Abstract
Abstract. Snow cover on the Qinghai–Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms should be developed to retrieve snow depth with higher spatial resolution and should consider the variation in brightness temperatures at different frequencies emitted from ground with changing ground features.
Highlights
The Qinghai–Tibetan Plateau (QTP) is considered the third pole of the world and the Asian water tower (Kang et al, 2010; Wu and Qian, 2003; Wang et al, 2015; Immerzeel et al, 2010; Xu et al, 2008)
The MODIS snow cover fraction product, meteorological station observations and field campaign snow depth observations are compared with the AMSR-E/Advanced Microwave Scanning Radiometer-2 (AMSR2) snow cover, and snow depths observed at meteorological stations and field experiments are compared with AMSR-E/AMSR2 snow depths
This study presented the accuracy of a snow depth product derived from passive microwave (PMW) by comparing MODIS snow cover fraction and in situ data, and it analyzed the potential causes resulting from the uncertainties of the product
Summary
The Qinghai–Tibetan Plateau (QTP) is considered the third pole of the world and the Asian water tower (Kang et al, 2010; Wu and Qian, 2003; Wang et al, 2015; Immerzeel et al, 2010; Xu et al, 2008). The NASA snow water equivalent product derived from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) generally tends to underestimate snow depth in North America (Tedesco and Narvekar, 2010) when compared with World Meteorological Organization (WMO) and Snow Data Assimilation System (SNODAS) but overestimate in northwest and northeast of China (Dai et al, 2012; Che et al, 2016) when compared with meteorological station and field work observations These authors pointed out that the errors primarily came from the spatiotemporal variability of grain size and forest cover. When the derived snow cover fractions were compared to Landsat-7 Enhanced Thematic Mapper ground-truth observations covering a substantial range of snow cover conditions, the correlation coefficients were near 0.9 and the RMSE were near 0.10 (Salomonson and Appel, 2006)
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