Observations for Model Intercomparison Project (Obs4MIPs): Status for CMIP6

The Observations for Model Intercomparison Projects (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Progr...

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Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: Waliser, Duane, Gleckler, Peter J., Ferraro, Robert, Taylor, Karl E., Ames, Sasha, Biard, James, Bosilovich, Michael G., Brown, Otis, Chepfer, Helene, Cinquini, Luca, Durack, Paul, Eyring, Veronika, Mathieu, Pierre-Philippe, Lee, Tsengda, Pinnock, Simon, Potter, Gerald L., Rixen, Michel, Saunders, Roger, Shulz, Jörg, Thépaut, Jean-Noel, Tuma, Matthias
Format: Other Non-Article Part of Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
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Online Access:https://elib.dlr.de/135145/
https://elib.dlr.de/135145/1/Waliser-eyring-etal-gmd-13-2945-2020.pdf
https://gmd.copernicus.org/articles/13/2945/2020/
Description
Summary:The Observations for Model Intercomparison Projects (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs: 1) targets observed variables that can be compared to CMIP model variables, 2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output, 3) provides brief technical documentation for each dataset, designed for non-experts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits and limitations, and 4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80, many undergoing updates, with another 20 or so in preparation, and more than 100 proposed and under consideration. Current global satellite-based datasets include, but are not limited to, humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top of atmosphere longwave and shortwave radiation; along with ozone (O3), methane (CH4) and carbon dioxide (CO2) products. Proposed products expected for inclusion for CMIP6 analysis include, but are not limited to, alternative products for the above quantities, along with additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g. FAPAR, LAI, burnt area fraction), ice sheet mass and height, carbon monoxide (CO) and nitrogen dioxide (NO2). While most obs4MIPs datasets are delivered as monthly and global, greater emphasis is being places on products with higher time resolution (e.g. daily) and/or regional products. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including: 1) an updated obs4MIPs data specifications document that provides for additional search facets and generally improves congruence with CMIP6 specifications for model datasets, 2) a set of six easily understood indicators that help guide users as to a dataset’s maturity and suitability for application, and 3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in-situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth System models used in CMIP.