Surveying the Cryosphere Aloft High Summits and Below Deep Soils: Applications for Monitoring and Modeling the Mountain Land Surface with Remotely Sensed Estimates, Reanalysis Datasets, and In-Situ Observations 35 views

The cryosphere is an essential component of high mountain systems. The hydrologic balance of montane environments is intricately linked to the thermal balance at the near to deep subsurface, from glaciers and periodic snowfall to permafrost and seasonally frozen grounds. As global average temperatures rise, the accelerating loss of glacial mass, increasing variability of precipitation events, and gradual thawing of soils in the cryosphere pose significant dangers to the health and livelihoods of mountains communities from the Andes to the Himalayas. The nonlinearity and locality of elevation-dependent warming effects and land surface dynamics in topographically complex regions, however, impedes the transferability of engineering solutions or policy decisions designed around a singular set or source of data. Thus, multimodal methods are required to understand not only emerging patterns at the regional scale, but also local phenomena that may be unique to a mountain valley or hillslope. Unfortunately, the scarcity of high-altitude land surface observations prevents more robust calibration and validation of models that rely on the plethora of datasets that have become available with the rise of remote sensing technologies and high-performance computing. To reduce the uncertainty associated with measurement accuracy and precision in alpine systems, this dissertation treks through three studies in order of increasing granularity and domain depth to assess and quantify both warming conditions and modeling capabilities in the mountain cryosphere. The first surveys the Andes Cordillera with remotely sensed and modeled estimates of surface temperatures and snow cover to determine seasonal trends at categorized elevation bands. The second explores an empirical technique for delineating permafrost extent across High Mountain Asia and qualifies the practicality of employing satellite-based temperature retrievals to classify permafrost zonation with modeled snow depth and soil moisture estimates. The third diagnoses the viability of calibration-free simulations using an experimental framework for comparing steady state and transient predictions, given either the presence or absence of in situ observations above and below the ground, of deep permafrost temperatures in the Tibetan Plateau.

PHD (Doctor of Philosophy)

permafrost; snow; soil moisture; temperature; mountain; land surface modeling; remote sensing; hydrology

English

2026-04-22