Copulas函数在二维干旱变量空间分析中的应用

根据新疆地区41个气象站的长系列月降水资料,提取干旱历时、干旱烈度和烈度峰值3个干旱特征变量,基于8种单参数族的Copulas函数,结合ArcGIS9.3软件进行二维干旱变量的空间分析。经拟合优度评价,FrankCopula对干旱历时和干旱烈度、干旱历时和烈度峰值的拟合度最好;而Clayton Copula对于干旱烈度和烈度峰值的拟合效果最佳。二维变量联合超越概率值随单变量的值减小而增大;二维干旱变量中任一特征变量的条件概率随另一变量的增大而减小;干旱特征变量的条件发生概率在新疆地区从北到南依次递增。表明Copulas函数结合ArcGIS9.3软件能够描述二维干旱特征变量的空间演变规律。

Application of Copulas Function in Spatial Analysis of Two-dimension Drought Variables

Spatial analysis of drought variables is very important to the study of the evolution rules of drought events.Three drought variables,i.e.,drought duration,drought severity and drought peak,were selected from long sequence of monthly rainfall data in Xinjiang,China.Two-dimension joint distribution of drought variables and spatial analysis were analyzed based on 8 kinds of single parameter copulas functions combined with ArcGIS9.3 software for 41 weather stations in Xinjiang.The evaluation of goodness degree for fitting showed that,Frank copula function was best applied to drought duration and drought severity,also the best for drought duration and drought peak.Clayton copula function was best applied to drought severity and drought peak.The exceeding probability of two drought variables increased with the decrease of the single variable.The conditional probability of either variable in two decreased with the increase of another variable.And conditional probability of drought characteristic variables increased from the north to the south in Xinjiang.This study showed that Copulas function combining with ArcGIS9.3 software can describe evolution rule of two-dimensional drought variables.