Land Surface Brightness Temperature Modeling Using Solar Insolation

Retrieval of land surface emissivity and temperature from microwave brightness temperature data is a complex problem. The diurnal variation of temperature due to the diurnal cycle of solar radiation and weather conditions makes this problem even more challenging. In this paper, we use solar radiation in modeling the temporal variation of the brightness temperature state of the surface. Solar insolation modeling is used to estimate the diurnal variation of land surface brightness temperature. Solar radiation and brightness temperature are linked through temperature of the surface which is derived based on the radiation balance equation. The temperature state model behaves consistent to the measured temperature data. The root-mean-square (rms) error of the model and measured temperature during 1999 is 1.47 K with a correlation of 0.98. Brightness temperature is calculated as a product of physical temperature and emissivity. This relationship is used to transform the temperature state model into the temporal model of the brightness temperature. The model is validated using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) brightness temperature observations at 10.65-GHz vertical polarization. The rms error of the modeled and measured brightness temperature during 1999 is 2.15 K with a correlation of 0.98. Physical and brightness temperature models are ordinary differential equations that are solved numerically to estimate model parameters. The model parameters are related to geophysical characteristics that modulate the temporal variation of the physical and brightness temperature. These parameters provide new insight into the thermal characteristics of the land surface. Brightness temperature model is used to retrieve emissivity from TMI measurements. Images of emissivity and other model parameters are spatially coherent and reflect ground geometrical and dielectric conditions. The results confirm that incident solar radiation is an important input in - - modeling the temporal variation in the physical temperature and brightness temperature.