{"id":1811,"date":"2019-10-25T13:44:43","date_gmt":"2019-10-25T11:44:43","guid":{"rendered":"https:\/\/genr.interpunct.dev\/?p=1811"},"modified":"2021-02-09T18:39:00","modified_gmt":"2021-02-09T16:39:00","slug":"improving-metadata-standards-for-atmospheric-models-the-atmodat-project","status":"publish","type":"post","link":"https:\/\/genr.interpunct.dev\/improving-metadata-standards-for-atmospheric-models-the-atmodat-project\/","title":{"rendered":"Improving (Meta)Data Standards for Atmospheric Models \u2013 the AtMoDat Project"},"content":{"rendered":"\n

The newly launched AtMoDat project is carrying out research to enable data used in Atmospheric Models for Climate Research to be open and reusable. The research will make use of DataCite DOIs and metadata schema for climate models, acting as extension to the schema while being supported by AtMoDat partner infrastructure service providers.<\/strong><\/p>\n\n\n\n

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Image: Chen, Baozhang and Coops, Nicholas C, 2009:  Understanding of Coupled Terrestrial Carbon, Nitrogen and Water Dynamics\u2014An Overview. Sensors (Basel, Switzerland). Sensors, 9, 8624-8657, doi: https:\/\/doi.org\/10.3390\/s91108624<\/a>, CC BY 4.0<\/p>\n<\/div><\/div><\/div>\n\n\n\n

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DOI <\/p> 10.25815\/X0BF-K589<\/a> <\/summary>

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Citation format: The Chicago Manual of Style, 17th Edition<\/em>

Ganske, Anette, and Angelina Kraft. \u201cImproving (Meta)Data Standards for Atmospheric Models \u2013 the AtMoDat Project.\u201d Generation Research, 2019. https:\/\/doi.org\/10.25815\/X0BF-K589<\/a>. <\/p>\n<\/div><\/details><\/div>\n\n\n\n\n\n\n\n

\"AtMoDat\"<\/figure><\/div>\n\n\n\n

Atmospheric Models are a relevant element of Climate Research. They are e.g., part of Climate Models, which help to translate the scenarios for future increases of atmospheric greenhouse gas concentrations into possible changes of the earth system such as future changes in air temperature or sea level heights. The earth is a very complex chaotic system, where all components interact with each other, e.g., there are heat exchanges between the atmosphere and the ocean (Baede et al., 2001<\/a>). Therefore, climate models consist of several submodels, e.g., for the atmosphere, the ocean or the land surfaces, which regularly exchange information during the simulations. The results of a climate simulation consist of a large number of variables (e.g., water temperature, humidity of the air, ocean currents, etc.) for which values are calculated over the entire earth and at several atmospheric and oceanic levels. Hence, a simulation of a climate model for a period of more than one hundred years is very expensive and a lot of results for several variables are computed. Nevertheless, one simulation with a climate model only shows one possible physical outcome and the simulation with another climate model can lead to a different solution. For example, the timeline of the future warming of the atmosphere (or which part of the additional energy is stored in the atmosphere and in the ocean) differs if two simulations with different climate models are made. As a consequence, reports on climate change (e.g., the IPCC reports<\/a>) always rely on the results of several models. Large internationally coordinated model comparison studies have been organized in order to assess this variability and uncertainty of climate models. The most recent study of this type is CMIP6 (Climate Model Intercomparison Project Phase 6, see Eyring et al., 2016<\/a>).<\/p>\n\n\n\n

Data format, quality and curation standards have been\ndeveloped, to make climate model results intercomparable and to enable scientists\nall over the world to analyse the data (e.g., Taylor et al., 2018<\/a>). This standardization actually is a precondition for\nsuccessfully performing intercomparison studies such as CMIP6. The German Climate Computing Center (Deutsches\nKlimarechenzentrum, DKRZ<\/a>) provides a high performance computing cluster for\nperforming climate simulations and hosts one of the data centers, which store\nthe data and provide them as open data for download to scientists and other\ninterested persons. Each dataset is tested to comply with the established\nstandards. At an appropriate level of granularity, all data receives a DataCite\nDOI<\/a>\n(Digital Object Identifier) so that it can be uniquely identified and found.<\/p>\n\n\n\n

Although standardization is very valuable when it\ncomes to comparing model results, joint standards are not common for the data\nof all atmospheric modeling sub-disciplines for all their applications. As a\nresult, the results of many atmospheric model simulations are not published as\nopen data and are seldom used by other scientists. To increase the use of\natmospheric model results, the project AtMoDat has been started in June 2019.\nIt is carried out by the two infrastructure service providers, the Technische\nInformationsbibliothek (TIB)<\/a>, Leibniz Information Centre of Science and\nTechnology, and the DKRZ, and by two research groups: the Meteorological Institute of the University of Hamburg<\/a> and the Institute for Meteorology of the University of Leipzig<\/a>.<\/p>\n\n\n\n

The task of AtMoDat is to systematically adapt data\ncuration standards inspired by the CMIP standard to the specific requirements\nof two research communities: small model comparison studies and urban climate\nresearch. Standards will be developed and applied to existing atmospheric model\ndata and will be evaluated for their universal usability, which will\nsignificantly increase the reusability of these data. Based on these adapted\nstandards, an extension of the DataCite metadata schema to domain-specific data\nwill increase the value of DataCite DOIs as a quality feature. A sustainable\napplication of the universal data standard as well as the allocation of\nsubject-specific DataCite DOIs will be ensured by the service offers of the two\ninfrastructure service providers TIB and DKRZ.<\/p>\n\n\n\n

More information about AtMoDat can be found at https:\/\/www.atmodat.de\/<\/a><\/p>\n\n\n\n

Literature<\/h2>\n\n\n\n

Eyring, V., Bony, S., Meehl, G. A., Senior, C. A.,\nStevens, B., Stouffer, R. J., and Taylor, K. E., 2016: Overview of the Coupled\nModel Intercomparison Project Phase 6 (CMIP6) experimental design and\norganization, Geosci. Model Dev., 9, 1937\u20131958, https:\/\/doi.org\/10.5194\/gmd-9-1937-2016<\/a> <\/p>\n\n\n\n

Baede, A.M.P; Ahlonsou, E.; Ding, Y. and  Schimel, D, 2001: The Climate System: an Overview. In: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp. https:\/\/www.ipcc.ch\/site\/assets\/uploads\/2018\/03\/TAR-01.pdf<\/a><\/p>\n\n\n\n

Karl E. Taylor, Martin Juckes, V. Balaji, Luca Cinquini, S\u00e9bastien Denvil, Paul J. Durack, Mark Elkington, Eric Guilyardi, Slava Kharin, Michael Lautenschlager, Bryan Lawrence, Denis Nadeau, and Martina Stockhause, 2018. CMIP6 Global Attributes, DRS, Filenames, Directory Structure, and CV\u2019s. Document Version v6.2.7. https:\/\/goo.gl\/v1drZl<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The newly launched AtMoDat project is carrying out research to enable data used in Atmospheric Models for Climate Research to be open and reusable. The research will make use of DataCite DOIs and metadata schema for climate models, acting as extension to the schema while being supported by AtMoDat partner infrastructure service providers<\/p>\n","protected":false},"author":37,"featured_media":1816,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":"","_wordproof_timestamp":false},"categories":[374,5],"tags":[66,429,427,75,68,302,432,25,23,428,431,47,170,433,430,119,67,14,22,73,129],"cc_featured_image_caption":{"caption_text":false,"source_text":false,"source_url":false},"featured_image_src":"https:\/\/genr.interpunct.dev\/wp-content\/uploads\/2019\/10\/sensors-09-08624f1.jpg","featured_image_src_square":"https:\/\/genr.interpunct.dev\/wp-content\/uploads\/2019\/10\/sensors-09-08624f1.jpg","author_info":{"display_name":"Anette Ganske and Angelina Kraft","author_link":"https:\/\/genr.interpunct.dev\/author\/atmodat\/"},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/posts\/1811"}],"collection":[{"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/users\/37"}],"replies":[{"embeddable":true,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/comments?post=1811"}],"version-history":[{"count":0,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/posts\/1811\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/media\/1816"}],"wp:attachment":[{"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/media?parent=1811"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/categories?post=1811"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/genr.interpunct.dev\/wp-json\/wp\/v2\/tags?post=1811"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}