TY - JOUR A1 - Greene, Chad A. A1 - Thirumalai, Kaustubh A1 - Kearney, Kelly A. A1 - Delgado, Jose Miguel Martins A1 - Schwanghart, Wolfgang A1 - Wolfenbarger, Natalie S. A1 - Thyng, Kristen M. A1 - Gwyther, David E. A1 - Gardner, Alex S. A1 - Blankenship, Donald D. T1 - The Climate Data Toolbox for MATLAB JF - Geochemistry, geophysics, geosystems N2 - Climate science is highly interdisciplinary by nature, so understanding interactions between Earth processes inherently warrants the use of analytical software that can operate across the disciplines of Earth science. Toward this end, we present the Climate Data Toolbox for MATLAB, which contains more than 100 functions that span the major climate-related disciplines of Earth science. The toolbox enables streamlined, entirely scriptable workflows that are intuitive to write and easy to share. Included are functions to evaluate uncertainty, perform matrix operations, calculate climate indices, and generate common data displays. Documentation is presented pedagogically, with thorough explanations of how each function works and tutorials showing how the toolbox can be used to replicate results of published studies. As a well-tested, well-documented platform for interdisciplinary collaborations, the Climate Data Toolbox for MATLAB aims to reduce time spent writing low-level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing. Plain Language Summary This article describes a collection of computer code that has recently been released to help scientists analyze many types of Earth science data. The code in this toolbox makes it easy to investigate things like global warming, El Nino, or other major climate-related processes such as how winds affect ocean circulation. Although the toolbox was designed to be used by expert climate scientists, its instruction manual is well written, and beginners may be able to learn a great deal about coding and Earth science, simply by following along with the provided examples. The toolbox is intended to help scientists save time, help them ensure their analysis is accurate, and make it easy for other scientists to repeat the results of previous studies. Y1 - 2019 U6 - https://doi.org/10.1029/2019GC008392 SN - 1525-2027 VL - 20 IS - 7 SP - 3774 EP - 3781 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Khider, D. A1 - Emile-Geay, J. A1 - McKay, N. P. A1 - Gil, Y. A1 - Garijo, D. A1 - Ratnakar, V A1 - Alonso-Garcia, M. A1 - Bertrand, S. A1 - Bothe, O. A1 - Brewer, P. A1 - Bunn, A. A1 - Chevalier, M. A1 - Comas-Bru, L. A1 - Csank, A. A1 - Dassie, E. A1 - DeLong, K. A1 - Felis, T. A1 - Francus, P. A1 - Frappier, A. A1 - Gray, W. A1 - Goring, S. A1 - Jonkers, L. A1 - Kahle, M. A1 - Kaufman, D. A1 - Kehrwald, N. M. A1 - Martrat, B. A1 - McGregor, H. A1 - Richey, J. A1 - Schmittner, A. A1 - Scroxton, N. A1 - Sutherland, E. A1 - Thirumalai, Kaustubh A1 - Allen, K. A1 - Arnaud, F. A1 - Axford, Y. A1 - Barrows, T. A1 - Bazin, L. A1 - Birch, S. E. Pilaar A1 - Bradley, E. A1 - Bregy, J. A1 - Capron, E. A1 - Cartapanis, O. A1 - Chiang, H-W A1 - Cobb, K. M. A1 - Debret, M. A1 - Dommain, RĂ©ne A1 - Du, J. A1 - Dyez, K. A1 - Emerick, S. A1 - Erb, M. P. A1 - Falster, G. A1 - Finsinger, W. A1 - Fortier, D. A1 - Gauthier, Nicolas A1 - George, S. A1 - Grimm, E. A1 - Hertzberg, J. A1 - Hibbert, F. A1 - Hillman, A. A1 - Hobbs, W. A1 - Huber, M. A1 - Hughes, A. L. C. A1 - Jaccard, S. A1 - Ruan, J. A1 - Kienast, M. A1 - Konecky, B. A1 - Le Roux, G. A1 - Lyubchich, V A1 - Novello, V. F. A1 - Olaka, L. A1 - Partin, J. W. A1 - Pearce, C. A1 - Phipps, S. J. A1 - Pignol, C. A1 - Piotrowska, N. A1 - Poli, M-S A1 - Prokopenko, A. A1 - Schwanck, F. A1 - Stepanek, C. A1 - Swann, G. E. A. A1 - Telford, R. A1 - Thomas, E. A1 - Thomas, Z. A1 - Truebe, S. A1 - von Gunten, L. A1 - Waite, A. A1 - Weitzel, N. A1 - Wilhelm, B. A1 - Williams, J. A1 - Winstrup, M. A1 - Zhao, N. A1 - Zhou, Y. T1 - PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data JF - Paleoceanography and paleoclimatology N2 - The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches. KW - standards KW - FAIR KW - paleoclimate KW - paleoceanography KW - data KW - best practices Y1 - 2019 U6 - https://doi.org/10.1029/2019PA003632 SN - 2572-4517 SN - 2572-4525 VL - 34 IS - 10 SP - 1570 EP - 1596 PB - American Geophysical Union CY - Washington ER -