Collaborative Proposal: Type 1: Developing and Implementing Ocean-Atomosphere Reanalyses for Climate Applications (oarca)
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Technical Description This research will develop new oceanic and atmospheric reanalyses with quantified uncertainties to address several unresolved questions in the area of observed climate variability and change since 1871. The work involves developing a hierarchy of numerical models resulting in a new reanalysis system called OARCA (Ocean Atmosphere Reanalysis for Climate Applications) to be used for understanding global and regional climate change and variability. The data assimilation system is based on two existing reanalyses: The Twentieth Century Reanalysis system (20CR) for the atmosphere and the Simple Ocean Data Assimilation system (SODA) for the global oceans. The OARCA effort relies on high performance massively parallel platforms such as those at NCCS and DOE NERSC to produce the reanalyses. Its production will advance the knowledge of how to efficiently compute very large geophysical systems. The resulting state estimates of the climate system for the period 1871 to 2008 will be used to explore modes of decadal variability that include changes in the tropical Pacific circulation and variability of the Atlantic Merdional Overturning Circulation. These reanalyses will also help us better understand the decadal variability of climate phenomena such as drought cycles, El Niño, North American and Asian monsoons, and the low frequency variability of hurricane activity. Broader Significance and Importance The resulting state estimate of the climate system will be distributed via data servers at Texas A&M and at the NOAA Earth System Research Laboratory and University of Colorado CIRES Climate Diagnostics Center. Researchers will be able to use these data for their own studies of climate variability and climate change that range from the statistics of weather extremes to decadal variability and long-term trends. In addition to using the reanalysis to diagnose climate variability in the 20th Century, the state estimation will be available to be used for initial and boundary conditions for regional downscaling and decadal prediction models. The OARCA datasets will be useful to researchers interested in improving Earth System models by providing benchmarks and metrics with quantified uncertainties for testing and evaluating climate prediction models. The new reanalyses will provide to the research community SST(Sea Surface Temperature) analyses with error bars that are state dependent, which can be used as an objective verification of climate model AR5 regional trends and variability over long periods.
