Internship – Exploring the drivers of variation of evapotranspiration in the Southeastern U.S (BNF-related)


The ecosystems and landscapes across the Southeastern United States are recognized as a global biodiversity hotspot, spanning a broad climatic regime and with a range of topographic complexity that contain critical plant and animal habitats. The forests in this region also provide important regional and global ecosystem services including recreation opportunities, evaporative cooling, and carbon sequestration. At the same time, climate change and human activities are threatening the ongoing maintenance of this biodiversity and forest ecosystem services. Increasing frequency of severe weather, heat waves (extent and duration), and changing precipitation along with changes in land use practices are putting new pressures on natural and managed ecosystems and their resources which could significantly impact the regional water cycle and land-atmosphere interactions (LAI).

In this project, student(s) will utilize surface measurement networks and multi-scale remote sensing observations together with reanalysis meteorological data to evaluate spatio-temporal drivers of surface energy balance, vegetation photosynthetic function and evapotranspiration across select regions of the Southeastern U.S. and in response to seasonal ambient environmental conditions. The student(s) will specifically utilize remotely sensed land-surface temperature (LST), evapotranspiration (ET), leaf area index, and gross primary productivity (GPP) products (as well as other ad hoc data products) and connect trends in space and time with landcover information, surface measurements/mesonets, reanalysis data and estimates of root-zone soil moisture from meteorological satellites. Using a time-series analyses, statistical correlation and/or random forest/ machine learning approached, the student(s) will investigate connections across data and scales (space and time) to identify primary drivers of variation in carbon, water and energy cycling. The resulting analysis will provide key insights into drivers of variation in surface fluxes across the Southeastern U.S. and can provide valuable information for larger, synoptic scale analyses of surface-atmosphere couplings, including the influences on the development of clouds and atmospheric humidity.