CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States
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- Lawrence Livermore National Laboratory, Livermore CA USA
- Met Office, Exeter UK
- European Centre for Medium-Range Weather Forecasts, Reading UK
- Pacific Northwest National Laboratory, Richland WA USA
- Laboratoire de Météorologie Dynamique, Paris France
- Canadian Centre for Climate Modelling and Analysis, Environment Canada, Victoria British Columbia Canada
- CNRM, Meteo-France/CNRS, Toulouse France
- Research Center for Environmental Change, Academia Sinica, Taipei Taiwan
Many weather forecasting and climate models simulate a warm surface air temperature (T2m) bias over mid-latitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multi-model intercomparison project (CAUSES: Cloud Above the United States and Errors at the Surface), which aims to evaluate the role of cloud, radiation, and precipitation biases in contributing to T2m bias using a short-term hindcast approach with observations mainly from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during the period of April to August 2011. The present study examines the contribution of surface energy budget errors to the bias. All participating models simulate higher net shortwave and longwave radiative fluxes at the surface but there is no consistency on signs of biases in latent and sensible heat fluxes over the Central U.S. and ARM SGP. Nevertheless, biases in net shortwave and downward longwave fluxes, as well as surface evaporative fraction (EF) are the main contributors to T2m bias. Radiation biases are largely affected by cloud simulations, while EF is affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation is derived to further quantify the magnitudes of radiation and EF contributions to T2m bias. Our analysis suggests that radiation errors are always an important source of T2m error for long-term climate runs with EF errors either of equal or lesser importance. However, for the short-term hindcasts, EF errors are more important provided a model has a substantial EF bias.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1439003
- Report Number(s):
- PNNL-SA-126060; KP1701000
- Journal Information:
- Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 5; ISSN 2169-897X
- Publisher:
- American Geophysical Union
- Country of Publication:
- United States
- Language:
- English
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