Characterization of Antarctic Firn by Multi-Frequency Passive Remote Sensing from Space
This project will test the hypothesis that physical and thermal properties of Antarctic firn--partially compacted granular snow in an intermediate stage between snow and glacier ice--can be remotely measured from space. Although these properties, such as internal temperature, density, grain size, and layer thickness, are highly relevant to studies of Antarctic climate, ice-sheet dynamics, and mass balance, their measurement currently relies on sparse in-situ surveys under challenging weather conditions. Sensors on polar-orbiting satellites can observe the entire Antarctic every few days during their years-long lifetime. Consequently, the approaches developed in this study, when coupled with the advancing technologies of small and low-cost CubeSats, aim to contribute to Antarctic science and lead to cost-effective, convenient, and accurate long-term analyses of the Antarctic system while reducing the human footprint on the continent. Moreover, the project will be solely based on publicly-available datasets; thus, while contributing to interdisciplinary undergraduate and graduate research and education at the grantee's institution, the project will also encourage engagement of citizen scientists through its website. The overarching goal of this project is to characterize Antarctic firn layers in terms of their thickness, physical temperature, density, and grain size through multi-frequency microwave radiometer measurements from space. Electromagnetic penetration depth changes with frequency in ice; thus, multi-frequency radiometers are able to profile firn layer properties versus depth. To achieve its objective, the project will utilize the Global Precipitation Measurement (GPM) satellite constellation as a single multi-frequency microwave radiometer system with 11 frequency channels observing the Antarctic Ice Sheet. Archived in-situ measurements of Antarctic firn density, grain size, temperature, and layer thickness will be collected and separated into training and test datasets. Microwave emissions simulated using the training data will be compared to GPM constellation measurements to evaluate and improve state-of-the-art forward microwave emission models. Based on these models, the project will develop numerical retrieval algorithms for the thermal and physical properties of Antarctic firn. Results of retrievals will be validated using the test dataset, and uncertainty and error analyses will be conducted. Lastly, changes in the thermal and physical characteristics of Antarctic firn will be examined through long-term retrieval studies exploiting GPM constellation measurements.
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