Abstract
By using a coupled land surface-atmosphere model with initial conditions of varying resolution and ensembles of systematically changed soil moisture, convective-scale simulations of a typical frontal rainstorm in the Yangtze River Basin are collected to investigate: (1) effects of different datasets on the simulated frontal mesoscale convective systems (MCSs); (2) possible linkages between soil moisture, planetary boundary layer (PBL), MCSs and precipitation in this modeled rainstorm. Firstly, initial soil moisture differences can affect the PBL, MCSs and precipitation of this frontal rainstorm. Specially, for a 90 mm precipitation forecast, the Threat score (TS) can increase 6.61% by using the Global Land Data Assimilation System (GLDAS) soil moisture. Secondly, sensitivity experiment results show that the near-surface thermodynamic conditions are more sensitive to dry soil than wet due to the initial moist surface; atmosphere conditions have suppressed the relations between soil and atmosphere; and decreased precipitation can be found over both wet and dry surfaces. Generally, a positive feedback between soil moisture and the near-surface thermodynamic conditions is identified, while the relations between soil moisture and precipitation are quite complicated. This relationship shows a daytime mixing of warm surface soil over dry surfaces and a daytime evaporation of adequate moisture over wet surfaces. The large-scale forcing can affect these relations and finally cause decreased precipitation over both wet and dry surfaces.
Highlights
Soil moisture has been widely recognized as one of the key factors for rainfall prediction [1,2,3,4,5,6].The relationship between soil moisture and precipitation is typically described as a closed feedback loop [7,8,9]
A decrease in soil moisture may increase the clouds of the planetary boundary layer (PBL) in several observational cases [17,18], which has supported the negative relations between land surface moisture and its overlaying atmosphere
Since this study focuses on the relationships between soil moisture, PBL and precipitation, it is reasonable to consider both atmospheric forcing and soil moisture of varying resolutions and sophistications so as to determine a reliable performance of the mesoscale convective systems (MCSs) and surface-PBL simulations
Summary
Soil moisture has been widely recognized as one of the key factors for rainfall prediction [1,2,3,4,5,6]. The relationship between soil moisture and precipitation is typically described as a closed feedback loop [7,8,9] This feedback has been verified by many observational and numerical studies in the transition zones between dry and wet climatic regions, where the high coupling between the land surface and the planetary boundary layer (PBL) could significantly influence the mesoscale convective systems (MCSs) [10,11]. In the Yangtze River Basin, observational studies have reported that the correlations between soil moisture and atmosphere are notably positive in precipitation and negative in the near-surface temperature [41] These relationships are relatively significant during the local summertime [42]. Prediction, which is quite important for agricultural irrigation management [53,54,55,56]
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