Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6135-2021
https://doi.org/10.5194/gmd-14-6135-2021
Model evaluation paper
 | 
12 Oct 2021
Model evaluation paper |  | 12 Oct 2021

Influence on the temperature estimation of the planetary boundary layer scheme with different minimum eddy diffusivity in WRF v3.9.1.1

Hongyi Ding, Le Cao, Haimei Jiang, Wenxing Jia, Yong Chen, and Junling An

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Cited articles

Angevine, W. M.: An Integrated Turbulence Scheme for Boundary Layers with Shallow Cumulus Applied to Pollutant Transport, J. Appl. Meteorol., 44, 1436–1452, 2005. a, b
Angevine, W. M., Jiang, H., and Mauritsen, T.: Performance of an Eddy Diffusivity–Mass Flux Scheme for Shallow Cumulus Boundary Layers, Mon. Weather Rev., 138, 2895–2912, 2010. a, b, c
Banks, R. F., Tiana-Alsina, J., Baldasano, J. M., Rocadenbosch, F., Papayannis, A., Solomos, S., and Tzanis, C. G.: Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, and radiosondes during the HygrA-CD campaign, Atmos. Res., 176, 185–201, 2016. a
Bougeault, P. and Lacarrere, P.: Parameterization of orography-induced turbulence in a mesobeta–scale model, Mon. Weather Rev., 117, 1872–1890, 1989. a
Broxton, P. D., Zeng, X., Sulla-Menashe, D., and Troch, P. A.: A global land cover climatology using MODIS data, J. Appl. Meteorol. Clim., 53, 1593–1605, https://doi.org/10.1175/JAMC-D-13-0270.1, 2014. a
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Short summary
We performed a WRF model study to figure out the mechanism of how the change in minimum eddy diffusivity (Kzmin) in the planetary boundary layer (PBL) closure scheme (ACM2) affects the simulated near-surface temperature in Beijing, China. Moreover, the influence of changing Kzmin on the temperature prediction in areas with different land-use categories was studied. The model performance using a functional-type Kzmin for capturing the temperature change in this area was also clarified.
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