Abstract
Thermal inertia is a physical parameter that evaluates soil thermal properties with an emphasis on the stability of the temperature when the soil is affected by heating/cooling. Thermal inertia can be retrieved from a heat budget formulation as a parameter when the time series of Earth surface temperature and forcing variables, such as insolation and air temperature, are given. In this study, a two-layer, linearized heat budget model was employed for the retrieval of thermal inertia over a grassland in a semiarid region. Application of different formulations to the aerodynamic conductance with respect to atmospheric stability significantly improved the accuracy of the thermal inertia retrieval. The retrieved values of thermal inertia were well correlated with in situ surface soil moisture at multiple ground stations. The daily time series of thermal inertia–derived soil moisture qualitatively agreed well with in situ soil moisture after antecedent rainfalls, which was found after fitting the time series to an exponentially decaying function. On the contrary, AMSR2 soil moisture mostly did not agree with in situ soil moisture. The results of the estimation showed high accuracy: the root-mean-square error was 0.038 m3 m−3 compared to the in situ data and was applied to an area of 2° × 2° in which the in situ observation locations were included. The spatiotemporal distribution of surface soil moisture was mapped at a 0.03° × 0.03° spatial resolution in the study area as 10- or 11-day averages over a vegetation growth period of 2012.
Thermal Inertia Approach Using a Heat Budget Model to Estimate the Spatial Distribution of Surface Soil Moisture over a Semiarid Grassland in Central Mongolia
