Research On Regional Extreme Drought Events And Their Numerical Simulation And Prediction In Xinjiang Area

Most parts of Xinjiang are in the arid area, which caused people become accustomed to the drought problems in the region, so insufficient attention was paid to its extreme drought problem. However, as the largest inland province in China, Xinjiang occupies around1/6of China’s land mass. The regional extreme drought in Xinjiang province persistently induces important influences on the agriculture and stock, the water resources, the national unity, the regional stability and the prosperity of Silk Road Economic Belt. It is obviously that studying the extreme drought problems in Xinjiang province will not only has an important scientific value, but also has an essential practical significance.In this paper, we first inspect the applicability of SPI indexes on the drought characterization, select the most optimal distribution function for suiting the characteristics of rainfall distribution in Xinjiang province, and calculate the SPI indexes based on the improved distribution function. Then the standard of extreme drought is defined,the extreme drought types are classified, and the extreme drought events sequence in Xinjiang province during the period of1961-2012are detected. Moreover, we select and simulate the typical extreme drought events of each region by using the regional climate model RegCM3, structure the optimal scheme of convective parameters by comparing the simulation results, and improve simulation model system which suitable for the drought climate simulation in Xinjiang province. Finally, we build the PSO_LSSVM models according to the different seasons and regions in Xinjiang province and forecast the drought events, respectively. The main results of this paper are as follows:1. The precipitation distributions of different time scales in Xinjiang province are fitted by using the six kinds of probability distribution functions, the results show that, on1month,3months and6months time scales, the Weibull distribution is the best to fit the precipitation reality, and thus the improved SPI index formulas are more suitable for studying the regional extreme droughts of Xinjiang province.2. The SPI indexes of49meteorological stations from1962to2012are calculated and analyzed from the improved SPI index.The results show that, in the recent51years, the extreme drought in Xinjiang province has a totally downward trend, and there is a mutationin1978. The wavelet analysis show that there are obvious differences between the periodic variation of different time during the past51years:before70’s of20th, the most significant cycle is5years; it is7years of predominant period in the late70’s and80’s of20th, and5year period mainly from the late80’s of20th to early21th, respectively; from2002, however,7years period is gradually appears again.3. Based on the calculation results and spatial distributions of the improved SPI indexes. The results show that, the extreme drought in Xinjiang province can be divided into three spatial distribution patterns by using the EOF and REOF methods:Northern Xinjiang type, Southern Xinjiang type and Eastern Xinjiang type. According our diagnosis on the weather elements and analysis to the circulation of the three kinds of extreme drought events, we find that, at the extreme drought events stages, the corresponding humidity field are partially drier, the downdraft flow are stronger, and the temperature are higher. Among them, the extreme drought events of Northern Xinjiang type and Eastern Xinjiang type are mainly caused by the stability of high ridge in Black Sea and the stronger geopotential height field in northern Xinjiang and Mongolia. Meanwhile, the extreme drought events of the Southern Xinjiang type are due to Iran subtropical high eastward expansion to the southern Xinjiang.4.From the numerical simulations for the typical cases of the three kinds of extreme drought spatial distribution types, we observe that the KUO scheme is suitable for the extreme drought events of Northern Xinjiang type and Eastern Xinjiang type,and that the Grell scheme is suitable for the extreme drought events of Southern Xinjiang type. Such results provide a useful reference for selecting appropriate parameterization scheme of the extreme drought events numerical simulation in Xinjiang province.5. By introducing the advanced PSO method into extreme drought events prediction, the values of two key parameters (y and a2) in LSSVM model can be objectively optimized, which excludes the subjective interferences and make the model more globally representative and universal. Then the PSO_LSSVM grade prediction model according to different regions and seasons are established based on the extreme drought events from1962to2012. The prediction testing shows that, after optimizing the key parameters, the predictive accuracy of regional extreme drought events in Xinjiang has a significant increase.Summarily, this paper selects the Weibull distribution as the most suitable distribution for detecting the extreme drought events in Xinjiang province, improve the original SPI indexes and make the model more suitable and useful to study Xinjiang’s extreme drought problems. By using the spatial distribution of improved SPI indexes, we divide the extreme droughts into three spatial distribution types:Northern Xinjiang type, Southern Xinjiang type and Eastern Xinjiang type, and clarify the corresponding circulation situations and physics characteristics.The numerical simulations results show that KUO scheme is good for the extreme drought events of Northern Xinjiang type and Eastern Xinjiang type, and Grell scheme is more matched to the extreme drought events of Southern Xinjiang type.Accordingly, we can optimize the parameterization schemes and distinctly improve the capability of the model system for regional extreme drought climate simulation in Xinjiang province. Also, the drought prediction models of different regions and seasons are establish based on PSO_LSSVM. All of these can provide the remarkable scientific basis and technical support for the detection,forecast and disaster prevention of the extreme drought events in Xinjiang province.