I am a professor in the Department of Atmospheric Sciences at National Taiwan University, Taiwan.

Dr. Lo’s research has concentrated on understanding linkages and feedbacks between the land and the climates, focusing specifically on how land hydrological processes affect the local/regional/global climate and exploring how anthropogenic forcings (such as irrigation, deforestation, CO2 concentrations, etc.) impact the hydrological cycle across various spatiotemporal scales by using satellite datasets, in-situ observations, reanalysis datasets, and climate models.

Research Experience:

A critical issue in hydro-climatology is quantifying the complex feedback between soil moisture and precipitation. Dr. Lo characterizes the spatial distribution of precipitation in relation to soil wetness and mesoscale soil moisture heterogeneity, which enhances our understanding of soil moisture–precipitation spatial coupling. It also highlights the importance of land surface hydrological processes in the climate system, with implications for precipitation changes during the dry regions that are not accurately observed in most current climate models. Furthermore, Dr. Lo applies this concept to explore the anthropogenic forcings’ fingerprint on the hydrological cycle. He studies the impact of the Maritime Continent’s land-use changes (deforestation) on the atmospheric convection and larger-scale climate, in which the deforestation in the Maritime Continent regions can increase the low-level water vapor convergences from the surrounding ocean that may destabilize the atmosphere, leading to potentially higher precipitation rates. These findings are different from what we thought previously about drying effects from land-use changes, which indicates the importance of regional dependence on the impact of land hydrological processes. The results also reveal possible reasons contributing to the disagreement among precipitation responses in current model simulations, providing clues to improve the climate models. Dr. Lo also uses model simulations and satellite datasets to evaluate and constrain the climate model’s land water storage simulations and rainfall anomalies, providing a comprehensive assessment of the reliability of the simulated land water storage that can be used to guide future water resource assessment.