A New Snow Observing Strategy in Support of Hydrological Science and Applications

This proposal aims to develop a new observing strategy (NOS) for snow that considers the most critical snow data needs along with existing and expected observations, models, and a future snow satellite mission. The Snow Observing System (SOS) will be used to estimate SWE and snow melt throughout the season, targeting observations (e.g. peak SWE and the onset of melt) with the greatest impact to hydrological metrics as they occur in different regions. Snow is a seasonally evolving process that results in a reflective, insulating cover over the Earth's land mass each year, provides water supply to billions of people and supports numerous ecosystems. Snow also contributes to short-term and long-term disasters. It is a critical storage component of the global water cycle, yet we currently do not have global snow observations that provide data needed to understand its role in hydrological regimes and respond to snow-related events. While numerous existing or expected satellite sensors are sensitive to snow and provide information on different snow properties, none provide global snow water equivalent (SWE) data, the essential information to address hydrologic science questions, at the frequency, resolution and accuracy needed. While snow contributes water resources to a large portion of the Earth's terrestrial area, its coverage and role evolves throughout the season, affecting different regions, elevations and latitudes at different times of the year. For instance, in North America, peak SWE, peak SWE uncertainty and melt onset shift from lower latitudes and elevations early in the year (Jan – Apr) to northern latitudes and elevations later (May – June), indicating that data needs may also shift throughout the year. Seasonal snow is a perfect candidate for an optimized observational strategy that leverages existing sensors and focuses future mission concepts on monitoring the most critical areas to provide cost-effective and robust information. The National Academy of Science identified snow water equivalent or snow depth as a critical observation in the 2017-2027 Decadal Survey and recommended it as a measurement priority in the Earth System Explorer (ESE) class missions. An ESE announcement of opportunity is expected within the next year (Earth Science "Earth System Explorers" AO Community Announcement NNH22ZDA002L), which could provide an opportunity to launch a SWE-focused mission. An optimized observing strategy for snow will be integral to the mission design to target the most critical data needs. Our approach will be to evaluate observations from existing missions that have previously not been combined in an optimized way; create a hypothetical experiment to determine an optimal observing strategy focused on specific hydrological events; assess the value of new potential sensors, such as from commercial smallsats to fill observing gaps and provide higher frequency observations during critical time periods. We will also evaluate the potential for focusing higher density observations in regions where concerns for flood, drought or wildfires will benefit from early warning. These dynamic observations could help rally ground, UAS or airborne observations in regions showing snow volumes outside the normal range or experiencing unexpected snowpack conditions. The expected outcome is a demonstrated plan for a new observing system that responds to the dynamic nature of seasonal terrestrial snow and focuses on regions of interest in a timely manner. This strategy will allow high-resolution observations in critical areas for improving science and application understanding, reduce the potential cost of a global snow-observing satellite mission by not observing non-snow-covered areas, and take advantage of new commercial smallsat assets which are advancing rapidly and becoming increasingly available at the frequencies of interest.

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