UFZ Helmholtz Centre for Environmental Research
About
During my time spent at UFZ in the Remote Sensing department as a research intern, I was able to utilize various satellite and reanalysis data to conduct research regarding land-atmosphere interactions.
Initially, under consideration of factors such as cloud and vegetation coverage, evapotranspiration, and climate, I conducted analysis with remote sensing data to determine correlation between air and soil with heat fluxes at Earth’s surface.
An example correlation map for air temperature extremes is provided. Here, these extremes are compared across different heat fluxes that make up net radiation at the surface.
In addition to this analysis I constructed and tuned a random forest machine learning algorithm to derive latent heat flux. This involved utilizing eddy covariance measurements of latent heat flux as a target and High-resolution land surface fluxes from satellite and reanalysis data (HOLAPS) as forcings to train and tune the ML model.