It has been a longstanding problem for current weather/climate models to accurately predict summer heavy precipitation
over the Yangtze-Huaihe Region (YHR) which is the key flood-prone area in China with intensive population and
developed economy. Large uncertainty has been identified with model deficiencies in representing precipitation processes
such as microphysics and cumulus parameterizations. This study focuses on examining the effects of microphysics
parameterization on the simulation of different type of heavy precipitation over the YHR taking into account two different
cumulus schemes. All regional persistent heavy precipitation events over the YHR during 2008-2012 are classified into
three types according to their weather patterns: the type I associated with stationary front, the type II directly associated
with typhoon or with its spiral rain band, and the type III associated with strong convection along the edge of the
Subtropical High. Sixteen groups of experiments are conducted for three selected cases with different types and a local
short-time rainstorm in Shanghai, using the WRF model with eight microphysics and two cumulus schemes. Results show
that microphysics parameterization has large but different impacts on the location and intensity of regional heavy
precipitation centers. The Ferrier (microphysics) –BMJ (cumulus) scheme and Thompson (microphysics) – KF (cumulus)
scheme most realistically simulates the rain-bands with the center location and intensity for type I and II respectively. For
type III, the Lin microphysics scheme shows advantages in regional persistent cases over YHR, while the WSM5
microphysics scheme is better in local short-term case, both with the BMJ cumulus scheme.
A typical heavy rainfall event occurred in Shanghai on September 13, 2009 was simulated using the Weather Research and Forecasting Model (WRF) to study the impact of microphysics parameterization on heavy precipitation simulations. Sensitivity experiments were conducted using the cumulus parameterization scheme of Betts-Miller-Janjic (BMJ), but with three different microphysics schemes (Lin et al, WRF Single-Moment 5-class scheme (WSM5) and WRF Single-Moment 6-class scheme (WSM6)) under three-way nested domains with horizontal resolutions of 36km, 12km and 4km. The results showed that all three microphysics schemes are able to capture the general pattern of this heavy rainfall event, but differ in simulating the location, center and intensity of precipitation. Specifically, the Lin scheme overestimated the rainfall intensity and simulated the rainfall location drifting northeastwards. However, the WSM5 scheme better simulated the rainfall location but stronger intensity than the observation, while the WSM6 scheme better produced the rainfall intensity, but with an unrealistic rainfall area.
This study calculated the land water storage using the time-varying monthly gravity data from the GRACE (Gravity Recovery and Climate Experience) gravity satellite combined with Gaussian smoothing filter. The characteristics of spatiotemporal variations of long-term regional land water storage derived from the linear fitting method were then examined from January 2003 to December 2013. The results showed that the water storage over the huang-huai-hai plain showed an overall declining trend from 2003 to 2013 and the average declining rate is about 2.86 mm/a. The comparison between the GEACE calculation results with the soil moisture content products from the global land data assimilation system (GLDAS) showed that they are very highly consistent. The variations of regional mean soil moisture over the huang-huai-hai plain also exhibited a downward trend from 2003 to 2013 with an average declining rate about 0.74 mm/a. Based on water balance equation, we obtained the change of average groundwater storage and it showed a decreasing variability with a general declining trend with an average rate about 2.22 mm/a. In addition, the retrieved groundwater data was proven to be accurate compared to observations from groundwater wells measurement with high consistency and correlations. . Further investigations focused on analyzing the impacts of precipitation factors on groundwater variations, implying that the human influences are the main reasons for the decline in groundwater.
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