Next-Generation Large-Scale Fractional Freeze/Thaw Analysis

As water in various components of the Earth’s surface freezes, its movement is largely curtailed as are its impacts on climate, hydrology, ecology, and biogeochemical processes. Freezing and thawing processes are also closely related to the development and ablation of snowpack. Passive and active remote sensing has allowed near real-time, all-weather monitoring of the binary landscape freeze/thaw (FT) state. However, the limitations of microwave derived FT state as a binary switch limits the representation of very complex surface FT processes. Many of which can vary based on climate, land cover, and topographic variability.

The primary goals of this study are to provide a comprehensive analysis of existing FT products and their limitations, develop new algorithms to better capture FT state, as well as determine optimum in situ and aircraft observation strategies. To help achieve the latter goals, the use of targeted airborne and in-situ field campaigns such as the Manitoba Scanning L-Band Active Passive experiment (SLAPex 2015) and data from the NASA SnowEX project has been and is continuing to be utilized. Active participation in the planning of related field campaigns by the team is ongoing and will contribute to breakthroughs in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. Multi-scale (in-situ, drone, aircraft, and satellite) data collected during these campaigns is being used to examine surface FT heterogeneity in relation to climate and landscape properties such as topography, vegetation, and soils. Additional investigations into the use of global land surface temperature products are also being considered to improve surface FT characterization.

To date, the cross comparison of high-resolution targeted data sets with lower-resolution satellite-based products from the Earth System Data Record FT (FT-ESDR) and Soil Moisture Active Passive FT (SMAP-FT) has enabled the identification of gaps in FT representation. From these analyses we continue to explore the potential of developing a higher resolution and/or a fractional FT product that go beyond current methods by representing intermediate phases between frozen and thawed states. This includes identifying responses of various types of frozen or thawed ground that can vary temporally, with depth, and widely over varying landscape properties. Data fusion approaches have showed promise for improving the characterization of freeze types (near surface, deep soil, sporadic) as well as representing sub-pixel/fractional FT state.

Funded by NASA ROSES 2015 Terrestrial Hydrology Program

Team: Dr. Houser (PI); Dr. Maggioni (co-I); Mr. Johnston (Graduate Research Assistant)

Performance Period: July 2017 – July 2022