Climate and Dynamics
Analysis of the Arctic atmospheric energy budget in WRF: A comparison with reanalyses and satellite observations
Article first published online: 19 NOV 2011
Copyright 2011 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 116, Issue D22, November 2011
How to Cite
2011), Analysis of the Arctic atmospheric energy budget in WRF: A comparison with reanalyses and satellite observations, J. Geophys. Res., 116, D22108, doi:10.1029/2011JD016622., , and (
- Issue published online: 19 NOV 2011
- Article first published online: 19 NOV 2011
- Manuscript Accepted: 13 SEP 2011
- Manuscript Revised: 12 SEP 2011
- Manuscript Received: 26 JUL 2011
- energy budget
 The Weather Research and Forecasting (WRF) model is used to dynamically downscale the regional climate of the Arctic, an area undergoing rapid climate changes. Because the WRF model is increasingly being run over larger spatial and temporal scales, an assessment of its ability to reconstruct basic properties of regional climates, such as terms in the energy budget, is crucial. Estimates of the Arctic energy budget from WRF are compared with estimates from reanalyses and satellite observations. The WRF model was run on a large pan-Arctic domain continuously from 2000 to 2008. Apart from a few systematic shortcomings, WRF sufficiently captures the Arctic energy budget. The major deficiency, with differences from reanalyses and satellite observations as large as 40 W m−2 in summer months, is in the shortwave radiative fluxes at both the surface and top of atmosphere (TOA). WRF's positive bias in upwelling shortwave radiation is due to a specified constant sea ice albedo of 0.8, which is too high during the summer. When sea ice albedo in WRF is allowed to vary in a more realistic manner in a test simulation, both surface and TOA energy budget components improve, while showing little impact on the atmospheric energy convergence and storage. A second, similar WRF simulation was performed but with gridded nudging enabled. When the large-scale circulation is constrained to the forcing data, the two energy budget terms that are most dependent on weather patterns, the convergence of atmospheric energy transport and the tendency of column-integrated energy, closely resemble their reanalysis counterparts.