DART/CAM: An ensemble data assimilation system for CESM atmospheric models

• Published in: Journal of Climate
• Other Authors: Raeder, Kevin (author), Anderson, Jeffrey (author), Collins, Nancy (author), Hoar, Timothy (author), Kay, Jennifer (author), Lauritzen, Peter (author), Pincus, Robert (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2012
• Subjects: Kalman filters; Model evaluation/performance; Model comparison; Data assimilation; Climate models; Arctic; Sea ice
• Online Access: http://nldr.library.ucar.edu/repository/collections/OSGC-000-000-011-238; https://doi.org/10.1175/JCLI-D-11-00395.1

The Community Atmosphere Model (CAM) has been interfaced to the Data Assimilation Research Testbed (DART), a community facility for ensemble data assimilation. This provides a large set of data assimilation tools for climate model research and development. Aspects of the interface to the Community Earth System Model (CESM) software are discussed and a variety of applications are illustrated, ranging from model development to the production of long series of analyses. CAM output is compared directly to real observations from platforms ranging from radiosondes to global positioning system satellites. Such comparisons use the temporally and spatially heterogeneous analysis error estimates available from the ensemble to provide very specific forecast quality evaluations. The ability to start forecasts from analyses, which were generated by CAM on its native grid and have no foreign model bias, contributed to the detection of a code error involving Arctic sea ice and cloud cover. The potential of parameter estimation is discussed. A CAM ensemble reanalysis has been generated for more than 15 yr. Atmospheric forcings from the reanalysis were required as input to generate an ocean ensemble reanalysis that provided initial conditions for decadal prediction experiments. The software enables rapid experimentation with differing sets of observations and state variables, and the comparison of different models against identical real observations, as illustrated by a comparison of forecasts initialized by interpolated ECMWF analyses and by DART/CAM analyses.