地表土壤水分是控制水循环、碳循环以及陆地与大气之间能量交换的关键变量。目前,L波段的被动微波观测被认为是获取表层土壤水分信息的最佳波段。但是,被动微波空间分辨率低,不足以满足水文模型、天气预报、农业规划和水资源管理等应用...地表土壤水分是控制水循环、碳循环以及陆地与大气之间能量交换的关键变量。目前,L波段的被动微波观测被认为是获取表层土壤水分信息的最佳波段。但是,被动微波空间分辨率低,不足以满足水文模型、天气预报、农业规划和水资源管理等应用的需求。被动微波遥感的直接观测值是亮度温度(Brightness Temperature,TB),因此获取高分辨率的亮度温度是获取高分辨率土壤水分的基础。针对这一问题,本研究以时间序列回归(Time Series Regression,TSR)方法为基础,引入微波植被指数(Microwave Vegetation Index,MVI)削弱植被信息对降尺度模型的影响,利用先进微波扫描辐射计(Advanced Microwave Scanning Radiometer-2,AMSR-2)的X波段高分辨率亮温信息来提高土壤湿度主被动计划(Soil Moisture Active and Passive,SMAP)L波段亮温的空间分辨率。通过使用青藏高原L波段地基微波辐射计观测数据对降尺度结果进行验证,结果表明:TSR-MVI降尺度亮温在精度上能与SMAP原始数据保持一致,在垂直极化下的均方根误差(RMSE)最小为9.864 K,相关系数(R)最大为0.861;空间细节方面,基于TSR-MVI方法的降尺度结果优于Backus-Gilbert最优插值的结果,信息量更大,图像的清晰度更高。该方法能够对L波段SMAP亮温进行降尺度,其结果优于BG产品。展开更多
In view of the extremely low sea ice concentration(SIC) appeared at high latitudes of the Arctic in the summer of 2010, the changes of SIC in the central Arctic from 2010 to 2017 were investigated in this paper based ...In view of the extremely low sea ice concentration(SIC) appeared at high latitudes of the Arctic in the summer of 2010, the changes of SIC in the central Arctic from 2010 to 2017 were investigated in this paper based on the AMSR-E/AMSR-2 SIC products retrieved by the NT2 algorithm. The results show that the extremely low sea ice concentration in the central Arctic not only occurred in 2010 but also occurred again in 2016, and the daily average sea ice concentration(ASIC) reached a minimum of 0.70, which was significantly lower than the value of 0.78 in 2010 and became a new historical low record. A large area of sea ice in the sector 150°E–180° in 2010 disappeared in 2016, which was the most important difference to produce the new minimum. Also, the ice edge in 2016 retreated into the 85°N circle, whereas in 2010 it was far from the central Arctic. In 2010 and 2016, there were high correlations between the wind stress curl and the relative variation rate of ASIC, which indicates that wind stress curl(WSC) drove the divergence of sea ice. It directly leads to the decrease in the SIC and is the main cause of the extremely low SIC events. The results in this paper show that the decline of Arctic sea ice is represented by not only the reduction of sea ice coverage but also the reduction of SICs. The central Arctic has always been covered by large amount of sea ices, so the drastic reduction of SIC will not only change the structure of the ice field, but also lead to critical climatic effects that deserve further attention.展开更多
文摘地表土壤水分是控制水循环、碳循环以及陆地与大气之间能量交换的关键变量。目前,L波段的被动微波观测被认为是获取表层土壤水分信息的最佳波段。但是,被动微波空间分辨率低,不足以满足水文模型、天气预报、农业规划和水资源管理等应用的需求。被动微波遥感的直接观测值是亮度温度(Brightness Temperature,TB),因此获取高分辨率的亮度温度是获取高分辨率土壤水分的基础。针对这一问题,本研究以时间序列回归(Time Series Regression,TSR)方法为基础,引入微波植被指数(Microwave Vegetation Index,MVI)削弱植被信息对降尺度模型的影响,利用先进微波扫描辐射计(Advanced Microwave Scanning Radiometer-2,AMSR-2)的X波段高分辨率亮温信息来提高土壤湿度主被动计划(Soil Moisture Active and Passive,SMAP)L波段亮温的空间分辨率。通过使用青藏高原L波段地基微波辐射计观测数据对降尺度结果进行验证,结果表明:TSR-MVI降尺度亮温在精度上能与SMAP原始数据保持一致,在垂直极化下的均方根误差(RMSE)最小为9.864 K,相关系数(R)最大为0.861;空间细节方面,基于TSR-MVI方法的降尺度结果优于Backus-Gilbert最优插值的结果,信息量更大,图像的清晰度更高。该方法能够对L波段SMAP亮温进行降尺度,其结果优于BG产品。
基金funded by the National Natural Science Foundation of China (No.41976022)the Global Change Research Program of China (No.2015CB953900)。
文摘In view of the extremely low sea ice concentration(SIC) appeared at high latitudes of the Arctic in the summer of 2010, the changes of SIC in the central Arctic from 2010 to 2017 were investigated in this paper based on the AMSR-E/AMSR-2 SIC products retrieved by the NT2 algorithm. The results show that the extremely low sea ice concentration in the central Arctic not only occurred in 2010 but also occurred again in 2016, and the daily average sea ice concentration(ASIC) reached a minimum of 0.70, which was significantly lower than the value of 0.78 in 2010 and became a new historical low record. A large area of sea ice in the sector 150°E–180° in 2010 disappeared in 2016, which was the most important difference to produce the new minimum. Also, the ice edge in 2016 retreated into the 85°N circle, whereas in 2010 it was far from the central Arctic. In 2010 and 2016, there were high correlations between the wind stress curl and the relative variation rate of ASIC, which indicates that wind stress curl(WSC) drove the divergence of sea ice. It directly leads to the decrease in the SIC and is the main cause of the extremely low SIC events. The results in this paper show that the decline of Arctic sea ice is represented by not only the reduction of sea ice coverage but also the reduction of SICs. The central Arctic has always been covered by large amount of sea ices, so the drastic reduction of SIC will not only change the structure of the ice field, but also lead to critical climatic effects that deserve further attention.
