Simulating the Influence of Temperature on Microwave Transmissivity of Trees during Winter Observed by Spaceborne Microwave Radiometery

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Abstract

Forest transmissivity is a key parameter for understanding spaceborne and airborne observations of the Earth's land surface because not only does it influences the proportion of subcanopy upwelling microwave emission penetrating through the forest canopy, it also controls the forest thermal emission. In frozen winter conditions, our previous study has indicated that observed microwave transmissivity of trees is also strongly influenced by temperature. This follow-on study uses ground-based radiometer observations, advanced microwave scanning radiometer 2 (AMSR2) observations, and model simulation to evaluate how this temperature-transmissivity relationship affects spaceborne passive microwave (PM) snow observations. A model is developed to simulate the relationship between tree transmissivity and air temperature. The R2 of the model is 0.85 (0.81) with a root mean square error (RMSE) of 0.03 (0.03) at the 18.7 (36.5) GHz channels, respectively. We find that this temperature-transmissivity relationship has a significant influence on the Tb of the tree, which influences both ground-based radiometer and spaceborne AMSR2 observations. The influence of the temperature-transmissivity relationship on upwelling ground emission is frequency dependent, demonstrating that the findings have implications for frequency difference based approaches for PM snow depth and snow water equivalent retrievals which observe snow-covered landscapes, including boreal forests, at air temperatures below freezing. This effect should therefore be accounted for in frequency difference or ratio approaches of snow accumulation retrievals.

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Li, Q., Kelly, R., Lemmetyinen, J., & Pan, J. (2020). Simulating the Influence of Temperature on Microwave Transmissivity of Trees during Winter Observed by Spaceborne Microwave Radiometery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4816–4824. https://doi.org/10.1109/JSTARS.2020.3017618

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