High-resolution spatial and temporal measurements in the surface layer (Department of Energy Early Career)
We are using high resolution spatial and temporal measurements of turbulence using Distributed Temperature Sensing (DTS). Some of the questions we have answered are: is Taylor’s hypothesis valid in the atmospheric boundary layer or does it need to be corrected.
We are using remote solar induced fluorescence (SIF) to retrieve surface carbon and water fluxes.
Machine learning is used instead of radiative transfer model inversion to retrieve soil moisture for data assimilation into land-surface models.
We are using remotely sensed solar induced fluorescence (SIF) as a proxy for photosynthesis to investigate the coupling between the biosphere and the atmosphere in observations compared to models.
Using high-resolution turbulence models combined with observations we are reinvestigating surface layer turbulent transport, with a focus on the role of coherent structures.
We are using cloud resolving models and large eddy simulations to investigate the causes of the transition between shallow and deep convection.