Advancing the application of remote sensing to improve land surface modeling

Over the recent two decades, space agencies have put enormous effort into remote sensing for understanding the global water and energy cycles. Our understanding of global hydrology has advanced in this golden age of satellite hydrology. This dissertation explores the global to continental- scale applications of multiple satellite missions for Earth system models to understand land-surface processes. Data assimilation is a novel approach to integrated satellite observations and models to provide continuous and more realistic estimates. In Chapter 2, I investigate impacts of land data assimilation (DA) on runoff and river discharge. Multiple experiments with the assimilation of different combinations of remote-sensing datasets are conducted using the Community Land Model version 4 (CLM4), constrained by assimilating observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), Gravity Recovery and Climate Experiment (GRACE), and Advanced Microwave Scanning Radiometer for EOS (AMSR-E). Results show GRACE-DA dominants runoff, and snow-DA-induced runoff are pronounced in high and mid-latitude. GRACE-DA improves the spatial pattern of river discharge during summer and autumn. This study shows how data assimilation help improve discharge estimation. Satellite observations are used as benchmarks for diagnosing model performances in Chapter 3. Results show a systematic cold bias over drylands in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulation, associated with overestimated evapotranspiration cooling. The aridity-dependent biases in skin temperatures show modeled deficiencies in land-atmosphere interactions. Results suggest a higher priority to develop and improve related processes to eliminate temperature biases in state-of-art climate models in dry conditions. Predicting droughts is a great challenge of climate models. In Chapter 4, we investigate the physical process that controls water availability during drought to understand the mechanisms causing the disparities. Results suggest that using different physical parameterizations, such as considering vegetation response, affect water availability but also skin temperature through the modulation of evapotranspiration. The studies presented in this dissertation demonstrate the applications of satellite information in the field of large-scale climate modeling as data assimilation, benchmarking, and data inputs. Emerging challenges are shown and shed some light on the future research direction of global hydrology.