CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States. Issue 5 (15th March 2018)

• Record Type: Journal Article
• Authors: Ma, H.‐Y.; Klein, S. A.; Xie, S.; Zhang, C.; Tang, S.; Tang, Q.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.; Ahlgrimm, M.; Berg, L. K.; Cheruy, F.; Cole, J.; Forbes, R.; Gustafson, W. I.; Huang, M.; Liu, Y.; Merryfield, W.; Qian, Y.; Roehrig, R.; Wang, Y.‐C.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 5(2018)
• Page Start: 2888
• Page End: 2909
• Publication Date: 2018-03-15
• Subjects: surface air temperature -- systematic errors -- SGP -- surface energy budget -- radiation -- evaporative fraction; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2017JD027194
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Many weather forecast and climate models simulate warm surface air temperature (T2m ) biases over midlatitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multimodel 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 the T2m bias using a short‐term hindcast approach during the spring and summer of 2011. Observations are mainly from the Atmospheric Radiation Measurement Southern Great Plains sites. The present study examines the contributions of surface energy budget errors. All participating models simulate too much net shortwave and longwave fluxes at the surface but with no consistent mean bias sign in turbulent fluxes over the Central United States and Southern Great Plains. Nevertheless, biases in the net shortwave and downward longwave fluxes as well as surface evaporative fraction (EF) are contributors to T2m bias. Radiation biases are largely affected by cloud simulations, while EF bias is largely affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation based upon the surface energy budget is derived to further quantify the magnitudes of radiation and EF contributions to T2m bias. Our analysis ascribes that a large EF underestimate is the dominant source of error in all models with a large positive temperature bias, whereas an EF overestimate compensates for an excess of absorbed shortwave radiation in nearly all the models with the smallest temperature bias. Key Points: Biases in the net shortwave, downward longwave fluxes, and evaporative fraction are contributors to warm surface air temperature biases Radiation and evaporative fraction biases are associated with clouds, precipitation, evaporation, and soil moisture biases Biases in evaporative fraction are generally more important than biases in radiation in explaining the temperature biases