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

  • K. Van Weverberg
  • , C. J. Morcrette
  • , J. Petch
  • , S. A. Klein
  • , H. Y. Ma
  • , C. Zhang
  • , S. Xie
  • , Q. Tang
  • , W. I. Gustafson
  • , Y. Qian
  • , L. K. Berg
  • , Y. Liu
  • , M. Huang
  • , M. Ahlgrimm
  • , R. Forbes
  • , E. Bazile
  • , R. Roehrig
  • , J. Cole
  • , W. Merryfield
  • , W. S. Lee
  • F. Cheruy, L. Mellul, Y. C. Wang, K. Johnson, M. M. Thieman
  • Now at Met Office Hadley Centre
  • Lawrence Livermore National Laboratory
  • Pacific Northwest National Laboratory
  • European Centre for Medium-Range Weather Forecasts
  • Météo-France/CNRS
  • Meteorological Research Branch
  • Université Pierre et Marie Curie
  • Academia Sinica Taiwan
  • Brookhaven National Laboratory
  • SSAI

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)3612-3644
Number of pages33
JournalJournal of Geophysical Research: Atmospheres
Volume123
Issue number7
DOIs
Publication statusPublished - 16 Apr 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • CAUSES
  • attribution
  • clouds
  • radiation
  • warm bias

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