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Title: CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stations near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in-depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while othermore » models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.« less
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  1. Met Office, Exeter (United Kingdom)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. European Centre for Medium-Range Weather Forecasts, Reading (United Kingdom)
  5. CNRM, Meteo-France/CNRS, Toulouse (France)
  6. Environment and Climate Change Canada, Victoria British Columbia (Canada)
  7. Laboratoire de Meteorologie Dynamique, Paris (France)
  8. Academia Sinica, Taipei (Taiwan)
  9. Brookhaven National Lab. (BNL), Upton, NY (United States)
  10. Science Systems and Applications, Inc, Norfolk, VA (United States)
Publication Date:
Report Number(s):
LLNL-JRNL-732219; BNL-205767-2018-JAAM
Journal ID: ISSN 2169-897X
Grant/Contract Number:
AC52-07NA27344; SC0014122; SC0005259; AC05-76RL01830; AC02-05CH11231; SC0012704
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 123; Journal Issue: 7; Journal ID: ISSN 2169-897X
American Geophysical Union
Research Org:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; warm bias; CAUSES; radiation; attribution; clouds
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1454812