Estimation of snowfall over the sea of Japan using AMSR-E passive microwave remote sensing observation

Abstract

Snowfall is an important geophysical parameter and the observation of the spatial and temporal distribution of snowfall can provide valuable information for a wide range of applications including climate change studies and atmospheric modelling. This paper investigates the feasibility to estimates the amount of solid precipitation and the cloud liquid water content over the ocean using AMSR-E passive microwave brightness temperature observations. The parameters are retrieved by minimizing the difference between the observed and modeled brightness temperature. The radiative transfer in the atmosphere is solved using the discrete ordinate method (4 streams) and the Henyey-Greenstein phase function. The scattering effect of the snow particles is calculated using Mie theory and the liquid-equivalent size of the ice particle. Except for the snowfall and the cloud liquid water content, most parameters, which influence the observation are derived from other data sources. The Newton-Raphson method is used to solve the iteration process using observed brightness temperatures at 89 GHz vertical polarization and 36.5 GHz horizontal polarization. The algorithm was applied using data from the Wakasa Bay Experiment 2003 in Japan and the results are compared to snowfall observation derived using a Z-R relationship and data from the Mikuni Doppler radar. Good agreement was achieved for different atmospheric conditions