Abstract
ABSTRACTThe MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data have been widely used for air temperature estimation in mountainous regions where station observations are sparse. However, the performance of MODIS LST in high-elevation glacierized areas remains unclear. This study investigates air temperature estimation in glacierized areas based on ground observations at four glaciers across the Tibetan Plateau. Before being used to estimate the air temperature, MODIS LST data are evaluated at two of the glaciers, which indicates that MODIS night-time LST is more reliable than MODIS daytime LST data. Then, linear models based on each of the individual MODIS LST products from two platforms (Terra and Aqua) and two overpasses (night-time and daytime) are built to estimate daily mean, minimum and maximum air temperatures in glacierized areas. Regional glacier surface (RGS) models (mean /-mean-square differences: 3.3, 3.0 and 4.8°C for daily mean, minimum and maximum air temperatures, respectively) show higher accuracy than local non-glacier surface models (mean root-mean-square differences: 4.2, 4.7 and 5.7°C). In addition, the RGS models based on MODIS night-time LST perform better to estimate daily mean, minimum and maximum air temperatures than using temperature lapse rate derived from local stations.
Highlights
Air temperature (Tair) is an important input for hydrological, ecological and climate models
It should be noted that compared with this study, a much larger RMSD was found for air temperature estimation from MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) in the Antarctic (Meyer and others, 2016) where ice sheets are widespread, which may be largely due to: (1) Antarctic area has more extremely low temperatures (
Since careful validation is the basis of efficient application of remotely sensed LST, MODIS LST data were first compared with in-situ LST measurements of automatic weather stations (AWSs) at two glaciers
Summary
Air temperature (Tair) is an important input for hydrological, ecological and climate models. Extensive studies related to recent global warming have demanded more representative air temperature observations, especially in high-elevation areas (Liu and Chen, 2000; Qin and others, 2009; Cai and others, 2017). The wellknown temperature lapse rate (TLR) with increasing elevation is commonly used for Tair interpolation (Li and others, 2013a), especially in glacierized basins over the TP (Zhang and others, 2013, 2015; Immerzeel and others, 2014; Gao and others, 2015). The limited number of stations within or near a mountainous river basin may create large uncertainty in the representativeness and accuracy of the estimated TLR, mainly because most stations are located in valley and lowaltitude areas (Zhang and others, 2016a)
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