摘要
An ensemble method was used to combine three surface soil moisture products,retrieved from passive microwave remote sensing data,to reconstruct a monthly soil moisture data set for China between 2003 and 2010.Using the ensemble data set,the temporal and spatial variations of surface soil moisture were analyzed.The major findings were:(1) The ensemble data set was able to provide more realistic soil moisture information than individual remote sensing products;(2) during the study period,the soil moisture increased in semiarid regions and decreased in arid regions with anoverall drying trend for the whole country;(3) the soil moisture variation trends derived from the three retrieval products and the ensemble data differ from each other but all data sets show the dominant drying trend for the summer,and that most of the drying regions were in major agricultural areas;(4) compared with the precipitation trends derived from Global Precipitation Climatology Project data,it is speculated that climate change is a possible cause for the drying trend in semiarid regions and the wetting trend in arid regions;and (5) combining soil moisture trends with land surface temperature trends derived from Moderate Resolution Imaging Spectroradiomete,the study domain was divided into four categories.Regions with drying and warming trends cover 33.2%,the regions with drying and cooling trends cover 27.4%,the regions with wetting and warming trends cover 21.1% and the regions with wetting and cooling trends cover 18.1%.The first two categories primarily cover the major grain producing areas,while the third category primarily covers nonarable areas such as Northwest China and Tibet.This implies that the moisture and heat variation trends in China are unfavorable to sustainable development and ecology conservation.
An ensemble method was used to combine three surface soil moisture products, retrieved from passive microwave remote sensing data, to reconstruct a monthly soil moisture data set for China between 2003 and 2010. Using the ensemble data set, the temporal and spatial variations of surface soil moisture were analyzed. The major findings were： （1） The ensemble data set was able to provide more realistic soil moisture information than individual remote sensing products; （2） during the study period, the soil moisture increased in semiarid regions and decreased in arid regions with anoverall drying trend for the whole country; （3） the soil moisture variation trends derived from the three retrieval products and the ensemble data differ from each other but all data sets show the dominant drying trend for the summer, and that most of the drying regions were in major agricultural areas; （4） compared with the precipitation trends derived from Global Precipitation Climatology Project data, it is speculated that climate change is a possible cause for the drying trend in semiarid regions and the wetting trend in arid regions; and （5） combining soil moisture trends with land surface temperature trends derived from Moderate Resolution Imaging Spectroradiomete, the study domain was divided into four categories. Regions with drying and warming trends cover 33.2%, the regions with drying and cooling trends cover 27.4%, the regions with wetting and warming trends cover 21.1% and the regions with wetting and cooling trends cover 18.1%. The first two categories primarily cover the major grain producing areas, while the third category primarily covers nonarable areas such as Northwest China and Tibet. This implies that the moisture and heat variation trends in China are unfavorable to sustainable development and ecology conservation.
基金
supported by the National Natural Science Foundation of China(51109111 and 40930530)
Tsinghua University Initiative Research Program(2011081132)
