Compound dry-hot events on Qinghai-Tibet Plateau and their effects on vegetationEI北大核心CSCD

基于Copula函数联合标准化降水指数(SPI)和标准化地表温度指数(SLTI),构建了复合干热事件指数(CDHI)用于评价青藏高原复合干热事件,分析了2000—2019年夏季干旱和高温的时空变化特征,探究了降水和地表温度对复合干热事件的相对贡献度及不同植被对复合干热事件的响应程度。结果表明:SPI与SLTI拟合效果最好的函数为Gaussian Copula函数,CDHI与标准化增强型植被指数(SEVI)拟合效果最好的函数也为Gaussian Copula函数;青藏高原夏季干热情况有轻微加重的趋势,4种植被类型中草地和林地的干热情况加重,干热情况在空间上呈现北部减缓、南部加重的趋势;SLTI持续增大是复合干热事件严重程度加重的主要原因,农田的SPI、SLTI对CDHI变化的相对贡献度差值最大,分别为0.71和0.29;东北部的植被生长易受复合干热事件影响,农田对复合干热事件最为敏感。

Compound dry-hot events on Qinghai-Tibet Plateau and their effects on vegetation

Based on the Copula function combined with the standardized precipitation index (SPI) and the standardized land surface temperature index (SLTI), the compound dry-hot events index (CDHI) was constructed to evaluate the compound dry-hot events and applied to the Qinghai Tibet Plateau as an example. The spatiotemporal changes of drought and high temperature in summer from 2000 to 2019 were investigated to explore the relative contribution of precipitation and land surface temperature to the compound dry-hot events and the response of different vegetation types to the compound dry-hot events. The results show that Gaussian Copula is the most appropriate distribution function for fitting SPI and SLTI as well as CDHI and standardized enhanced vegetation index(SEVI). The summer dry-hot situation in the study area shows a slight aggravation trend. Among the four vegetation types, the dry-hot situation in grasslands and forests intensifies, and the dry-hot situation shows a spatial trend of slowing down in the north and worsening in the south. The continuous increase in SLTI is the main reason for the aggravation of the severity of compound dry-hot events, with the relative contribution differences of SPI and SLTI in farmland to CDHI changes are the largest, with values of 0.71 and 0.29, respectively. The vegetation growth in the northeast is easily affected by compound dry-hot events, and farmland is the most sensitive to compound dry-hot events.