More than one-sixth of the world’s population (~1.2 billion people) relies on seasonal snowpack and glaciers for their water supply. Snowmelt-generated water supply is likely to decrease this century. Snow is also a critical component of Earth’s cold regions ecosystems where wildlife, vegetation and snow have strongly interconnected fates.
To understand the time and space variation in the snow’s energy and mass balances along with the extensive feedbacks with the Earth’s climate, water cycle, and carbon cycle, it is critical to accurately measure snowpack. The ability to measure snow cover fraction and albedo from space is a proven technology and has yielded tremendous advances into our understanding of the Earth system. Indeed, the most recent Earth Science Decadal Survey (ESDS) recommended the Surface Biology and Geology (SBG) as an imperative “Designated measurement”. SBG would include a visible through shortwave infrared imaging spectrometer and spectral thermal imager for understanding snow spectral albedo, the controls on snow albedo, and snow surface temperature. However, the great diversity in snowpack characteristics (e.g., depth, liquid water content) and cold regions environments (e.g., forests, complex terrain, barren tundra) pose a great challenge for measuring global snow water equivalent (SWE). The international snow remote sensing community has been active in responding to this challenge, and has developed a number of snow remote sensing technologies. For example, the NASA Cold Lands Processes Experiments significantly advanced microwave radar technology to estimate SWE. While airborne SWE and albedo measurement has been successfully applied at the watershed and regional scale, several spaceborne SWE missions have been proposed but ultimately were not been selected; additional missions to map SWE are currently in development globally. There are several new approaches that have been proposed, e.g., using L-band measurements from UAVSAR to measure SWE. The ESDS has recommended a Snow Depth/SWE concept based on radar, InSAR, or LiDAR as a to-be-competed Explorer measurement. Only by inter-comparing the various measurement techniques will we be able to quantify their capabilities in different environments, as well as possible multi-sensor synergies in the context of modeling and data assimilation for future global SWE mapping in an integrated Earth System framework.
To better characterize the performance of proposed sensors, and to identify optimum multi-sensor synergies and model assimilation for mapping the critical snowpack properties in future satellite missions, the SnowEx campaign was undertaken by the NASA Terrestrial Hydrology Program (THP). The project aims to quantify and compare capabilities and limitations of traditional and newer snow estimation techniques across a range of environmental conditions, with an emphasis on articulating satellite remote sensing strategies and requirements. The newer technologies hold great promise but need to be tested more extensively with airborne observations alongside existing technologies for a comparison of their relative accuracy and global applicability. Advances in snow modeling and data assimilation must be further leveraged to integrate measurements from multiple sensors to estimate SWE. Remote sensing of components related to the snow surface energy balance - including albedo and surface temperature - are critical for understanding energy cycles and changes in climate and are also a significant opportunity for understanding changes in SWE as well as improved SWE estimation through assimilation.
SnowEx was initiated in the 2016-2017 winter with a field campaign in Colorado that was designed to evaluate the sensitivity of different snow remote sensing techniques to increasing forest density at Grand Mesa, a large mesa in western Colorado in the United States. In the remaining years, SnowEx campaigns will focus on the efficacy of SWE measurement and modeling techniques in up to four regions of interest:
• Mountain ranges and temperate forests of the western United States
• Boreal forests (taiga) and arctic tundra of North America
• Cold prairies in interior regions of North America, and/or
• A maritime gradient spanning the Pacific Northwest region of the United States
The process for recommending these focal areas is documented further in the SnowEx Science Plan.