Sihui Wen

As a PhD student, Sihui joined the department in 2019 after studying Applied Remote Sensing and GIS. 

Thesis title: Understanding Controls on Dust Emission in the Gonghe Basin. 

Dust is a significant part of the Earth's climate system. However, inherent seasonal and diurnal variability in dust emission from source regions along with apparent spatial heterogeneity with dust sources are both poorly constrained in global and mesoscale models due to inexact source allocation and quantification. Observations of dust source regions at the sub-basin scale, utilizing high-temporal/spatial resolution remote sensing data have been successful in deriving dust source and activation frequency data, but few studies exist globally at this scale. China contains some of the largest dust sources in the northern hemisphere, and has a long recorded history of dust emission. However, our understanding of processes occurring in these source regions remains incomplete. My PhD project aims to use synergistic remote sensing and climate data sets to determine the factors controlling dust emission within the Gonghe basin at the sub-basin scale. To achieve this, we use an integrated Remote Sensing (RS) data set to study dust emission. Firstly, we characterise the seasonal dust variability in Gonghe Basin, and climate data is used to quantify factors that control the nature and magnitude of dust emissions, improving the understanding and quantification of the complex spatial and temporal relationships among dust emission factors and the broader regional climate and human impacts. Then, we utilize a range of high spatial /temporal resolution RS data from PlanetScope, Sentinel-2, MODIS, and Himawari-8. to track and locate dust plumes, identify key geomorphological units responsible for dust emission, and determine dust emission mechanism associated with each event. The 10 case study provides a basis for long-term monitoring of dust emission from this basin using a combination of RS and field data. These data will be coupled with regional and basin-scale climate observations (wind speed, temperature, and vegetation) to provide a robust basis for characterizing dust emission controls at multiple scales.

Supervisor: Robert Bryant and Mark Bateman.