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Title: Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA)

Abstract

As an important step toward a coupled data assimilation system for generating reanalysis fields needed to assess climate model projections, the Ocean Atmosphere Coupled Reanalysis for Climate Applications (OARCA) project assesses and improves the longest reanalyses currently available of the atmosphere and ocean: the 20th Century Reanalysis Project (20CR) and the Simple Ocean Data Assimilation with sparse observational input (SODAsi) system, respectively. In this project, we make off-line but coordinated improvements in the 20CR and SODAsi datasets, with improvements in one feeding into improvements of the other through an iterative generation of new versions. These datasets now span from the 19th to 21st centuries. We then study the extreme weather and variability from days to decades of the resulting datasets. A total of 24 publications have been produced in this project.

Authors:
 [1];  [2]
  1. Univ. of Colorado, Boulder, CO (United States)
  2. National Oceanic and Atmospheric Administration, Silver Springs, MD (United States)
Publication Date:
Research Org.:
Univ. of Colorado, Boulder, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
Contributing Org.:
Texas A&M University; United Kingdom Met Office; Atmospheric Circulation Reconstructions over the Earth
OSTI Identifier:
1433384
Report Number(s):
DOE-CIRES-6966
DOE Contract Number:
SC0006966
Resource Type:
Technical Report
Resource Relation:
Related Information: go.usa.gov/XTdhttp://portal.nersc.gov/project/20C_Reanalysis/portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis_version_2c/https://rda.ucar.edu/datasets/ds131.2/http://reanalyses.orghttps://reanalyses.org/atmosphere/writ
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; reanalysis; synthesis; state estimation; climate; weather extremes; climate variability; climate change

Citation Formats

Compo, Gilbert P., and Sardeshmukh, Prashant D. Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA). United States: N. p., 2018. Web. doi:10.2172/1433384.
Compo, Gilbert P., & Sardeshmukh, Prashant D. Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA). United States. doi:10.2172/1433384.
Compo, Gilbert P., and Sardeshmukh, Prashant D. Tue . "Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA)". United States. doi:10.2172/1433384. https://www.osti.gov/servlets/purl/1433384.
@article{osti_1433384,
title = {Final Technical Report for Collaborative Research: Developing and Implementing Ocean-Atmosphere Reanalyses for Climate Applications (OARCA)},
author = {Compo, Gilbert P. and Sardeshmukh, Prashant D.},
abstractNote = {As an important step toward a coupled data assimilation system for generating reanalysis fields needed to assess climate model projections, the Ocean Atmosphere Coupled Reanalysis for Climate Applications (OARCA) project assesses and improves the longest reanalyses currently available of the atmosphere and ocean: the 20th Century Reanalysis Project (20CR) and the Simple Ocean Data Assimilation with sparse observational input (SODAsi) system, respectively. In this project, we make off-line but coordinated improvements in the 20CR and SODAsi datasets, with improvements in one feeding into improvements of the other through an iterative generation of new versions. These datasets now span from the 19th to 21st centuries. We then study the extreme weather and variability from days to decades of the resulting datasets. A total of 24 publications have been produced in this project.},
doi = {10.2172/1433384},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 17 00:00:00 EDT 2018},
month = {Tue Apr 17 00:00:00 EDT 2018}
}

Technical Report:

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