4.6 Article

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the US Southern Great Plains

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 123, Issue 7, Pages 3612-3644

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2017JD027188

Keywords

warm bias; CAUSES; radiation; attribution; clouds

Funding

  1. U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
  2. DOE [DE-SC0014122]
  3. DOE by Battelle Memorial Institute [DE-AC05-76RL01830]
  4. Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]
  5. Regional and Global Climate Modeling program of the Biological and Environmental Research Division in the Office of Sciences of the U.S. Department of Energy (DOE) under U. S. Department of Energy by LLNL [DE-AC52-07NA27344]
  6. Atmospheric System Research program of the Biological and Environmental Research Division in the Office of Sciences of the U.S. Department of Energy (DOE) under U. S. Department of Energy by LLNL [DE-AC52-07NA27344]
  7. Atmospheric Radiation Measurement (ARM) program of the Biological and Environmental Research Division in the Office of Sciences of the U.S. Department of Energy (DOE) under U. S. Department of Energy by LLNL [DE-AC52-07NA27344]
  8. Institut du Developpement et des Ressources en Informatique Scientifique, CNRS, France [DARI-0292]
  9. DEPHY2 project - French national program LEFE/INSU
  10. DOE grant [DE-SC0005259]
  11. Office of Biological and Environmental Research

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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 other 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.

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