Assessing the effect of sub-grid cell lakes on late winter passive microwave snow water equivalent estimations on the North Slope of Alaska

Abstract

This research investigates the effect of lakes on late winter Snow Water Equivalent (SWE) and snow depth estimations on the North Slope of Alaska. Time-invariant and temporal sub-grid variability is assessed through the comparison of brightness temperature evolutions for three grid cells with varying lake fraction. Two new stepwise regression-derived algorithms to estimate SWE and snow depth using brightness temperatures and lake fractions, and two new algorithms to estimate lake fraction using brightness temperatures from SSM/I and AMSR-E are presented. Evaluation of various goodness-of-fit metrics display strengths and weaknesses of each algorithm. The methods employed in this study result in improved estimation with R² values of 0.202 for SWE and 0.292 for snow depth. The two lake fraction estimation algorithms resulted in R² values of 0.509 and 0.738 for SSM/I and AMSR-E, respectively. This study shows that spectral gradient methods utilizing the 19-37 GHz channel difference are not suitable for Alaska North Slope. Lakes were determined to have a strong effect on SWE and snow depth estimation. Inclusion of local lake fraction yielded improvements in performance.