review or meta-review (or newspaper/magazine etc. for articles), or might commonly go by other terms altogether, like essay .

By this definition, not all articles are papers, and not all papers are articles, but all scientific (research) articles are also scientific (research) papers.

Just to mention that in my consideration of experimental sciences I present the opposite conclusion from that you draw from the OED. Please don't think I am saying you are wrong, but as I explain, that your assertions only hold for certain areas of science. – David Commented Jul 15, 2017 at 22:27
@David The key distinction I make is that articles are published . That would, indeed, include things like (literature) review articles, commentary, and possibly book reviews. It does not exclude original research in any field of which I am aware (which includes "experimental science"). It is certainly possible that certain disciplines or specific journals have non-standard usages, but I don't believe it breaks down along "experimental" and "non-experimental" lines. – 1006a Commented Jul 16, 2017 at 16:38
I agree about there being a difference in relation to publication. The whole background of "reading a paper" implies it can exist without being published, and even in the experimental sciences one might say "I wrote a paper about 'whatever' and sent it to such-and-such a Journal, but they rejected it because the referees were too stupid to understand it". You might feasibly say that about an article (I once had a solicited mini-review rejected because it was thought to be in bad taste) but it would be unusual. But a very popular program for storing PDFs of publications is called... "Papers". – David Commented Jul 16, 2017 at 16:53

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Characteristics of a Primary Research Article

Goal is to present the result of original research that makes a new contribution to the body of knowledge
Sometimes referred to as an empirical research article
Typically organized into sections that include: Abstract, Introduction, Methods, Results, Discussion/Conclusion, and References.

Example of a Primary Research Article:

Flockhart, D.T.T., Fitz-gerald, B., Brower, L.P., Derbyshire, R., Altizer, S., Hobson, K.A., … Norris, D.R., (2017). Migration distance as a selective episode for wing morphology in a migratory insect. Movement Ecology , 5(1), 1-9. doi: doi.org/10.1186/s40462-017-0098-9

Characteristics of a Review Article

Goal is to summarize important research on a particular topic and to represent the current body of knowledge about that topic.
Not intended to provide original research but to help draw connections between research studies that have previously been published.
Help the reader understand how current understanding of a topic has developed over time and identify gaps or inconsistencies that need further exploration.

Example of a Review Article:

https://www-sciencedirect-com.ezproxy.oswego.edu/science/article/pii/S0960982218302537

<< Previous: Plagiarism
Next: Peer Review >>

International Journal of Research (IJR)

IJR Journal is Multidisciplinary, high impact and indexed journal for research publication. IJR is a monthly journal for research publication.

DIFFERENCE BETWEEN RESEARCH PAPER AND JOURNAL ARTICLE

Difference between research paper and journal article.

Research Paper

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Argumentative Research Paper

Analytical research paper, journal article, the differences, research paper:, journal article:.

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Review vs. Research Articles

How can you tell if you are looking at a research paper, review paper or a systematic review examples and article characteristics are provided below to help you figure it out., research papers.

A research article describes a study that was performed by the article’s author(s). It explains the methodology of the study, such as how data was collected and analyzed, and clarifies what the results mean. Each step of the study is reported in detail so that other researchers can repeat the experiment.

To determine if a paper is a research article, examine its wording. Research articles describe actions taken by the researcher(s) during the experimental process. Look for statements like “we tested,” “I measured,” or “we investigated.” Research articles also describe the outcomes of studies. Check for phrases like “the study found” or “the results indicate.” Next, look closely at the formatting of the article. Research papers are divided into sections that occur in a particular order: abstract, introduction, methods, results, discussion, and references.

Let's take a closer look at this research paper by Bacon et al. published in the International Journal of Hypertension :

Review Papers

Review articles do not describe original research conducted by the author(s). Instead, they give an overview of a specific subject by examining previously published studies on the topic. The author searches for and selects studies on the subject and then tries to make sense of their findings. In particular, review articles look at whether the outcomes of the chosen studies are similar, and if they are not, attempt to explain the conflicting results. By interpreting the findings of previous studies, review articles are able to present the current knowledge and understanding of a specific topic.

Since review articles summarize the research on a particular topic, students should read them for background information before consulting detailed, technical research articles. Furthermore, review articles are a useful starting point for a research project because their reference lists can be used to find additional articles on the subject.

Let's take a closer look at this review paper by Bacon et al. published in Sports Medicine :

Systematic Review Papers

A systematic review is a type of review article that tries to limit the occurrence of bias. Traditional, non-systematic reviews can be biased because they do not include all of the available papers on the review’s topic; only certain studies are discussed by the author. No formal process is used to decide which articles to include in the review. Consequently, unpublished articles, older papers, works in foreign languages, manuscripts published in small journals, and studies that conflict with the author’s beliefs can be overlooked or excluded. Since traditional reviews do not have to explain the techniques used to select the studies, it can be difficult to determine if the author’s bias affected the review’s findings.

Systematic reviews were developed to address the problem of bias. Unlike traditional reviews, which cover a broad topic, systematic reviews focus on a single question, such as if a particular intervention successfully treats a medical condition. Systematic reviews then track down all of the available studies that address the question, choose some to include in the review, and critique them using predetermined criteria. The studies are found, selected, and evaluated using a formal, scientific methodology in order to minimize the effect of the author’s bias. The methodology is clearly explained in the systematic review so that readers can form opinions about the quality of the review.

Let's take a closer look this systematic review paper by Vigano et al. published in Lancet Oncology :

Finding Review and Research Papers in PubMed

Many databases have special features that allow the searcher to restrict results to articles that match specific criteria. In other words, only articles of a certain type will be displayed in the search results. These “limiters” can be useful when searching for research or review articles. PubMed has a limiter for article type, which is located on the left sidebar of the search results page. This limiter can filter the search results to show only review articles.

Home » Review Article vs Research Article

Review Article vs Research Article

Table of Contents

Review articles and Research Articles are two different types of scholarly publications that serve distinct purposes in the academic literature.

Research Articles

A Research Article is a primary source that presents original research findings based on a specific research question or hypothesis. These articles typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections. Research articles often include detailed descriptions of the research design, data collection and analysis procedures, and the results of statistical tests. These articles are typically peer-reviewed to ensure that they meet rigorous scientific standards before publication.

Review Articles

A Review Article is a secondary source that summarizes and analyzes existing research on a particular topic or research question. These articles provide an overview of the current state of knowledge on a particular topic, including a critical analysis of the strengths and limitations of previous research. Review articles often include a meta-analysis of the existing literature, which involves combining and analyzing data from multiple studies to draw more general conclusions about the research question or topic. Review articles are also typically peer-reviewed to ensure that they are comprehensive, accurate, and up-to-date.

Difference Between Review Article and Research Article

Here are some key differences between review articles and research articles:

Aspect	Research Article	Review Article
	Present original research findings based on a research question or hypothesis	Summarize and analyze existing research on a particular topic or research question
	Standard sections including an introduction, literature review, methodology, results, discussion, and conclusion	Depends on the journal and topic, but typically includes an introduction, methods, results, discussion, and conclusion
	Describe the research design, data collection and analysis procedures, and results of statistical tests	Describe the methodology used to identify and analyze the literature
	Statistical analysis of data	Meta-analysis or systematic review of existing literature
	Presents original data collected through research	Does not present original data, but rather synthesizes and analyzes existing data
	Based on the results of the research conducted	Based on the analysis of existing literature
	Peer-reviewed to ensure that they meet rigorous scientific standards before publication	Peer-reviewed to ensure that they are comprehensive, accurate, and up-to-date

In summary, research articles and review articles serve different purposes in the academic literature. Research articles present original research findings based on a specific research question or hypothesis, while review articles summarize and analyze existing research on a particular topic or research question. Both types of articles are typically peer-reviewed to ensure that they meet high standards of scientific rigor and accuracy.

Also see Research Methods

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Q. What's the difference between a research article and a review article?

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Answered By: Sarah Naomi Campbell Last Updated: Sep 07, 2018 Views: 216139

Watch this short video to learn about types of scholarly articles, including research articles and literature reviews!

Not in the mood for a video? Read on!

What's the difference between a research article and a review article?

Research articles , sometimes referred to as empirical or primary sources , report on original research. They will typically include sections such as an introduction, methods, results, and discussion.

Here is a more detailed explanation of research articles .

Review articles , sometimes called literature reviews or secondary sources , synthesize or analyze research already conducted in primary sources. They generally summarize the current state of research on a given topic.

Here is a more detailed explanation of review articles .

The video above was created by the Virginia Commonwealth University Libraries .

The defintions, and the linked detailed explanations, are paraphrased from the Publication Manual of the American Psychological Association , 6th ed .

The linked explanations are provided by the Mohawk Valley Community College Libraries .

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What are the differences between these kinds of articles: original, review, letter, and short communication?

I am interested in knowing, what are the differences between Original Paper, Review Paper, Letter and Short/ Rapid/ Brief Communication paper?

Thanks to everyone for reading and taking the time for the great responses.

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2 Bear in mind that this will vary heavily between specific journals. – Andrew is gone Commented Nov 29, 2015 at 13:20
2 Most respected journals have specific authors instructions which guide you in defining these types of manuscripts. In clinical medicine there are also explicit reporting guidelines: equator-network.org – Giuseppe Biondi-Zoccai Commented Feb 2, 2017 at 13:35

5 Answers 5

This will vary pretty heavily depending on the journal in question. But generally speaking, in broad strokes:

"Original Paper" - This is a generic term for a full-length, original research finding paper that doesn't fall into another specialized category.
"Review Paper" - This is a paper summarizing the state of research on a topic. These can often be somewhat long, are often but not always by invitation only, and this category can include meta-analysis, but doesn't have to. This may also be the umbrella that commentaries fall under, but again, not always.
"Short/Rapid/Brief Communication" - A shorter version of "Original Paper", whose methods, findings, etc. don't justify a full length paper. They still contain original findings, but are general much more straightforward.
Letters - Possibly even shorter original findings, field reports, single observations, etc. This can also include arguments about previously published papers, which involve either opinion pieces or snippets of contradictory or supporting research.

1 Note that for Nature, a Brief Communication Arising is not a research paper but usually critical comments on a Nature paper, typically accompanied by a response from the authors of the criticized paper. This is in contrast to a Letter , which is simply a short research paper. – Bitwise Commented Feb 2, 2017 at 14:15

"Original paper" is any research paper not falling into below categories. "Review paper" is that reporting a critical overview of recent articles in the field, can be very long, say, 30-40 journal pages. "Letter" is a short research paper, ca. 4 journal pages. "Communication" is essentially the same as "Letter", sporadically can contain comments (there is a specific genre called "Comments" as well) on some recently published paper in this journal.

Original research articles are detailed studies reporting original research conducted by the author. They include hypothesis, background study, methods, results, interpretation of findings, and a discussion of possible implications.

Review articles give an overview of existing literature in a field, often identifying specific problems or issues and analysing information from available published work on the topic with a balanced perspective. Review articles can be of three types, broadly speaking: literature reviews, systematic reviews, and meta-analyses.

Short communications are usually a concise format used to report significant improvements to existing methods, a new practical application, or a new tool or resource. These need to be reported quickly as the need to communicate such findings is very high.

Letters are usually short and flexible articles that express readers' opinion on previously published articles, or provide evidence to support/oppose an existing viewpoint.

Downvoter: why? – Andrew Commented May 29, 2018 at 18:30

Original papers are extracted from researches that are innovative enough and have new and important achievements. All of d etails are given in these papers. They also have high scientific value.

Original artical is under good headings ,all headings that must be present in every original paper but review sometime have some heading missed like materials and methods but not always happen this ,the main difference is that study is rational , different areas result collecting together .The size of review artical is longer than original one.the short communication have not headings properly but all aspects are clear properly it is much comprehensive.

1 I recommend you to expand your answer and provide some references... typically authors instructions of journals provide clear guidance on this issue. – Giuseppe Biondi-Zoccai Commented Feb 2, 2017 at 13:34

You must log in to answer this question.

Not the answer you're looking for browse other questions tagged publications terminology review-articles ..

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New research shows why arctic streams are turning orange, in the pristine brooks range in arctic alaska, streams are turning bright orange and fish are disappearing, threatening the well-being of local communities. a recent scientific paper reveals why..

By Nina Chambers

Image credit: U.S. Geological Survey / Josh Koch

The Arctic is warming much faster than the global average, and it’s altering terrestrial and aquatic ecosystems . Warmer temperatures are causing permafrost to thaw and release substances that have been locked in the frozen ground for thousands of years. For some compounds, such as the greenhouse gases carbon dioxide and methane, their release is largely invisible. But recent releases are very visible: streams in Arctic Alaska’s Brooks Range have turned bright orange. A recent paper in Nature Communications Earth & Environment describes how this is occurring and what it means to people who live in this remote region.

“We first noticed an orange stream in 2018 during regular Arctic stream monitoring ,” said Jon O’Donnell, lead author and ecologist for the National Park Service’s Arctic Inventory & Monitoring Network. “We thought it was anomalous and set out to learn everything we could about what was happening and why.” O’Donnell and other scientists from the National Park Service, U.S. Geological Survey, and several universities have since found many more streams that have turned orange across the Arctic. As this was not an isolated event, they wanted to understand the cause of the color change, when streams started to change, and the effect on aquatic ecosystems.

Determining the Extent of the Problem

The Arctic Network consists of over 19 million acres of parklands—about a quarter of the total land area in the National Park System. Within that area, network ecologists conduct site visits to monitor a relatively small number of streams and rivers for changes in their chemistry and biology. To document the scope of the problem, O’Donnell and colleagues began by crowd-sourcing observations from bush pilots, wilderness guides, other scientists, and rural and Indigenous communities. Through this process, they compiled observations of more than 75 orange streams that span more than 600 miles (1,000 km) of remote terrain in Alaska’s Brooks Range.

They were able to document that streams changed color in the last decade during a period of rapid warming and permafrost thaw.

The next step was to determine when the streams turned orange, and to do that, the authors turned to satellite imagery. They collected satellite images of the area taken from 1985 to 2022, between the months of July and August, and when cloud cover was less than 30 percent. For three sites where they had conducted visits, they used the satellite images to calculate a Redness Index for each scene, removing any images that had smoke from wildfires. They identified a value of 1.5 as the threshold for when water changes from clear to orange/red.

Image credit: NPS / Ken Hill

By looking at Redness Index values over time, they were able to document that streams changed color in the last decade during a period of rapid warming and permafrost thaw . A more general review of satellite imagery across the region supported these findings, indicating that most orange streams were clear up until the last decade. “We selected study sites where streams had recently changed from clear to orange based on both the crowd-sourced observations and satellite analyses,” said O’Donnell. “From that, we also selected sites that are relatively easy to access from hub communities like Kotzebue.” Some satellite images indicated downstream shifts from orange to clear. More research could help scientists understand why.

“We lucked out by having biological data before and after that stream changed color, so we were able to directly assess impact to aquatic life.”

Between June and September 2022, O’Donnell and fellow scientists measured the chemistry of both orange streams and nearby clearwater streams, including metal concentrations, pH (or degree of acidity), temperature, and other factors. They compared water chemistry, aquatic invertebrates, and fish before and after stream discoloration, based on years of monitoring data. This enabled them to determine how biological systems were being affected. “We had been monitoring a small stream in the Akillik River basin in Kobuk Valley National Park, starting in 2017,” O’Donnell recalled. “During a 2018 site visit, we noticed that this stream had changed from clear to orange. In a way, we lucked out by having biological data before and after that stream changed color, so we were able to directly assess impact to aquatic life.”

Rivers Are Rusting

O’Donnell and his colleagues found high levels of iron, nickel, zinc, cadmium, and copper in affected waters, although oxidized iron is what’s turning them orange. Movement of metals from thawed ground to water may cause a loss of habitat for important subsistence fish species like Dolly Varden, chum salmon, and whitefish. The metals transported downstream from headwater streams to larger rivers could also contaminate drinking water supplies for nearby villages.

Image credit: O'Donnell et al., Communications Earth & Environment, 2024. Illustration by Julia Ditto.

Narrative description of "possible factors" illustration

This image is a detailed illustration of possible factors leading to the discoloration of Arctic streams, and their consequences. Several rectangular sections are overlaid on an illustration of an arctic stream flowing down from the mountains into lowlands, ending in a cross-sectional view of the stream and surrounding soils.

Upper Part of the Illustration

Common biota of arctic streams (top left).

This rectangular section has three smaller sections showing different arctic stream organisms: First is algae, illustrated by a light green tuft. An arrow leads from this section into the next, which depicts macroinvertebrates: mayflies, stoneflies, midges, craneflies, and snails. An arrow leads from this section to the third section, which shows three species of fish: dolly varden ( Salvelinus malma ), chum salmon ( Oncorhynchus keta ), and Arctic grayling ( Thymallus arcticus ).

Upland Processes (top right)

This rectangular section depicts processes associated with the higher reaches of the stream and points to an illustration of a mountain stream.

Text reads: As permafrost thaws by active layer thickening, sulfide minerals (e.g., pyrite) are exposed to chemical weathering, releasing sulfate, acid, and trace metals into groundwater and streams.

A diagram below shows an upland stream cross-section, clear on the left, and orange on the right. There's pyrite in the permafrost on both sides, but on the orange side, more of the surface has thawed and part of the pyrite is shown leaching into the stream with flowing groundwater, blanketing the bottom with an iron (III) particulate layer. On the clear side, the groundwater is restricted to above the pyrite, and flows cleanly into the stream, which has a layer of algae present on the bottom.

Middle Part of the Illustration

Point source.

This rectangular section points to an illustration of a patch of dead vegetation in the lowland, just upslope of the stream.

Text reads: Point sources of acidic water can occur through groundwater seeps that emerge at the ground surface, likely through thermokarst processes. In some cases, this acidic water can kill tundra and boreal vegetation.

( Thermokarst is a process that occurs when ice-rich permafrost thaws, creating distinct landforms like hummocks and hollows .)

Water Quality

This rectangular section points to an illustration of a cross section of the stream.

Text reads: Orange stream reaches are more turbid, acidic, and have higher concentrations of iron particulates and other trace metals than nearby clearwater streams. Stream beds are typically blanketed with precipitated iron minerals that can impact the benthic aquatic food web.

Lower Part of the Illustration

This part depicts processes associated with the lower reaches of the stream.

Lowland Processes (bottom left)

This rectangular section points to an illustration of a cross section of lowland soils beside the stream, where groundwater is shown flowing through saturated soils above a permafrost layer, leaching orange water into the stream.

Text reads: Permafrost thaw can result in wetter soils and the release of iron from previously frozen soil. Under these conditions, iron is reduced to the highly mobile dissolved iron(II) ion, which can be transported by groundwater to streams.

Human Implications (bottom left)

This rectangular section has two numbered parts:

1. Drinking Water

Text reads: Downstream communities that rely on rivers for domestic use, including drinking water, may be impacted by iron and trace metal mobilization.An illustration to the right of the text depicts an orange water droplet falling from a faucet into a glass of water.

2. Subsistence Fishing

Text reads: Orange streams may impact subsistence fisheries through the accumulation of toxins in fish species, the loss of habitat, and degraded spawning grounds.

An illustration to the right of the text depicts a person in a small boat pulling up a fishing net with a fish in it.

Impacts to Aquatic Food Webs (bottom right)

This rectangular section points to an illustration of the lower waters of the stream and a fish. It has three numbered parts:

1. Direct uptake of trace metals by fish from the water column.

An illustration to the right of the text depicts a cluster of orange dots with a curved arrow pointing at a drawing of a salmon.

2. Bioaccumulation of toxic metals in an organism with time

An illustration below the text depicts, from left to right, algae, a mayfly larva, and a fish. Each organism depicted has orange dots in or on it, with arrows pointing to the next organism.

3. Ecosystem contraction , resulting in loss of habitat due to degraded conditions

An illustration below the text depicts the same as above, but with "not" icons (circles with slashes) over the larva and the fish.

“This kind of acid rock drainage is what you expect to see at a mining site, not in the remote and pristine Brooks Range.”

In recent years, Arctic air and ground temperatures have abruptly increased compared to the preceding 30-year record, exceeding the freezing threshold for near-surface permafrost. Thawing permafrost can alter stream chemistry through changes in watershed vegetation, soil, and topography . More water reaching deeper in the ground unlocks minerals and exposes them to microbes and weathering. The weathering of sulfide minerals like pyrite releases acid, iron, sulfate, and potentially toxic metals to streams and rivers, which discolor the water and displace fish . “This kind of acid rock drainage is what you expect to see at a mining site, not in the remote and pristine Brooks Range in Alaska<,” said Brett Poulin, assistant professor in Environmental Toxicology, University of California-Davis, and a co-author of the paper.

Why This Is Important

Arctic rivers support many types of fish used by subsistence harvesters, recreational anglers, and commercial fisheries. These fish are already suffering the effects of climate change . Metal release due to thawing permafrost is one more stressor. When the Akillik River changed color from clear in 2017 to orange in 2018—and when the stream pH suddenly dropped and metal concentrations increased—it completely lost two fish species, juvenile Dolly Varden and slimy sculpin. Aquatic invertebrates also declined.

Impaired streams from metal contaminants are a serious problem for nearby villages.

Although arsenic and lead did not exceed EPA or World Health Organization recommendations in study streams, the researchers found concentrations of cadmium, nickel, and manganese that did. Impaired streams from metal contaminants are a serious problem for nearby villages. Metal contamination from this naturally occurring leaching process extends the problem to a large area.

Arctic rivers are ever-changing ecosystems. The specific causes and long-term consequences of their impairment remain to be discovered. “We are still learning about what makes certain rivers vulnerable to rusting, as the underlying causes are complex,” said O’Donnell. But this study will help scientists, parks, and communities understand why rivers are turning orange. It gives us a better idea of how big the problem is and how far it has spread. With further research, it could also help determine how long the discoloration might last .

Portrait of Chambers in an olive green beanie and a black puffy jacket by a river, smiling for the camera.

About the author

Neural general circulation models for weather and climate

Dmitrii Kochkov ORCID: orcid.org/0000-0003-3846-4911 1 na1 ,
Janni Yuval ORCID: orcid.org/0000-0001-7519-0118 1 na1 ,
Ian Langmore 1 na1 ,
Peter Norgaard 1 na1 ,
Jamie Smith 1 na1 ,
Griffin Mooers 1 ,
Milan Klöwer 2 ,
James Lottes 1 ,
Stephan Rasp 1 ,
Peter Düben ORCID: orcid.org/0000-0002-4610-3326 3 ,
Sam Hatfield 3 ,
Peter Battaglia 4 ,
Alvaro Sanchez-Gonzalez 4 ,
Matthew Willson ORCID: orcid.org/0000-0002-8730-1927 4 ,
Michael P. Brenner 1 , 5 &
Stephan Hoyer ORCID: orcid.org/0000-0002-5207-0380 1 na1

Nature volume 632 , pages 1060–1066 ( 2024 ) Cite this article

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Atmospheric dynamics
Climate and Earth system modelling
Computational science

General circulation models (GCMs) are the foundation of weather and climate prediction 1 , 2 . GCMs are physics-based simulators that combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes such as cloud formation. Recently, machine-learning models trained on reanalysis data have achieved comparable or better skill than GCMs for deterministic weather forecasting 3 , 4 . However, these models have not demonstrated improved ensemble forecasts, or shown sufficient stability for long-term weather and climate simulations. Here we present a GCM that combines a differentiable solver for atmospheric dynamics with machine-learning components and show that it can generate forecasts of deterministic weather, ensemble weather and climate on par with the best machine-learning and physics-based methods. NeuralGCM is competitive with machine-learning models for one- to ten-day forecasts, and with the European Centre for Medium-Range Weather Forecasts ensemble prediction for one- to fifteen-day forecasts. With prescribed sea surface temperature, NeuralGCM can accurately track climate metrics for multiple decades, and climate forecasts with 140-kilometre resolution show emergent phenomena such as realistic frequency and trajectories of tropical cyclones. For both weather and climate, our approach offers orders of magnitude computational savings over conventional GCMs, although our model does not extrapolate to substantially different future climates. Our results show that end-to-end deep learning is compatible with tasks performed by conventional GCMs and can enhance the large-scale physical simulations that are essential for understanding and predicting the Earth system.

Accurate medium-range global weather forecasting with 3D neural networks

Deep learning for twelve hour precipitation forecasts

Skilful predictions of the Asian summer monsoon one year ahead

Solving the equations for Earth’s atmosphere with general circulation models (GCMs) is the basis of weather and climate prediction 1 , 2 . Over the past 70 years, GCMs have been steadily improved with better numerical methods and more detailed physical models, while exploiting faster computers to run at higher resolution. Inside GCMs, the unresolved physical processes such as clouds, radiation and precipitation are represented by semi-empirical parameterizations. Tuning GCMs to match historical data remains a manual process 5 , and GCMs retain many persistent errors and biases 6 , 7 , 8 . The difficulty of reducing uncertainty in long-term climate projections 9 and estimating distributions of extreme weather events 10 presents major challenges for climate mitigation and adaptation 11 .

Recent advances in machine learning have presented an alternative for weather forecasting 3 , 4 , 12 , 13 . These models rely solely on machine-learning techniques, using roughly 40 years of historical data from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5) 14 for model training and forecast initialization. Machine-learning methods have been remarkably successful, demonstrating state-of-the-art deterministic forecasts for 1- to 10-day weather prediction at a fraction of the computational cost of traditional models 3 , 4 . Machine-learning atmospheric models also require considerably less code, for example GraphCast 3 has 5,417 lines versus 376,578 lines for the National Oceanic and Atmospheric Administration’s FV3 atmospheric model 15 (see Supplementary Information section A for details).

Nevertheless, machine-learning approaches have noteworthy limitations compared with GCMs. Existing machine-learning models have focused on deterministic prediction, and surpass deterministic numerical weather prediction in terms of the aggregate metrics for which they are trained 3 , 4 . However, they do not produce calibrated uncertainty estimates 4 , which is essential for useful weather forecasts 1 . Deterministic machine-learning models using a mean-squared-error loss are rewarded for averaging over uncertainty, producing unrealistically blurry predictions when optimized for multi-day forecasts 3 , 13 . Unlike physical models, machine-learning models misrepresent derived (diagnostic) variables such as geostrophic wind 16 . Furthermore, although there has been some success in using machine-learning approaches on longer timescales 17 , 18 , these models have not demonstrated the ability to outperform existing GCMs.

Hybrid models that combine GCMs with machine learning are appealing because they build on the interpretability, extensibility and successful track record of traditional atmospheric models 19 , 20 . In the hybrid model approach, a machine-learning component replaces or corrects the traditional physical parameterizations of a GCM. Until now, the machine-learning component in such models has been trained ‘offline’, by learning parameterizations independently of their interaction with dynamics. These components are then inserted into an existing GCM. The lack of coupling between machine-learning components and the governing equations during training potentially causes serious problems, such as instability and climate drift 21 . So far, hybrid models have mostly been limited to idealized scenarios such as aquaplanets 22 , 23 . Under realistic conditions, machine-learning corrections have reduced some biases of very coarse GCMs 24 , 25 , 26 , but performance remains considerably worse than state-of-the-art models.

Here we present NeuralGCM, a fully differentiable hybrid GCM of Earth’s atmosphere. NeuralGCM is trained on forecasting up to 5-day weather trajectories sampled from ERA5. Differentiability enables end-to-end ‘online training’ 27 , with machine-learning components optimized in the context of interactions with the governing equations for large-scale dynamics, which we find enables accurate and stable forecasts. NeuralGCM produces physically consistent forecasts with accuracy comparable to best-in-class models across a range of timescales, from 1- to 15-day weather to decadal climate prediction.

Neural GCMs

A schematic of NeuralGCM is shown in Fig. 1 . The two key components of NeuralGCM are a differentiable dynamical core for solving the discretized governing dynamical equations and a learned physics module that parameterizes physical processes with a neural network, described in full detail in Methods , Supplementary Information sections B and C , and Supplementary Table 1 . The dynamical core simulates large-scale fluid motion and thermodynamics under the influence of gravity and the Coriolis force. The learned physics module (Supplementary Fig. 1 ) predicts the effect of unresolved processes, such as cloud formation, radiative transport, precipitation and subgrid-scale dynamics, on the simulated fields using a neural network.

a , Overall model structure, showing how forcings F t , noise z t (for stochastic models) and inputs y t are encoded into the model state x t . The model state is fed into the dynamical core, and alongside forcings and noise into the learned physics module. This produces tendencies (rates of change) used by an implicit–explicit ordinary differential equation (ODE) solver to advance the state in time. The new model state x t +1 can then be fed back into another time step, or decoded into model predictions. b , The learned physics module, which feeds data for individual columns of the atmosphere into a neural network used to produce physics tendencies in that vertical column.

The differentiable dynamical core in NeuralGCM allows an end-to-end training approach, whereby we advance the model multiple time steps before employing stochastic gradient descent to minimize discrepancies between model predictions and reanalysis (Supplementary Information section G.2 ). We gradually increase the rollout length from 6 hours to 5 days (Supplementary Information section G and Supplementary Table 5 ), which we found to be critical because our models are not accurate for multi-day prediction or stable for long rollouts early in training (Supplementary Information section H.6.2 and Supplementary Fig. 23 ). The extended back-propagation through hundreds of simulation steps enables our neural networks to take into account interactions between the learned physics and the dynamical core. We train deterministic and stochastic NeuralGCM models, each of which uses a distinct training protocol, described in full detail in Methods and Supplementary Table 4 .

We train a range of NeuralGCM models at horizontal resolutions with grid spacing of 2.8°, 1.4° and 0.7° (Supplementary Fig. 7 ). We evaluate the performance of NeuralGCM at a range of timescales appropriate for weather forecasting and climate simulation. For weather, we compare against the best-in-class conventional physics-based weather models, ECMWF’s high-resolution model (ECMWF-HRES) and ensemble prediction system (ECMWF-ENS), and two of the recent machine-learning-based approaches, GraphCast 3 and Pangu 4 . For climate, we compare against a global cloud-resolving model and Atmospheric Model Intercomparison Project (AMIP) runs.

Medium-range weather forecasting

Our evaluation set-up focuses on quantifying accuracy and physical consistency, following WeatherBench2 12 . We regrid all forecasts to a 1.5° grid using conservative regridding, and average over all 732 forecasts made at noon and midnight UTC in the year 2020, which was held-out from training data for all machine-learning models. NeuralGCM, GraphCast and Pangu compare with ERA5 as the ground truth, whereas ECMWF-ENS and ECMWF-HRES compare with the ECMWF operational analysis (that is, HRES at 0-hour lead time), to avoid penalizing the operational forecasts for different biases than ERA5.

Model accuracy

We use ECMWF’s ensemble (ENS) model as a reference baseline as it achieves the best performance across the majority of lead times 12 . We assess accuracy using (1) root-mean-squared error (RMSE), (2) root-mean-squared bias (RMSB), (3) continuous ranked probability score (CRPS) and (4) spread-skill ratio, with the results shown in Fig. 2 . We provide more in-depth evaluations including scorecards, metrics for additional variables and levels and maps in Extended Data Figs. 1 and 2 , Supplementary Information section H and Supplementary Figs. 9 – 22 .

a , c , RMSE ( a ) and RMSB ( c ) for ECMWF-ENS, ECMWF-HRES, NeuralGCM-0.7°, NeuralGCM-ENS, GraphCast 3 and Pangu 4 on headline WeatherBench2 variables, as a percentage of the error of ECMWF-ENS. Deterministic and stochastic models are shown in solid and dashed lines respectively. e , g , CRPS relative to ECMWF-ENS ( e ) and spread-skill ratio for the ENS and NeuralGCM-ENS models ( g ). b , d , f , h , Spatial distributions of RMSE ( b ), bias ( d ), CRPS ( f ) and spread-skill ratio ( h ) for NeuralGCM-ENS and ECMWF-ENS models for 10-day forecasts of specific humidity at 700 hPa. Spatial plots of RMSE and CRPS show skill relative to a probabilistic climatology 12 with an ensemble member for each of the years 1990–2019. The grey areas indicate regions where climatological surface pressure on average is below 700 hPa.

Deterministic models that produce a single weather forecast for given initial conditions can be compared effectively using RMSE skill at short lead times. For the first 1–3 days, depending on the atmospheric variable, RMSE is minimized by forecasts that accurately track the evolution of weather patterns. At this timescale we find that NeuralGCM-0.7° and GraphCast achieve best results, with slight variations across different variables (Fig. 2a ). At longer lead times, RMSE rapidly increases owing to chaotic divergence of nearby weather trajectories, making RMSE less informative for deterministic models. RMSB calculates persistent errors over time, which provides an indication of how models would perform at much longer lead times. Here NeuralGCM models also compare favourably against previous approaches (Fig. 2c ), with notably much less bias for specific humidity in the tropics (Fig. 2d ).

Ensembles are essential for capturing intrinsic uncertainty of weather forecasts, especially at longer lead times. Beyond about 7 days, the ensemble means of ECMWF-ENS and NeuralGCM-ENS forecasts have considerably lower RMSE than the deterministic models, indicating that these models better capture the average of possible weather. A better metric for ensemble models is CRPS, which is a proper scoring rule that is sensitive to full marginal probability distributions 28 . Our stochastic model (NeuralGCM-ENS) running at 1.4° resolution has lower error compared with ECMWF-ENS across almost all variables, lead times and vertical levels for ensemble-mean RMSE, RSMB and CRPS (Fig. 2a,c,e and Supplementary Information section H ), with similar spatial patterns of skill (Fig. 2b,f ). Like ECMWF-ENS, NeuralGCM-ENS has a spread-skill ratio of approximately one (Fig. 2d ), which is a necessary condition for calibrated forecasts 29 .

An important characteristic of forecasts is their resemblance to realistic weather patterns. Figure 3 shows a case study that illustrates the performance of NeuralGCM on three types of important weather phenomenon: tropical cyclones, atmospheric rivers and the Intertropical Convergence Zone. Figure 3a shows that all the machine-learning models make significantly blurrier forecasts than the source data ERA5 and physics-based ECMWF-HRES forecast, but NeuralCGM-0.7° outperforms the pure machine-learning models, despite its coarser resolution (0.7° versus 0.25° for GraphCast and Pangu). Blurry forecasts correspond to physically inconsistent atmospheric conditions and misrepresent extreme weather. Similar trends hold for other derived variables of meteorological interest (Supplementary Information section H.2 ). Ensemble-mean predictions, from both NeuralGCM and ECMWF, are closer to ERA5 in an average sense, and thus are inherently smooth at long lead times. In contrast, as shown in Fig. 3 and in Supplementary Information section H.3 , individual realizations from the ECMWF and NeuralGCM ensembles remain sharp, even at long lead times. Like ECMWF-ENS, NeuralGCM-ENS produces a statistically representative range of future weather scenarios for each weather phenomenon, despite its eight-times-coarser resolution.

All forecasts are initialized at 2020-08-22T12z, chosen to highlight Hurricane Laura, the most damaging Atlantic hurricane of 2020. a , Specific humidity at 700 hPa for 1-day, 5-day and 10-day forecasts over North America and the Northeast Pacific Ocean from ERA5 14 , ECMWF-HRES, NeuralGCM-0.7°, ECMWF-ENS (mean), NeuralGCM-ENS (mean), GraphCast 3 and Pangu 4 . b , Forecasts from individual ensemble members from ECMWF-ENS and NeuralGCM-ENS over regions of interest, including predicted tracks of Hurricane Laura from each of the 50 ensemble members (Supplementary Information section I.2 ). The track from ERA5 is plotted in black.

We can quantify the blurriness of different forecast models via their power spectra. Supplementary Figs. 17 and 18 show that the power spectra of NeuralCGM-0.7° is consistently closer to ERA5 than the other machine-learning forecast methods, but is still blurrier than ECMWF’s physical forecasts. The spectra of NeuralGCM forecasts is also roughly constant over the forecast period, in stark contrast to GraphCast, which worsens with lead time. The spectrum of NeuralGCM becomes more accurate with increased resolution (Supplementary Fig. 22 ), which suggests the potential for further improvements of NeuralGCM models trained at higher resolutions.

Water budget

In NeuralGCM, advection is handled by the dynamical core, while the machine-learning parameterization models local processes within vertical columns of the atmosphere. Thus, unlike pure machine-learning methods, local sources and sinks can be isolated from tendencies owing to horizontal transport and other resolved dynamics (Supplementary Fig. 3 ). This makes our results more interpretable and facilitates the diagnosis of the water budget. Specifically, we diagnose precipitation minus evaporation (Supplementary Information section H.5 ) rather than directly predicting these as in machine-learning-based approaches 3 . For short weather forecasts, the mean of precipitation minus evaporation has a realistic spatial distribution that is very close to ERA5 data (Extended Data Fig. 4c–e ). The precipitation-minus-evaporation rate distribution of NeuralGCM-0.7° closely matches the ERA5 distribution in the extratropics (Extended Data Fig. 4b ), although it underestimates extreme events in the tropics (Extended Data Fig. 4a ). It is noted that the current version of NeuralGCM directly predicts tendencies for an atmospheric column, and thus cannot distinguish between precipitation and evaporation.

Geostrophic wind balance

We examined the extent to which NeuralGCM, GraphCast and ECMWF-HRES capture the geostrophic wind balance, the near-equilibrium between the dominant forces that drive large-scale dynamics in the mid-latitudes 30 . A recent study 16 highlighted that Pangu misrepresents the vertical structure of the geostrophic and ageostrophic winds and noted a deterioration at longer lead times. Similarly, we observe that GraphCast shows an error that worsens with lead time. In contrast, NeuralGCM more accurately depicts the vertical structure of the geostrophic and ageostrophic winds, as well as their ratio, compared with GraphCast across various rollouts, when compared against ERA5 data (Extended Data Fig. 3 ). However, ECMWF-HRES still shows a slightly closer alignment to ERA5 data than NeuralGCM does. Within NeuralGCM, the representation of the geostrophic wind’s vertical structure only slightly degrades in the initial few days, showing no noticeable changes thereafter, particularly beyond day 5.

Generalizing to unseen data

Physically consistent weather models should still perform well for weather conditions for which they were not trained. We expect that NeuralGCM may generalize better than machine-learning-only atmospheric models, because NeuralGCM employs neural networks that act locally in space, on individual vertical columns of the atmosphere. To explore this hypothesis, we compare versions of NeuralCGM-0.7° and GraphCast trained to 2017 on 5 years of weather forecasts beyond the training period (2018–2022) in Supplementary Fig. 36 . Unlike GraphCast, NeuralGCM does not show a clear trend of increasing error when initialized further into the future from the training data. To extend this test beyond 5 years, we trained a NeuralGCM-2.8° model using only data before 2000, and tested its skill for over 21 unseen years (Supplementary Fig. 35 ).

Climate simulations

Although our deterministic NeuralGCM models are trained to predict weather up to 3 days ahead, they are generally capable of simulating the atmosphere far beyond medium-range weather timescales. For extended climate simulations, we prescribe historical sea surface temperature (SST) and sea-ice concentration. These simulations feature many emergent phenomena of the atmosphere on timescales from months to decades.

For climate simulations with NeuralGCM, we use 2.8° and 1.4° deterministic models, which are relatively inexpensive to train (Supplementary Information section G.7 ) and allow us to explore a larger parameter space to find stable models. Previous studies found that running extended simulations with hybrid models is challenging due to numerical instabilities and climate drift 21 . To quantify stability in our selected models, we run multiple initial conditions and report how many of them finish without instability.

Seasonal cycle and emergent phenomena

To assess the capability of NeuralGCM to simulate various aspects of the seasonal cycle, we run 2-year simulations with NeuralGCM-1.4°. for 37 different initial conditions spaced every 10 days for the year 2019. Out of these 37 initial conditions, 35 successfully complete the full 2 years without instability; for case studies of instability, see Supplementary Information section H.7 , and Supplementary Figs. 26 and 27 . We compare results from NeuralGCM-1.4° for 2020 with ERA5 data and with outputs from the X-SHiELD global cloud-resolving model, which is coupled to an ocean model nudged towards reanalysis 31 . This X-SHiELD run has been used as a target for training machine-learning climate models 24 . For comparison, we evaluate models after regridding predictions to 1.4° resolution. This comparison slightly favours NeuralGCM because NeuralGCM was tuned to match ERA5, but the discrepancy between ERA5 and the actual atmosphere is small relative to model error.

Figure 4a shows the temporal variation of the global mean temperature to 2020, as captured by 35 simulations from NeuralGCM, in comparison with the ERA5 reanalysis and standard climatology benchmarks. The seasonality and variability of the global mean temperature from NeuralGCM are quantitatively similar to those observed in ERA5. The ensemble-mean temperature RMSE for NeuralGCM stands at 0.16 K when benchmarked against ERA5, which is a significant improvement over the climatology’s RMSE of 0.45 K. We find that NeuralGCM accurately simulates the seasonal cycle, as evidenced by metrics such as the annual cycle of the global precipitable water (Supplementary Fig. 30a ) and global total kinetic energy (Supplementary Fig. 30b ). Furthermore, the model captures essential atmospheric dynamics, including the Hadley circulation and the zonal-mean zonal wind (Supplementary Fig. 28 ), as well as the spatial patterns of eddy kinetic energy in different seasons (Supplementary Fig. 31 ), and the distinctive seasonal behaviours of monsoon circulation (Supplementary Fig. 29 ; additional details are provided in Supplementary Information section I.1 ).

a , Global mean temperature for ERA5 14 (orange), 1990–2019 climatology (black) and NeuralGCM-1.4° (blue) for 2020 using 35 simulations initialized every 10 days during 2019 (thick line, ensemble mean; thin lines, different initial conditions). b , Yearly global mean temperature for ERA5 (orange), mean over 22 CMIP6 AMIP experiments 34 (violet; model details are in Supplementary Information section I.3 ) and NeuralGCM-2.8° for 22 AMIP-like simulations with prescribed SST initialized every 10 days during 1980 (thick line, ensemble mean; thin lines, different initial conditions). c , The RMSB of the 850-hPa temperature averaged between 1981 and 2014 for 22 NeuralGCM-2.8° AMIP runs (labelled NGCM), 22 CMIP6 AMIP experiments (labelled AMIP) and debiased 22 CMIP6 AMIP experiments (labelled AMIP*; bias was removed by removing the 850-hPa global temperature bias). In the box plots, the red line represents the median. The box delineates the first to third quartiles; the whiskers extend to 1.5 times the interquartile range (Q1 − 1.5IQR and Q3 + 1.5IQR), and outliers are shown as individual dots. d , Vertical profiles of tropical (20° S–20° N) temperature trends for 1981–2014. Orange, ERA5; black dots, Radiosonde Observation Correction using Reanalyses (RAOBCORE) 41 ; blue dots, mean trends for NeuralGCM; purple dots, mean trends from CMIP6 AMIP runs (grey and black whiskers, 25th and 75th percentiles for NeuralGCM and CMIP6 AMIP runs, respectively). e – g , Tropical cyclone tracks for ERA5 ( e ), NeuralGCM-1.4° ( f ) and X-SHiELD 31 ( g ). h – k , Mean precipitable water for ERA5 ( h ) and the precipitable water bias in NeuralGCM-1.4° ( i ), initialized 90 days before mid-January 2020 similarly to X-SHiELD, X-SHiELD ( j ) and climatology ( k ; averaged between 1990 and 2019). In d – i , quantities are calculated between mid-January 2020 and mid-January 2021 and all models were regridded to a 256 × 128 Gaussian grid before computation and tracking.

Next, we compare the annual biases of a single NeuralGCM realization with a single realization of X-SHiELD (the only one available), both initiated in mid-October 2019. We consider 19 January 2020 to 17 January 2021, the time frame for which X-SHiELD data are available. Global cloud-resolving models, such as X-SHiELD, are considered state of the art, especially for simulating the hydrological cycle, owing to their resolution being capable of resolving deep convection 32 . The annual bias in precipitable water for NeuralGCM (RMSE of 1.09 mm) is substantially smaller than the biases of both X-SHiELD (RMSE of 1.74 mm) and climatology (RMSE of 1.36 mm; Fig. 4i–k ). Moreover, NeuralGCM shows a lower temperature bias in the upper and lower troposphere than X-SHiELD (Extended Data Fig. 6 ). We also indirectly compare precipitation bias in X-SHiELD with precipitation-minus-evaporation bias in NeuralGCM-1.4°, which shows slightly larger bias and grid-scale artefacts for NeuralGCM (Extended Data Fig. 5 ).

Finally, to assess the capability of NeuralGCM to generate tropical cyclones in an annual model integration, we use the tropical cyclone tracker TempestExtremes 33 , as described in Supplementary Information section I.2 , Supplementary Fig. 34 and Supplementary Table 6 . Figure 4e–g shows that NeuralGCM, even at a coarse resolution of 1.4°, produces realistic trajectories and counts of tropical cyclone (83 versus 86 in ERA5 for the corresponding period), whereas X-SHiELD, when regridded to 1.4° resolution, substantially underestimates the tropical cyclone count (40). Additional statistical analyses of tropical cyclones can be found in Extended Data Figs. 7 and 8 .

Decadal simulations

To assess the capability of NeuralGCM to simulate historical temperature trends, we conduct AMIP-like simulations over a duration of 40 years with NeuralGCM-2.8°. Out of 37 different runs with initial conditions spaced every 10 days during the year 1980, 22 simulations were stable for the entire 40-year period, and our analysis focuses on these results. We compare with 22 simulations run with prescribed SST from the Coupled Model Intercomparison Project Phase 6 (CMIP6) 34 , listed in Supplementary Information section I.3 .

We find that all 40-year simulations of NeuralGCM, as well as the mean of the 22 AMIP runs, accurately capture the global warming trends observed in ERA5 data (Fig. 4b ). There is a strong correlation in the year-to-year temperature trends with ERA5 data, suggesting that NeuralGCM effectively captures the impact of SST forcing on climate. When comparing spatial biases averaged over 1981–2014, we find that all 22 NeuralGCM-2.8° runs have smaller bias than the CMIP6 AMIP runs, and this result remains even when removing the global temperature bias in CMIP6 AMIP runs (Fig. 4c and Supplementary Figs. 32 and 33 ).

Next, we investigated the vertical structure of tropical warming trends, which climate models tend to overestimate in the upper troposphere 35 . As shown in Fig. 4d , the trends, calculated by linear regression, of NeuralGCM are closer to ERA5 than those of AMIP runs. In particular, the bias in the upper troposphere is reduced. However, NeuralGCM does show a wider spread in its predictions than the AMIP runs, even at levels near the surface where temperatures are typically more constrained by prescribed SST.

Lastly, we evaluated NeuralGCM’s capability to generalize to unseen warmer climates by conducting AMIP simulations with increased SST (Supplementary Information section I.4.2 ). We find that NeuralGCM shows some of the robust features of climate warming response to modest SST increases (+1 K and +2 K); however, for more substantial SST increases (+4 K), NeuralGCM’s response diverges from expectations (Supplementary Fig. 37 ). In addition, AMIP simulations with increased SST show climate drift, underscoring NeuralGCM’s limitations in this context (Supplementary Fig. 38 ).

NeuralGCM is a differentiable hybrid atmospheric model that combines the strengths of traditional GCMs with machine learning for weather forecasting and climate simulation. To our knowledge, NeuralGCM is the first machine-learning-based model to make accurate ensemble weather forecasts, with better CRPS than state-of-the-art physics-based models. It is also, to our knowledge, the first hybrid model that achieves comparable spatial bias to global cloud-resolving models, can simulate realistic tropical cyclone tracks and can run AMIP-like simulations with realistic historical temperature trends. Overall, NeuralGCM demonstrates that incorporating machine learning is a viable alternative to building increasingly detailed physical models 32 for improving GCMs.

Compared with traditional GCMs with similar skill, NeuralGCM is computationally efficient and low complexity. NeuralGCM runs at 8- to 40-times-coarser horizontal resolution than ECMWF’s Integrated Forecasting System and global cloud-resolving models, which enables 3 to 5 orders of magnitude savings in computational resources. For example, NeuralGCM-1.4° simulates 70,000 simulation days in 24 hours using a single tensor-processing-unit versus 19 simulated days on 13,824 central-processing-unit cores with X-SHiELD (Extended Data Table 1 ). This can be leveraged for previously impractical tasks such as large ensemble forecasting. NeuralGCM’s dynamical core uses global spectral methods 36 , and learned physics is parameterized with fully connected neural networks acting on single vertical columns. Substantial headroom exists to pursue higher accuracy using advanced numerical methods and machine-learning architectures.

Our results provide strong evidence for the disputed hypothesis 37 , 38 , 39 that learning to predict short-term weather is an effective way to tune parameterizations for climate. NeuralGCM models trained on 72-hour forecasts are capable of realistic multi-year simulation. When provided with historical SSTs, they capture essential atmospheric dynamics such as seasonal circulation, monsoons and tropical cyclones. However, we will probably need alternative training strategies 38 , 39 to learn important processes for climate with subtle impacts on weather timescales, such as a cloud feedback.

The NeuralGCM approach is compatible with incorporating either more physics or more machine learning, as required for operational weather forecasts and climate simulations. For weather forecasting, we expect that end-to-end learning 40 with observational data will allow for better and more relevant predictions, including key variables such as precipitation. Such models could include neural networks acting as corrections to traditional data assimilation and model diagnostics. For climate projection, NeuralGCM will need to be reformulated to enable coupling with other Earth-system components (for example, ocean and land), and integrating data on the atmospheric chemical composition (for example, greenhouse gases and aerosols). There are also research challenges common to current machine-learning-based climate models 19 , including the capability to simulate unprecedented climates (that is, generalization), adhering to physical constraints, and resolving numerical instabilities and climate drift. NeuralGCM’s flexibility to incorporate physics-based models (for example, radiation) offers a promising avenue to address these challenges.

Models based on physical laws and empirical relationships are ubiquitous in science. We believe the differentiable hybrid modelling approach of NeuralGCM has the potential to transform simulation for a wide range of applications, such as materials discovery, protein folding and multiphysics engineering design.

Differentiable atmospheric model

NeuralGCM combines components of the numerical solver and flexible neural network parameterizations. Simulation in time is carried out in a coordinate system suitable for solving the dynamical equations of the atmosphere, describing large-scale fluid motion and thermodynamics under the influence of gravity and the Coriolis force.

Our differentiable dynamical core is implemented in JAX, a library for high-performance code in Python that supports automatic differentiation 42 . The dynamical core solves the hydrostatic primitive equations with moisture, using a horizontal pseudo-spectral discretization and vertical sigma coordinates 36 , 43 . We evolve seven prognostic variables: vorticity and divergence of horizontal wind, temperature, surface pressure, and three water species (specific humidity, and specific ice and liquid cloud water content).

Our learned physics module uses the single-column approach of GCMs 2 , whereby information from only a single atmospheric column is used to predict the impact of unresolved processes occurring within that column. These effects are predicted using a fully connected neural network with residual connections, with weights shared across all atmospheric columns (Supplementary Information section C.4 ).

The inputs to the neural network include the prognostic variables in the atmospheric column, total incident solar radiation, sea-ice concentration and SST (Supplementary Information section C.1 ). We also provide horizontal gradients of the prognostic variables, which we found improves performance 44 . All inputs are standardized to have zero mean and unit variance using statistics precomputed during model initialization. The outputs are the prognostic variable tendencies scaled by the fixed unconditional standard deviation of the target field (Supplementary Information section C.5 ).

To interface between ERA5 14 data stored in pressure coordinates and the sigma coordinate system of our dynamical core, we introduce encoder and decoder components (Supplementary Information section D ). These components perform linear interpolation between pressure levels and sigma coordinate levels. We additionally introduce learned corrections to both encoder and decoder steps (Supplementary Figs. 4–6 ), using the same column-based neural network architecture as the learned physics module. Importantly, the encoder enables us to eliminate the gravity waves from initialization shock 45 , which otherwise contaminate forecasts.

Figure 1a shows the sequence of steps that NeuralGCM takes to make a forecast. First, it encodes ERA5 data at t = t 0 on pressure levels to initial conditions on sigma coordinates. To perform a time step, the dynamical core and learned physics (Fig. 1b ) then compute tendencies, which are integrated in time using an implicit–explicit ordinary differential equation solver 46 (Supplementary Information section E and Supplementary Table 2 ). This is repeated to advance the model from t = t 0 to t = t final . Finally, the decoder converts predictions back to pressure levels.

The time-step size of the ODE solver (Supplementary Table 3 ) is limited by the Courant–Friedrichs–Lewy condition on dynamics, and can be small relative to the timescale of atmospheric change. Evaluating learned physics is approximately 1.5 times as expensive as a time step of the dynamical core. Accordingly, following the typical practice for GCMs, we hold learned physics tendencies constant for multiple ODE time steps to reduce computational expense, typically corresponding to 30 minutes of simulation time.

Deterministic and stochastic models

We train deterministic NeuralGCM models using a combination of three loss functions (Supplementary Information section G.4 ) to encourage accuracy and sharpness while penalizing bias. During the main training phase, all losses are defined in a spherical harmonics basis. We use a standard mean squared error loss for prompting accuracy, modified to progressively filter out contributions from higher total wavenumbers at longer lead times (Supplementary Fig. 8 ). This filtering approach tackles the ‘double penalty problem’ 47 as it prevents the model from being penalized for predicting high-wavenumber features in incorrect locations at later times, especially beyond the predictability horizon. A second loss term encourages the spectrum to match the training data using squared loss on the total wavenumber spectrum of prognostic variables. These first two losses are evaluated on both sigma and pressure levels. Finally, a third loss term discourages bias by adding mean squared error on the batch-averaged mean amplitude of each spherical harmonic coefficient. For analysis of the impact that various loss functions have, refer to Supplementary Information section H.6.1 , and Supplementary Figs. 23 and 24 . The combined action of the three training losses allow the resulting models trained on 3-day rollouts to remain stable during years-to-decades-long climate simulations. Before final evaluations, we perform additional fine-tuning of just the decoder component on short rollouts of 24 hours (Supplementary Information section G.5 ).

Stochastic NeuralGCM models incorporate inherent randomness in the form of additional random fields passed as inputs to neural network components. Our stochastic loss is based on the CRPS 28 , 48 , 49 . CRPS consists of mean absolute error that encourages accuracy, balanced by a similar term that encourages ensemble spread. For each variable we use a sum of CRPS in grid space and CRPS in the spherical harmonic basis below a maximum cut-off wavenumber (Supplementary Information section G.6 ). We compute CRPS on rollout lengths from 6 hours to 5 days. As illustrated in Fig. 1 , we inject noise to the learned encoder and the learned physics module by sampling from Gaussian random fields with learned spatial and temporal correlation (Supplementary Information section C.2 and Supplementary Fig. 2 ). For training, we generate two ensemble members per forecast, which suffices for an unbiased estimate of CRPS.

Data availability

For training and evaluating the NeuralGCM models, we used the publicly available ERA5 dataset 14 , originally downloaded from https://cds.climate.copernicus.eu/ and available via Google Cloud Storage in Zarr format at gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3. To compare NeuralGCM with operational and data-driven weather models, we used forecast datasets distributed as part of WeatherBench2 12 at https://weatherbench2.readthedocs.io/en/latest/data-guide.html , to which we have added NeuralGCM forecasts for 2020. To compare NeuralGCM with atmospheric models in climate settings, we used CMIP6 data available at https://catalog.pangeo.io/browse/master/climate/ , as well as X-SHiELD 24 outputs available on Google Cloud storage in a ‘requester pays’ bucket at gs://ai2cm-public-requester-pays/C3072-to-C384-res-diagnostics. The Radiosonde Observation Correction using Reanalyses (RAOBCORE) V1.9 that was used as reference tropical temperature trends was downloaded from https://webdata.wolke.img.univie.ac.at/haimberger/v1.9/ . Base maps use freely available data from https://www.naturalearthdata.com/downloads/ .

Code availability

The NeuralGCM code base is separated into two open source projects: Dinosaur and NeuralGCM, both publicly available on GitHub at https://github.com/google-research/dinosaur (ref. 50 ) and https://github.com/google-research/neuralgcm (ref. 51 ). The Dinosaur package implements a differentiable dynamical core used by NeuralGCM, whereas the NeuralGCM package provides machine-learning models and checkpoints of trained models. Evaluation code for NeuralGCM weather forecasts is included in WeatherBench2 12 , available at https://github.com/google-research/weatherbench2 (ref. 52 ).

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Acknowledgements

We thank A. Kwa, A. Merose and K. Shah for assistance with data acquisition and handling; L. Zepeda-Núñez for feedback on the paper; and J. Anderson, C. Van Arsdale, R. Chemke, G. Dresdner, J. Gilmer, J. Hickey, N. Lutsko, G. Nearing, A. Paszke, J. Platt, S. Ponda, M. Pritchard, D. Rothenberg, F. Sha, T. Schneider and O. Voicu for discussions.

Author information

These authors contributed equally: Dmitrii Kochkov, Janni Yuval, Ian Langmore, Peter Norgaard, Jamie Smith, Stephan Hoyer

Authors and Affiliations

Google Research, Mountain View, CA, USA

Dmitrii Kochkov, Janni Yuval, Ian Langmore, Peter Norgaard, Jamie Smith, Griffin Mooers, James Lottes, Stephan Rasp, Michael P. Brenner & Stephan Hoyer

Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

Milan Klöwer

European Centre for Medium-Range Weather Forecasts, Reading, UK

Peter Düben & Sam Hatfield

Google DeepMind, London, UK

Peter Battaglia, Alvaro Sanchez-Gonzalez & Matthew Willson

School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

Michael P. Brenner

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Contributions

D.K., J.Y., I.L., P.N., J.S. and S. Hoyer contributed equally to this work. D.K., J.Y., I.L., P.N., J.S., G.M., J.L. and S. Hoyer wrote the code. D.K., J.Y., I.L., P.N., G.M. and S. Hoyer trained models and analysed the data. M.P.B. and S. Hoyer managed and oversaw the research project. M.K., S.R., P.D., S. Hatfield, P.B. and M.P.B. contributed technical advice and ideas. M.W. ran experiments with GraphCast for comparison with NeuralGCM. A.S.-G. assisted with data preparation. D.K., J.Y., I.L., P.N. and S. Hoyer wrote the paper. All authors gave feedback and contributed to editing the paper.

Corresponding authors

Correspondence to Dmitrii Kochkov , Janni Yuval or Stephan Hoyer .

Ethics declarations

Competing interests.

D.K., J.Y., I.L., P.N., J.S., J.L., S.R., P.B., A.S.-G., M.W., M.P.B. and S. Hoyer are employees of Google. S. Hoyer, D.K., I.L., J.Y., G.M., P.N., J.S. and M.B. have filed international patent application PCT/US2023/035420 in the name of Google LLC, currently pending, relating to neural general circulation models.

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Extended data figures and tables

Extended data fig. 1 maps of bias for neuralgcm-ens and ecmwf-ens forecasts..

Bias is averaged over all forecasts initialized in 2020.

Extended Data Fig. 2 Maps of spread-skill ratio for NeuralGCM-ENS and ECMWF-ENS forecasts.

Spread-skill ratio is averaged over all forecasts initialized in 2020.

Extended Data Fig. 3 Geostrophic balance in NeuralGCM, GraphCast 3 and ECMWF-HRES.

Vertical profiles of the extratropical intensity (averaged between latitude 30°–70° in both hemispheres) and over all forecasts initialized in 2020 of (a,d,g) geostrophic wind, (b,e,h) ageostrophic wind and (c,f,i) the ratio of the intensity of ageostrophic wind over geostrophic wind for ERA5 (black continuous line in all panels), (a,b,c) NeuralGCM-0.7°, (d,e,f) GraphCast and (g,h,i) ECMWF-HRES at lead times of 1 day, 5 days and 10 days.

Extended Data Fig. 4 Precipitation minus evaporation calculated from the third day of weather forecasts.

(a) Tropical (latitudes −20° to 20°) precipitation minus evaporation (P minus E) rate distribution, (b) Extratropical (latitudes 30° to 70° in both hemispheres) P minus E, (c) mean P minus E for 2020 ERA5 14 and (d) NeuralGCM-0.7° (calculated from the third day of forecasts and averaged over all forecasts initialized in 2020), (e) the bias between NeuralGCM-0.7° and ERA5, (f-g) Snapshot of daily precipitation minus evaporation for 2020-01-04 for (f) NeuralGCM-0.7° (forecast initialized on 2020-01-02) and (g) ERA5.

Extended Data Fig. 5 Indirect comparison between precipitation bias in X-SHiELD and precipitation minus evaporation bias in NeuralGCM-1.4°.

Mean precipitation calculated between 2020-01-19 and 2021-01-17 for (a) ERA5 14 (c) X-SHiELD 31 and the biases in (e) X-SHiELD and (g) climatology (ERA5 data averaged over 1990-2019). Mean precipitation minus evaporation calculated between 2020-01-19 and 2021-01-17 for (b) ERA5 (d) NeuralGCM-1.4° (initialized in October 18th 2019) and the biases in (f) NeuralGCM-1.4° and (h) climatology (data averaged over 1990–2019).

Extended Data Fig. 6 Yearly temperature bias for NeuralGCM and X-SHiELD 31 .

Mean temperature between 2020-01-19 to 2020-01-17 for (a) ERA5 at 200hPa and (b) 850hPa. (c,d) the bias in the temperature for NeuralGCM-1.4°, (e,f) the bias in X-SHiELD and (g,h) the bias in climatology (calculated from 1990–2019). NeuralGCM-1.4° was initialized in 18th of October (similar to X-SHiELD).

Extended Data Fig. 7 Tropical Cyclone densities and annual regional counts.

(a) Tropical Cyclone (TC) density from ERA5 14 data spanning 1987–2020. (b) TC density from NeuralGCM-1.4° for 2020, generated using 34 different initial conditions all initialized in 2019. (c) Box plot depicting the annual number of TCs across different regions, based on ERA5 data (1987–2020), NeuralGCM-1.4° for 2020 (34 initial conditions), and orange markers show ERA5 for 2020. In the box plots, the red line represents the median; the box delineates the first to third quartiles; the whiskers extend to 1.5 times the interquartile range (Q1 − 1.5IQR and Q3 + 1.5IQR), and outliers are shown as individual dots. Each year is defined from January 19th to January 17th of the following year, aligning with data availability from X-SHiELD. For NeuralGCM simulations, the 3 initial conditions starting in January 2019 exclude data for January 17th, 2021, as these runs spanned only two years.

Extended Data Fig. 8 Tropical Cyclone maximum wind distribution in NeuralGCM vs. ERA5 14 .

Number of Tropical Cyclones (TCs) as a function of maximum wind speed at 850hPa across different regions, based on ERA5 data (1987–2020; in orange), and NeuralGCM-1.4° for 2020 (34 initial conditions; in blue). Each year is defined from January 19th to January 17th of the following year, aligning with data availability from X-SHiELD. For NeuralGCM simulations, the 3 initial conditions starting in January 2019 exclude data for January 17th, 2021, as these runs spanned only two years.

Supplementary information

Supplementary information.

Supplementary Information (38 figures, 6 tables): (A) Lines of code in atmospheric models; (B) Dynamical core of NeuralGCM; (C) Learned physics of NeuralGCM; (D) Encoder and decoder of NeuralGCM; (E) Time integration; (F) Evaluation metrics; (G) Training; (H) Additional weather evaluations; (I) Additional climate evaluations.

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Kochkov, D., Yuval, J., Langmore, I. et al. Neural general circulation models for weather and climate. Nature 632 , 1060–1066 (2024). https://doi.org/10.1038/s41586-024-07744-y

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