Date of Award
Winter 2024
Project Type
Dissertation
Program or Major
Civil and Environmental Engineering
Degree Name
Doctor of Philosophy
First Advisor
Jennifer Jacobs
Abstract
Freezing conditions affect more than half of the exposed land in the Northern Hemisphere in cold seasons, where transitions between frozen and thawed states impact surface and subsurface water and energy budget. Recognized as an Essential Climate Variable (ECV), accurate, reliable and efficient estimates of soil freeze/thaw (FT) processes with a moderate spatiotemporal resolution are needed to fully resolve highly-dynamic processes taking place at the land-atmosphere interface. Active microwave remote sensing and land surface modeling are promising tools for advancing the monitoring of FT as an ECV. My dissertation addresses key scientific gaps in estimating soil FT conditions using active microwave remote sensing and land surface modeling to establish a foundation for improving the applicability, efficiency, and accuracy of these techniques and to reduce uncertainties in their estimates. For microwave remote sensing, my work presented the General Threshold Approach (GTA), a computationally efficient method to monitor FT processes using Synthetic Aperture Radar (SAR) observations at spatial resolution of 100 m or finer. The GTA achieved performance comparable to the widely recognized Seasonal Threshold Approach (STA) but addressed the computational limitations inherent in STA. This computational efficiency makes GTA suitable for the operational application of SAR observations across large spatial domains with sub-field-scale resolution. Such capability is particularly valuable for identifying ground conditions that may hinder the crop-growing season. My dissertation also explored the applicability of an interferometric coherence approach (ICA) for FT detection under shallow and intermittent snowpacks. While SAR imagery showed promise for retrieving soil FT states, the low temporal resolution of current instruments may limit its effectiveness in regions with dynamic winter conditions. In such cases, land surface models (LSMs), capable of delivering daily to sub-daily estimates, could prove highly valuable for estimating soil thermal conditions. Yet, our understanding of their skill in simulating FT processes and the uncertainties associated with their estimates is still limited. To address this gap, a nine-member ensemble was employed to quantify the spatial and inter-annual variability of winter soil characteristics across North America. Model simulations were also compared with in-situ observations to characterize the biases in model FT estimates over a wide range of snow regimes. My work demonstrated that differences in LSMs could become the dominant factor driving variability in winter soil characteristics rather than forcing data. My study also showed that errors and uncertainty in snow processes appear to notably impact differences in modeled versus observed soil temperatures throughout the entire winter. Given the importance of soil and snow interaction, the last chapter of my dissertation focused on an operational LSM (Noah-Multiparameterization) to characterize how variation in representations of snow processes impact temporal evolution of soil thermal dynamics across transitional and ephemeral snow covers in the Northeast USA. My analysis demonstrated that the choice of schemes to parameterize precipitation phase partitioning and snow thermal conductivity causes uncertainty in winter soil temperature, regardless of snow cover class. It also highlighted the need to reevaluate snow parameterization schemes for shallow, temporally discontinuous snowpacks in the Northeast USA.
Recommended Citation
MoradiKhaneghahi, Mahsa, "OBSERVING AND ESTIMATING SOIL FREEZE THAW PROCESSES: FROM REMOTE SENSING TO LAND SURFACE MODELING" (2024). Doctoral Dissertations. 2887.
https://scholars.unh.edu/dissertation/2887