Monitoring snowpack depth is essential in many applications at regional and global scales.
Space-borne passive microwave (PMW) remote sensing observations have been widely …

Climate-influenced changes in hydrology affect water-food-energy security that may impact
up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in …

Seasonal snowpack is a key water resource and plays an important role in regional climate.
However, how seasonal snow mass is distributed over space and time is not fully …

Accurate high spatial resolution snow depth mapping in arid and semi-arid regions is of
great importance for snow disaster assessment and hydrological modeling. However, due to …

This study explores the use of a support vector machine (SVM) as the observation operator
within a passive microwave brightness temperature data assimilation framework (herein …

In this study, we investigate applying deep learning (DL) models on a regional climate
simulation produced by the Terrestrial Systems Modelling Platform (TSMP Ground to …

Snow plays a crucial role in the global water cycle, providing water to over 20% of the
world's population and serving as a vital component for flora, fauna, and climate regulation …

Satellite-derived agricultural drought indices can provide a complementary perspective of
terrestrial vegetation trends. In addition, their integration for drought assessments under …

The retrieval of continuous snow water equivalent (SWE) directly from passive microwave
observations is hampered by ambiguity, which can potentially be mitigated by incorporating …

The main objective of this article is to develop a physically constrained support vector
machine (SVM) to predict C-band backscatter over snow-covered terrain as a function of …