Estimating land surface radiation balance using MODIS in northeastern China

Net radiation ( R n ) is the balance between the incoming and outgoing radiation fluxes of longwave and shortwave radiations. As an essential parameter for surface energy budgets, R n has been widely applied to weather prediction, agriculture evaluation, and regional water resource management. However, the traditional methods for estimating the net radiation are inadequate at the local to regional scales because of their spatial discontinuity and the uneven distribution of radiation sites. With high temporal and spatial resolutions, moderate resolution imaging spectroradiometer data provide numerous terrestrial and atmosphere products, which can help to estimate the shortwave and longwave radiations with limited measured meteorological data. Although many studies have calculated the radiation budget, most of them were applied in North America, where extensive ground validation data are available. In northeastern China, research on the radiation budget was rare, and ground validation data were difficult to acquire, which made our study meaningful and significant. In our work, we have experimented with different parameterization schemes of the components of the radiation budget in our study area and chose the most suitable one to estimate the instantaneous net radiation flux and its components for the study area. The results showed that the RMSE of the downwelling shortwave radiation flux, downwelling longwave radiation flux, upwelling longwave radiation flux, and instantaneous R n were 31.5, 22.36, 20.61, and 34.32 W/m 2 , respectively. The sinusoidal model of the diurnal cycle and instantaneous R n were used to calculate the daily average R n , and the resulting RMSE was 47.67 W/m 2 . Finally, the variation of the monthly average R n of northeastern China in 2011 was analyzed, and the result showed that the temporal and spatial distributions of the monthly average net radiation might be closely related to the land cover types, specifically the seasonal snow cover changes.