Observations for Model Intercomparison Project (Obs4MIPs) [electronic resource] : status for CMIP6.

The Observations for Model Intercomparison Project (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 Progra...

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Bibliographic Details
Online Access: Full Text (via OSTI)
Corporate Author: Lawrence Livermore National Laboratory (Researcher)
Format: Government Document Electronic eBook
Language:English
Published: Washington, D.C. : Oak Ridge, Tenn. : United States. National Nuclear Security Administration ; Distributed by the Office of Scientific and Technical Information, U.S. Department of Energy, 2020.
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500 |a Waliser, Duane ; Gleckler, Peter J. ; Ferraro, Robert ; Taylor, Karl E. ; Ames, Sasha ; Biard, James ; Bosilovich, Michael G. ; Brown, Otis ; Chepfer, Helene ; Cinquini, Luca ; et al;  
520 3 |a The Observations for Model Intercomparison Project (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 nonexperts 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 are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes 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; and ozone (O<sub>3</sub>), methane (CH<sub>4</sub>), and carbon dioxide (CO<sub>2</sub>) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g.,�FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO<sub>2</sub>). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g.,�daily) and/or regional products are now receiving more attention. 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 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. 
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