Abstract
Land-surface characteristics (LSCs) and land-soil moisture conditions can modulate energy partition at the land surface, impact near-surface atmosphere conditions, and further affect land–atmosphere interactions. This study investigates the effect of land-surface-characteristic parameters (LSCPs) including albedo, leaf-area index (LAI), and soil moisture (SM) on hot weather by in East China using the numerical model. Simulations using the Weather Research and Forecasting (WRF) Model were conducted for a hot weather event with a high spatial resolution of 1 km in domain 3 by using ERA-Interim forcing fields on 20 July 2017 until 16:00 UTC on 25 July 2017. The satellite-based albedo and LAI, and assimilation-based soil-moisture data of high temporal–spatial resolution, which are more accurate to match fine weather forecasts and high-resolution simulations, were used to update the default LSCPs. A control simulation with the default LSCPs (WRF_CTL), a main sensitivity simulation with the updated LSCP albedo, LAI and SM (WRF_CHAR), and a series of other sensitivity simulations with one or two updated LSCPs were performed. Results show that WRF_CTL could reproduce the spatial distribution of hot weather, but overestimated air temperature (Ta) and maximal air temperature (Tamax) with a warming bias of 1.05 and 1.32 °C, respectively. However, the WRF_CHAR simulation reduced the warming bias, and improved the simulated Ta and Tamax with reducing relative biases of 33.08% and 29.24%, respectively. Compared to the WRF_CTL, WRF_CHAR presented a negative sensible heat-flux difference, positive latent heat flux, and net radiation difference of the area average. LSCPs modulated the partition of available land-surface energy and then changed the air temperature. On the basis of statistical-correlation analysis, the soil moisture of the top 10 cm is the main factor to improve warming bias on hot weather in East China.
Highlights
IntroductionThe intensity and frequency of hot weather are generally rising [1]
With global warming, the intensity and frequency of hot weather are generally rising [1]
Another issue related to numerical simulations is high-resolution simulations, which are required both for understanding regional weather and climate, and for hydrological and ecosystem studies [32,33]; this can produce good results and reduce errors [33]
Summary
The intensity and frequency of hot weather are generally rising [1]. By using satellite-based land cover/use, green-vegetation fraction, leaf-area index (LAI), and albedo, simulated results are significantly improved [18,19,20]. Proper SM is crucial to performing hydrometeorological processes for numerical simulations, especially for short-term simulations [24,31] Another issue related to numerical simulations is high-resolution simulations (with grid spaces of a few km), which are required both for understanding regional weather and climate, and for hydrological and ecosystem studies [32,33]; this can produce good results and reduce errors [33]. In the present study, using the method of fine weather forecast and high-resolution simulation to investigate the impact of LSCPs on hot weather in EC, the land-surface condition near-real-time satellite-based MODIS albedo and LAI data, and assimilation-based SM data were integrated into the WRF model to improve the air-temperature simulation on hot weather in EC.
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