Remote sensing of snow using active and passive microwave instruments

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The Earth's seasonal snow cover exerts an important effect on climate and on water resources, transportation and agriculture, and related socio-economic activities in many countries of the world. The presence of snow and its albedo effect on the climate system influences climate state and can affect climate dynamics through amplified warming in polar and mountain regions. Snow also accounts for a significant portion of the Earth's useable freshwater. Knowledge of accumulated snow water equivalent (SWE) informs water managers of how much melt can be expected in spring. The long term objectives of this research are to develop improved snow accumulation estimates (SWE or snow depth) from satellite remote sensing instruments for use in river forecasting and for a better understanding of how snow accumulation is changing in the Earth's system. To achieve this, three primary objectives are defined. (1) develop a new high spatial resolution radar remote sensing approach for SWE estimation, particularly in mountain terrain and forested areas, using state of the art ground-based radar measurements of snow. This will require deployment of radar instruments to different landscapes for key periods in the winter snow season (early season freeze, mid-season accumulation and late season melt) to observe and quantify changes in snow and characterize them to develop estimation methods. (2) Leverage recent research developments in retrieval science that combine active and passive microwave remote sensing measurements to enable improved SWE estimates at the passive microwave observation scale. Having enhanced the coarse resolution passive microwave SWE data, the proposal will explore downscaling methods (Bayesian) to to estimate SWE at higher spatial resolution and generate a time series from 1979- present. This links well with a satellite SWE algorithm development and maintenance project funded by the Japan Aerospace Exploration Agency. (3) develop my Web 2.0 initiative, Snowtweets, for leveraging crowdsourced data for augmenting existing in situ snow depth data from established networks (federal, provincial and regional utility levels).