Quantifying Snow–Ground Backscatter Uncertainty: A Bayesian Approach Using Multifrequency SAR and In-Situ Observations
Year: 2026
Type: article
Abstract: Accurate estimation of snowpack microwave backscatter is critical for retrieving key physical properties of snow, such as snow depth (SD) and snow water equivalent (SWE), typically modeled using radiative transfer models (RTM). Among the various sources of uncertainty in RTM simulations, snow–ground reflectivity—used as a boundary condition—plays a critical role in influencing the accuracy of simulated backscatter. This study leverages high-resolution X- and Ku-band synthetic aperture radar (SAR) backscatter aircraft measurements using SWESARR and SnowSAR from NASA’s SnowEx campaigns, co-located with in situ snow pit observations in Grand Mesa, Colorado, and uses a Bayesian MCMC parameter optimization model with RTM framework to estimate the key ground parameters such as surface roughness, moisture content, and specular-to-total reflectivity ratio (STRR) governing the estimation of the snow–ground reflectivity and quantify the uncertainties associated with them. At the X-band, increasing ground surface roughness reduced the simulated backscatter by ~1.5 dB across the tested range, increasing the STRR produced an additional ~1.0 dB decrease while the dielectric properties of the ground are highly sensitive to the moisture content of frozen soil, and increasing the moisture content even by 2% increased the backscatter by 2–3 dB. The retrieval sensitivity to the STRR is minimized in the 0.6–0.7 range and it can be fixed at 0.65 without having discernible impact. The Bayesian inversion reveals that the extreme parameter values act as diagnostic indicators of unmodeled complexity rather than retrieval failures, with representativeness error often dominating over instrument noise. The study provides a robust methodology for the estimation of the snow–ground backscatter boundary condition for forward modeling, ultimately aiding SWE and SD retrieval from active microwave observations. While this study relied on Grand Mesa, the framework developed here is general and, along with the model uncertainty, is directly transferable and broadly applicable to other snow-dominated mountain regions where active microwave observations can be used for snowpack monitoring.
Source: Remote Sensing
DOI: 10.3390/rs18040634
Authors: Ashwani Rai, Ana P. Barros
Institution: University of Illinois Urbana-Champaign
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,258
Awards: G136433309, G532424719, SATELLITE-BASED REMOTE SENSING PROVIDES THE ONLY MEANS TO MONITOR SNOW MASS OVER LARGE REMOTE REGIONS. THE MEASUREMENT CHALLENGE IS TO BRIDGE THE SCALE GAP FROM THE MICRO SCALES AT WHICH SHOW PHYSICS DETERMINES THE TRANSIENT NATURE OF SNOWPACK STRUCTURE TO THE SATELLITE OBSERVING SCALE. KEY FACTORS OF TRANSIENT SNOW STRUCTURE HETEROGENEITY ARE ENVIRONMENTAL CONDITIONS ABOVE THE SNOWPACK (PRECIPITATION INPUT AIR HUMIDITY RADIATION TEMPERATURE AND WIND) AS WELL AS SNOWPACK RADIATIVE PROPERTIES (BROADBAND ALBEDO AND FREQUENCY DEPENDENT REFLECTIVITY AND EMISSIVITY) PROFILES AND GRADIENTS OF TEMPERATURE AND HUMIDITY GRADIENTS THROUGH ACCUMULATION METAMORPHOSIS AND MELTING PHASES. ON ACCOUNT OF THE HIGH SPATIAL AND TEMPORAL VARIABILITY OF SNOW COVERED AREA SURFACE ROUGHNESS SNOW DEPTH AND SNOW MICROPHYSICS GROUND-BASED MEASUREMENTS AT THE SPATIAL AND TEMPORAL RESOLUTION REQUIRED TO OBTAIN QUALITY MEASUREMENTS OF SNOW STRATIGRAPHY INCLUDING CHANGES IN SNOW DEPTH MICROSTRUCTURE AND DENSITY (SNOW WATER EQUIVALENT) ARE ESPECIALLY CHALLENGING AND MORE SO IN REGIONS OF COMPLEX TERRAIN WHICH ARE ALSO FREQUENTLY REMOTE REGIONS OF DIFFICULT ACCESS BECAUSE OF COMPLEX TOPOGRAPHY BUT ALSO BECAUSE OF THE UNDERLYING ALTITUDINAL AND LATITUDINAL CLIMATIC GRADIENTS. TO ADDRESS THIS CHALLENGE WE PROPOSE A SUITE OF DISTRIBUTED NONINTRUSIVE GROUND OBSERVATIONS TO BE INTEGRATED WITH CLASSICAL FIELD MEASUREMENTS OF SNOW IN PREPARATION FOR THE NEXT GENERATION COLD LANDS PROCESS EXPERIMENT TO CONSTRAIN AND EVALUATE COUPLED SNOW HYDROLOGY-MICROWAVE RADIATIVE TRANSFER MODELS FOLLOWED BY SCALING ANALYSIS OF SATELLITE AND AIRBORNE MICROWAVE (ACTIVE AND PASSIVE) MEASUREMENTS AND SNOWPACK STRUCTURE. THE OBJECTIVE IS TO IDENTIFY EMERGENT BEHAVIOR AT THE SATELLITE FOOTPRINT SCALE LEADING TO A PROGNOSTIC PHYSICAL STATISTICAL MODEL THAT RELATES THE TEMPORAL EVOLUTION OF MULTI-FREQUENCY MULTI-SENSOR MULTI-SCALE MICROWAVE OBSERVATIONS AT COARSER RESOLUTION TO THE SPACE-TIME EVOLUTION OF SNOW STRUCTURE AND SWE AT HIGH-SPATIAL RESOLUTION. ULTIMATELY SUCH PARAMETERIZATION CAN BE INTEGRATED WITH EXISTING RETRIEVAL ALGORITHMS TO ESTIMATE SWE OVER LARGE REGIONS OR IN MACRO SCALE HYDROLOGY AND CLIMATE MODELS TO DESCRIBE THE SUB-GRID SCALE HETEROGENEITY OF SHOW PHYSICS.
OpenAlex ID: W7130341235