Toward Reanalysis of the Arctic Climate System - Sea Ice Ocean Reconstruction with Data Assimilation

An Integrative Data Assimilation for the Arctic System (IDAAS) has been recommended for development by a special interagency research program "A Study of Environmental Arctic Change" (SEARCH, 2005). While existing operational reanalyses assimilate only atmospheric measurements, an IDAAS ac...

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Format: Dataset
Language:unknown
Published: Arctic Data Center
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Online Access:https://search.dataone.org/view/e0408d75-adc5-441a-a802-6ecf6669f25e
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Summary:An Integrative Data Assimilation for the Arctic System (IDAAS) has been recommended for development by a special interagency research program "A Study of Environmental Arctic Change" (SEARCH, 2005). While existing operational reanalyses assimilate only atmospheric measurements, an IDAAS activity would include non-atmospheric components: sea ice, oceanic, terrestrial geophysical and biogeochemical parameters and human dimensions data. The IDAAS was recommended for development "because recent global reanalyses of the atmosphere have received widespread use by the research community and because they are regarded as one of the major success stories of the past decade in atmospheric research" (SEARCH, 2005). Atmospheric reanalysis products play a major role in the arctic system studies and are used to force sea ice, ocean and terrestrial models, and to analyze the climate system's variability and to explain and understand the interrelationships of the system's components and the causes of their change. Motivated by this success and the major goals and recommendations of SEARCH, we develop an integrated set of assimilation procedures for the ice-ocean system that is able to provide gridded data sets that are physically consistent and constrained to the observations of sea ice and ocean parameters. Building on our past research activities in sea ice and ocean data assimilation, we make some first steps toward the creation of an Arctic Climate System Reanalysis that uses modern four-dimensional variational (4D-Var, adjoint) data assimilation methods. We employ sea ice and ocean models with new data assimilation procedures to maximize the integration of model results with observations and thus attempt to provide the arctic research community with complete and accurate data sets, ultimately for at least the last three decades. Here we describe three digital data sources made available for community by this project activities, namely: Observational hydrographic data interpolated into PIOMAS grid; Currents data in the original format as it was organized by Greg Holloway who collected these data and provided these data for our project; Our project results: Monthly hydrography and circulation averaged for three periods: 1972-1978, 1989-1996 and 1997-2006.