Precipitation regime classification based on cloud-top temperature time series for spatially-varied parameterization of precipitation models

Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches...

Improving soil moisture and surface turbulent heat flux estimates by assimilation of SMAP brightness temperatures or soil moisture retrievals and GOES land surface temperature retrievals

Surface heat fluxes are vital to hydrological and environmental studies, but mapping them accurately over a large area remains a problem. In this study, brightness temperature (TB) observations or soil moisture retrievals from the NASA Soil Moisture Active Passive (SMAP) mission and land surface temperature (LST) product from the...

Estimating Surface Heat Fluxes Using Temperature and Wetness Information: A Particle Data Assimilation Framework

Surface heat fluxes (latent and sensible heat over the land surface) play a key role in the land-atmosphere interaction, and their spatial pattern as well as temporal evolution are vital to the terrestrial water cycle and surface energy balance. Ideally, we want to have accurate estimates of spatially distributed and temporally continuous fluxes...

Impact of soil moisture data resolution on soil moisture and surface heat flux estimates through data assimilation: A case study in the Southern Great Plains

The spatial heterogeneity and temporal variation of soil moisture and surface heat fluxes are key to many geophysical and environmental studies. It has been demonstrated that they can be mapped by assimilating soil thermal and wetness information into surface energy balance models. The aim of this work is to determine whether enhancing the...