Daily Air Temperature Estimation On Glacier Surfaces In The Tibetan Plateau Using Modis Lst Data

• Other Authors: Zhang, Hongbo (authoraut), Zhang, Fan (authoraut), Zhang, Guoqing (authoraut), Ma, Yaoming (authoraut), Yang, Kun (authoraut), Ye, Ming (authoraut)
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2018
• Subjects: Journal of Glaciology
• Online Access: https://diginole.lib.fsu.edu/islandora/object/fsu%3A605146/datastream/TN/view/Daily%20Air%20Temperature%20Estimation%20On%20Glacier%20Surfaces%20In%20The%20Tibetan%20Plateau%20Using%20Modis%20Lst%20Data.jpg

The 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 (nighttime 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 degrees 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 degrees 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. Keywords: remote sensing, in-situ, mass-balance, altitudinal dependence, clear-sky, cloud contamination, energy-balance model, estimating daily maximum, glacier meteorology, ground measurements, ice temperature, imaging spectroradiometer data, temporal variations Publication Note: The publisher's version of record is available at https://doi.org/10.1017/jog.2018.6