Exploring the Spatiotemporal Coverage of Terrestrial Snow Mass Using a Suite of Satellite Constellation Configurations

Lizhao Wang,Barton A Forman,Edward Kim

doi:10.3390/rs14030633

Abstract

Terrestrial snow is a vital freshwater resource for more than 1 billion people. Remotely-sensed snow observations can be used to retrieve snow mass or integrated into a snow model estimate; however, optimally leveraging remote sensing observations of snow is challenging. One reason is that no single sensor can accurately measure all types of snow because each type of sensor has its own unique limitations. Another reason is that remote sensing data is inherently discontinuous across time and space, and that the revisit cycle of remote sensing observations may not meet the requirements of a given snow applications. In order to quantify the feasible availability of remotely-sensed observations across space and time, this study simulates the sensor coverage for a suite of hypothetical snow sensors as a function of different orbital configurations and sensor properties. The information gleaned from this analysis coupled with a dynamic snow binary map is used to evaluate the efficiency of a single sensor (or constellation) to observe terrestrial snow on a global scale. The results show the efficacy achievable by different sensors over different snow types. The combination of different orbital and sensor configurations is explored to requirements of remote sensing missions that have 1-day, 3-day, or 30-day repeat intervals. The simulation results suggest that 1100 km, 550 km, and 200 km are the minimum required swath width for a polar-orbiting sensor to meet snow-related applications demanding a 1-day, 3-day, and 30-day repeat cycles, respectively. The results of this paper provide valuable input for the planning of a future global snow mission.

Highlights

Accepted: 24 January 2022Snow is an important component of global freshwater storage
This study provides a slew of sensor coverage simulations with various sensor swath widths and orbital configurations
This study explores a suite of existing and hypothetical sensors in the viewing of snow-covered terrain as a function of sensor orbital configuration and sensor efficacy

Summary

Introduction

Snow is an important component of global freshwater storage. It provides freshwater supply for more than 1 billion people [1,2,3]. Snow-covered terrain serves as a natural reservoir that slowly attenuates freshwater runoff during the snow ablation season [4]. Snow albedo plays an important role in energy balance and climate change. Atmospheric warming could reduce the seasonal snow cover and, increase shortwave absorption at the land surface, which could introduce a positive feedback [5]. Snow storage estimation is increasingly important as the virtual reservoir of snow is threatened by global warming and climate change [6,7,8]. The vulnerability of snow storage has attracted considerable interest from the hydrologic community to monitor the equivalent amount of liquid water contained within the snowpack (a.k.a snow water equivalent or SWE) so that this vital resource may be better managed and preserved

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Results

Discussion

Conclusion