The use of microwave radiometer data for characterizing snow storage in western China

Abstract

In this study a new microwave snow retrieval algorithm was developed to account for the effects of atmospheric emission on microwave radiation over high-elevation land areas. This resulted in improved estimates of snow-covered area in western China when compared with the meteorological station data and with snow maps derived from visible imagery from the Defense Meteorological Satellite Program satellite. Some improvement in snow-depth estimation was also achieved, but a useful level of accuracy will require additional modifications tested against more extensive ground data.

Spatial and temporal variations of snow cover in the Loess Plateau, China

“…() examined the influence of Himalayan glaciers and snow cover ablation on basin run‐off, and Chang et al . () estimated the snow water reserve in western China.…”

“…Snow cover remains an important water resource in semi-arid and arid areas (Shi et al, 2007). Singh and Bengtsson (2005) and Singh et al (2006) examined the influence of Himalayan glaciers and snow cover ablation on basin run-off, and Chang et al (1992) estimated the snow water reserve in western China. Xin et al (2010) reported that precipitation on the Loess Plateau significantly decreased from 1956 to 2008, and Wang et al (2012) reached a similar conclusion.…”

Changes in North American snowpacks for 1979–2007 detected from the snow water equivalent data of SMMR and SSM/I passive microwave and related climatic factors

“…[]. Field measurements at large scales are logistically difficult and expensive, but there have been some intensive field studies conducted to validate remotely sensed SWE with observation such as the Cold Land Processes Experiment [ Cline et al ., , ], the SnowSTAR2002 Transect [ Shi et al ., ], and others [e.g., Langlois et al ., ; Yueh et al ., ; Derksen , ; Derksen and Walker , ; Mote et al ., ; Chang et al ., ]. Using measurements from snow course transects in the former Soviet Union, Armstrong and Brodzik [] found that nearly all retrieval algorithms (e.g., horizontal‐based polarization algorithm of Chang et al .…”

“…A good summary of these instruments can be found in Kelly et al [2003]. Field measurements at large scales are logistically difficult and expensive, but there have been some intensive field studies conducted to validate remotely sensed SWE with observation such as the Cold Land Processes Experiment [Cline et al, 2003, the SnowSTAR2002 Transect [Shi et al, 2009], and others [e.g., Langlois et al, 2010;Yueh et al, 2009;Derksen, 2008;Mote et al, 2003;Chang et al, 1991]. Using measurements from snow course transects in the former Soviet Union, Armstrong and Brodzik [2002] found that nearly all retrieval algorithms (e.g., horizontalbased polarization algorithm of Chang et al [1987] and vertical-based counterpart of Goodison et al [1990]) of passive-microwave data tend to underestimate SWE, especially as the forest cover density begins to exceed 30%-40%.…”

Comparasion on snow depth algorithms over China using AMSR-E passive microwave remote sensing

“…To compare and verify the accuracy of different passive microwave snow-depth algorithms in different regions of China, the author of the paper chose 5 algorithms, i.e. Chang algorithm [1], GSFC 96 algorithm [6], AMSR-E SWE algorithm (NASA operational algorithm), the Qinghai-Tibet Plateau (QTP) algorithm [8] and Savoie algorithm with atmospheric correction [9], and carried out a comparative study on their accuracy and regional applicability in Xinjiang, the Qinghai-Tibetan plateau, Inner Mongolia, Northwest China, 4 stable snow-covered areas in Northeast China and 2 unstable snow-covered areas in North China Plain, using the brightness temperature data and ground-measured data obtained during the three days from Feb. 10 to Feb. 12, 2010. …”