The USGS (United States Geological Survey) land-use data used in the Weather Research and Forecasting (WRF) model have become obsolete as they are unable to accurately represent actual underlying surface features. Therefore, this study developed a new multi-satellite remote-sensing land-use dataset based on the latest GLC2015 (Global Land Cover, 2015) land-use data, which had 300 m spatial resolution. The new data were used to update the default USGS land-use dataset. Based on observational data from national meteorological observing stations in Xinjiang, northwest China, a comparison of the old USGS and new GLC2015 land-use datasets in the WRF model was performed for July 2018, where the simulated variables included the sensible heat flux (SHF), latent heat flux (LHF), surface skin temperature (Tsk), two-meter air temperature (T2), wind speed (Winds), specific humidity (Q2) and relative humidity (RH). The results indicated that there were significant differences between the two datasets. For example, our statistical verification results found via in situ observations made by the MET (model evaluation tools) illustrated that the bias of T2 decreased by 2.54%, the root mean square error (RMSE) decreased by 1.48%, the bias of Winds decreased by 10.46%, and the RMSE decreased by 6.77% when using the new dataset, and the new parameter values performed a net positive effect on land–atmosphere interactions. These results suggested that the GLC2015 land-use dataset developed in this study was useful in terms of improving the performance of the WRF model in the summer months.
The terrain of Central Asia is complex and rugged over mountains. Consequently, wind speed is overestimated over mountains and plains when using the Weather Research Forecast (WRF) model in winter. To solve this problem, three different simulations (named as control simulation (CRTL), gravity waves (GWD), and flow-blocking drag (FBD), respectively) were designed to investigate the impact of sub-grid orography (gravity waves and flow-blocking drag) on wind forecasts. The results illustrated that near-surface wind-speed overestimations were alleviated when sub-grid orographic drag was used in GWD, though the upper-level wind fields at 500 hPa were excessively reduced compared to CRTL. Thus, we propose eliminating the gravity wave breaking at the upper level to improve upper-level wind underestimations and surface wind speeds at the same time. The sub-grid orographic drag stress of the vertical profile over mountains was reduced when only the flow-blocking drag was retained in FBD. This alleviated underestimations of the upper-level wind speed and near-surface wind, which both have the same positive effects as the gravity wave and flow-blocking total. The mean bias and root mean squared error reduced by 32.76% and 9.39%, respectively, compared to CRTL. Moreover, the temperature and specific humidity in the lower troposphere were indirectly improved. The results of the study demonstrate that it is better to remove sub-grid orographic gravity wave drag when using the gravity wave drag scheme of the WRF model.
Surface albedo is one of the key parameters of land surface radiation and energy balance. As surface albedoes for visible and near-infrared solar radiation are quite different, solar radiation partitioning is important to parameterize the total surface albedo and upward solar radiation. In this paper, a surface albedo parameterization scheme was introduced and a solar radiation partitioning method was developed to improve the simulation of the upward solar radiation. The simulation results were validated in a hinterland site of the Taklimakan Desert. The surface albedo is not only associated with the soil moisture, but associated with the solar zenith angle. The solar radiation partitioning method considers the joint influences of cloud cover, near-surface air pressure, and solar zenith angle and was compared with the method using the Simple Biosphere Model version 3 (SiB3). The total albedo depends on the partitioning of the total visible and near-infrared radiations. The results indicate the surface albedo parameterization scheme is important to parameterize the upward solar radiation. The new solar radiation partitioning method could improve the simulation result.
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