A Comparison of First-Order Permafrost Estimates in High Mountain Asia Using Remotely Sensed Land Surface Temperature, Air Temperature, and Snow Reanalysis Products
Abstract
The projected thawing of alpine permafrost in the 21st century will trigger major challenges related to slope instability, carbon emissions, public health, and water resource management in mountain communities and their downstream neighbors. Thus, accurate estimates of permafrost extent at high resolution are desirable, especially in data sparse regions like HMA, where highly rugged terrain renders in-situ data collection difficult. By definition, a mean annual ground temperature (MAGT) of or below 0 °C for at least two consecutive years determines permafrost presence in a given area. However, the mean annual air temperature (MAAT) and increasingly, the mean annual land surface temperature (MALST) are often used as proxy variables in lieu of direct MAGT measurements due to the accessibility of weather station and remotely sensed observations. This research leverages the sampling frequency and spatial coverage of gap-filled daily MODIS (Moderate Resolution Imaging Spectroradiometer) LST and monthly AIRS (Atmospheric Infrared Sounder) AT products to map permafrost zonation indices (PZI) based on a cumulative normal distribution function used by Gruber (2012) in HMA. Additionally, mean snow depths for the HMA region provided by Liu et al. (2021) are incorporated into a modified equation based on weighted freezing/thawing degree day indices originally derived by Smith & Riseborough (2002) to account for the insulating effect of snow cover on the MAGT. Preliminary estimates of total permafrost area are calculated based on the resulting PZI for the following sub-regions of HMA: the Tien Shan (94,300 km2), Pamirs (159,000 km2), Hindu Kush (36,800 km2), Himalayas (151,000 km2), Qinghai-Tibetan Plateau (1,380,000 km2), and Hengduan (105,000 km2).
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.C35F0936K