Inferring on-glacier meteorology from physical modeling and remote sensing

Abstract. Local meteorology is crucial to understanding the response of mountain glaciers to climate change, yet it remains one of the largest sources of uncertainty in glacier modeling due to limited observations and complex glacier–atmosphere interactions. Recent advances in high-resolution, globally available remote sensing observations provide new opportunities to exploit observed glacier changes in order to infer high-mountain meteorology from climate reanalysis data. Here, we present a Bayesian framework combining physical energy and glacier mass balance modeling with remote sensing data to infer spatial bias corrections for on-glacier air temperature and precipitation. Our method performs a spatially-distributed inference using a physically-based land-surface model forced with statistically downscaled ERA5-Land reanalysis and an ensemble of bias-correction factors, with satellite-derived glacier surface albedo and surface mass balance as targets. The method is tested and evaluated at four benchmark glaciers in the European Alps and High Mountain Asia, with available independent in-situ observations. Results demonstrate that 1) Leveraging physical modeling with quantitative and multitemporal albedo observations can substantially reduce parameter equifinality in the inferred meteorological bias corrections; 2) Spatially-variable bias corrections improve the consistency between the model and the distributed satellite observations; 3) Compared to statistical downscaling, multi-year average air temperature and precipitation inferred with our framework show improved agreement with nearby station observations and more realistic spatial patterns over glaciers; 4) Our framework provides promising annual and seasonal mass balance with RMSEs relative to in-situ measurements of <1.5 m w.e. and <1 m w.e. respectively, corresponding to improvements of 40-50% and 20-60% compared to without inference. These results make this framework a promising avenue to derive spatial patterns of air temperature and precipitation as well as temporally-resolved glacier mass balance at the regional scale.