Estimating atmospheric humidity using MODIS cloud-free data in a temperate humid region

Air relative humidity is an important variable that influences the dryness of dead fuels directly and live fuels indirectly. Many empirical and physical models have been used to estimate air relative humidity based on in-situ observing stations. However, these stations do not provide continuous measurements of relative humidity at large spatial scale. Alternatively, remote sensing provides data that can be used to bridge the spatial and temporal gaps left by the observing networks. The objective of the present study is to provide high-resolution air relative humidity by downscaling the column water vapor of Moderate Resolution Imaging Spectroradiometer (MODIS). This was achieved via an empirical relationship between digital elevation model and water vapor. We tested this model in a temperate humid region i.e. northeast of Iran. The root mean square error of the estimated air relative humidity is 4.8 percent and the mean absolute percentage error is 7 percent. It is proven in this study that a simple and feasible model can compute high-resolution air relative humidity using remote sensing data in a temperate humid region.