Assessment of Snow Grain-Size Model and Stratigraphy Representation Impacts on Snow Radiance Assimilation: Forward Modeling Evaluation

Two sets of experiments were performed to identify, respectively, the impacts of using different grain size models and simplified representations of snowpack stratigraphy on the predicted grain size evolution and the resulting radiance predictions. Three different grain size models were examined with the grain size prediction used as inputs to the Microwave Emission Model of Layered Snowpacks (MEMLS) model for predicting radiobrightness (at different frequencies) from the snowpack. The varying mechanisms and treatment of grain size growth lead to differences between the three models. Despite the differences, when using best-fit relationships between grain size and the exponential correlation length parameter needed by MEMLS, the predicted brightness temperatures are similar. For all three models, it was found that a proportional model between grain size and correlation length outperformed a more physically based model and that the regression coefficients differed from those in previous studies. The predicted V-pol brightness temperature measurements from the three grain size models showed good agreement with each other, with inter-model differences on the order of ~ 5 K. At H-pol the biases significantly increase, which is most likely due to errors in predicted density and grain size in melt-freeze layers. In the experiments aimed at assessing the impact of stratigraphy on predicted radiances, it was found that there were limited additional errors introduced in using a pre-specified one-, three-, or five-layer scheme at 18.7 and 36.5 GHz (V-pol), while sizeable errors were introduced at 89 GHz (V-pol). The additional errors at H-pol were relatively small, yet the overall errors were still larger than V-pol.