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Background: In recent years, the meteorological extreme events have caused the direct economic losses and human mortality increased significantly. While there has been a paucity of information regarding trends in meteorological disasters in Xinjiang. Based on two extreme climate measurements, i.e., the Palmer Drought Severity Index (PDSI) and the agricultural disaster area, the influence of meteorological disasters on agriculture were analyzed during the period 1960-2010. Results: (1) Temperature extremes exhibited patterns consistent with warming, with a large proportion of stations having statistically significant trends. The warming trends in the indices derived using daily minimum temperatures were greater than those obtained using maximum temperatures. Most of the precipitation indices exhibited increasing trends across the region, and the increased precipitation was due to the increase in both precipitation frequency and intensity. (2) The drought indices increased significantly in most regions of Xinjiang, and the seasonal PDSI exhibited significant correlations with the annual PDSI. For the entire geographical study area, two contrasting periods were evident in the PDSI between 1961 and 2010. Wet conditions dominated from 1987 to 2010, whereas persistent drought conditions occurred from 1960 to 1986. (3) Increased climate extremes resulted in increased agricultural disaster area. During warm summers, the droughts intensified; the corresponding snowmelt flood also became stronger. In addition, the sharply reduced effective irrigation area exacerbated the increased agricultural disaster area.
Data of flood, drought, hailstorms, and low temperature events in Xinjiang from 1949 to 2012 were analyzed with the diffusion method to assess the risk of the most common types of disasters in Xinjiang. It was proved that the frequency and intensity of meteorological disasters of the study area showed an increasing trend associated with global warming. Among the four types of disasters, surpass probability of drought was the largest, followed by hailstorm, low temperature and flood in turn. Moreover, the wavelet method analysis revealed that greater oscillations had occurred since 2000, which may be associated with the occurrence of extreme climatic changes. The spatial distribution of frequencies reveals that the northern slope of Tianshan Mountains is a multiple disaster area, the southern slope of Tianshan is the area where more floods and hailstorms occur, and the west of Turpan-Hami Basin is the area wind is prevalent. The relationships between disaster-affected areas and corresponding meteorological and socio-economic indexes were also analyzed. It indicated that there were significant positive correlations between the areas affected and the most meteorological and socio-economic indicators except the grain acreage.
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