Observations of the radiation divergence in the surface layer and its implication for its parameterization in numerical weather prediction models

• Published in: Journal of Geophysical Research
• Main Authors: Steeneveld, G.J., Wokke, M.J.J., Groot Zwaaftink, C.D., Pijlman, S., Jacobs, A.F.G., Holtslag, A.A.M.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2010
• Subjects: cases-99; climate model; contrasting nights; flux divergence; greenland; nocturnal boundary-layer; sensitivity; simulations; transport models; turbulence; Greenland
• Online Access: https://research.wur.nl/en/publications/observations-of-the-radiation-divergence-in-the-surface-layer-and; https://doi.org/10.1029/2009JD013074

This paper presents the results of 5 months of in situ observations of the diurnal cycle of longwave radiative heating rate in the lower part of the atmospheric boundary layer over grassland, with a particular focus on nighttime conditions. The observed longwave radiative heating is minimal at the evening transition, with a median value of -1.8 K h-1 between 1.3 and 10 m and -0.5 K h-1 between 10 and 20 m, respectively. After the transition, its magnitude gradually decreases during the night. For individual clear calm nights, a minimal radiative heating rate of -3.5 and -2.0 K h-1 was found for the two indicated layers. The total radiative heating rate appears dominantly controlled by the upward longwave flux divergence. Surprisingly, at noon a radiative heating rate of ~1 K h-1 was found between 1.3 and 10 m for clear calm days. The availability of these radiation divergence measurements enables evaluation of the model performance for the temperature tendency caused by radiation divergence. The mesoscale model MM5 performs poorly for the stable boundary layer, because it overestimates the surface temperature and wind speed, while it underestimates the magnitude of radiative cooling. Some computationally efficient methods based on physical modeling, statistical modeling, and dimensional analysis are proposed by examining the gathered data set. The physical modeling approach appears to perform best.