MSc thesis topic: Relating Amazonian rainforest structural propertiesto clouds

Photosynthesis and evapotranspiration strongly regulate the moisture content available to clouds. To better understand and quantify the links between photosynthesis and clouds in the Amazon, it is important to investigate surface fluxes at different spatial and temporal scales. The Amazon Tall Tower Observatory offers a unique scientific platform to obtain a more detailed view on the surface-atmosphere interactions. In this project, the available tower data will be augmented by remotely sensed imagery. Multiple remotely sensed datasets are available at a daily or even more frequent temporal resolution but there is general a trade-off with the spatial resolution of the data, with spatially coarser data being available more frequently.

This project will investigate the forest height structure derived from spaceborne LiDAR (GEDI) in combination with remotely sensed land surface temperature and evapotranspiration measures. The ultimate goal is to get a better understanding of the impact of forest structure on land surface temperature and evapotranspiration in the period of August 1 – 20, 2022. Canopy structure will be identified using GEDI data for the available footprints in the vicinity of the tower. Land surface temperature metrics will be derived from both Landsat 8 and 9, and MODIS (daily, day/night). Evapotranspiration data will be derived from daily MODIS data.

Relevance to research/projects at GRS or other groups

• This project will bridge the ongoing collaboration between GRS and MAQ (Meteorology and Air Quality)

Objectives and Research questions

• Study the forest height structure for the available GEDI footprints in the vicinity of the tower.
• Study LST and ET using Landsat 8/9 and daily MODIS day/night data and relate the observations to cloud patterns and forest height structure.
• Comparison of LST and ET products with in-situ observations taken at the ATTO tower.

Requirements:

• Depending on the background of the candidate we will provide some support to meteorology: concepts, processes, and variables.
• Geo scripting
• Affinity with work with large scale remote sensing datasets

Literature and information

• Kong, Juwon, et al. Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates. Agricultural and Forest Meteorology316 (2022): 108878.
• Vilà‐Guerau de Arellano, J., Hartogensis, O., Benedict, I., De Boer, H., Bosman, P. J., Botía, S., ... & Van Heerwaarden, C. C. (2023). Advancing understanding of land–atmosphere interactions by breaking discipline and scale barriers. Annals of the New York Academy of Sciences.
• Schimel, D., Schneider, F. D., & JPL Carbon and Ecosystem Participants. (2019). Flux towers in the sky: global ecology from space. New Phytologist, 224(2), 570-584.
• Zhang, Z., Li, X., & Liu, H. (2022). Biophysical feedback of forest canopy height on land surface temperature over contiguous United States. Environmental Research Letters, 17(3), 034002.

Expected reading list before starting the thesis research

• Depending on the background of the MSC student we can recommend some literature.

Theme: Sensing & measuring