B106-10
Understanding the role of energy fluxes in shaping the seasonal patterns of ABL heights and cloud dynamics for select AmeriFlux sites across the United States

Tuesday, 15 December 2020: 21:06
Virtual
Eric Beamesderfer1, Manuel Helbig2, Nathaniel A Brunsell3, Andrew D Richardson1 and AmeriFlux Collaborators, (1)Northern Arizona University, School of Informatics, Computing & Cyber Systems, Flagstaff, AZ, United States, (2)Dalhousie University, Department of Physics and Atmospheric Science, Halifax, NS, Canada, (3)University of Kansas, Department of Geography and Atmospheric Science, Lawrence, KS, United States
Abstract:
The exchange of energy, mass, and momentum between the land surface and atmosphere (measured by eddy covariance [EC] flux measurements) directly influences the daily and seasonal weather we experience. This relationship between the land surface (soil, vegetation, landscapes, etc.) and the lowest layer of the atmosphere (~1-3 km), known as the atmospheric boundary layer (ABL), exerts important controls on an area's water balance, energy balance, cloud formations, and land surface processes such as photosynthesis, respiration, and soil water availability (in the form of evapotranspiration). Unfortunately, few continuous ABL measurements are collected across the United States, especially in the vicinity of EC flux towers. This study aims to explore co-located EC and ABL observations across a latitudinal gradient of 5 AmeriFlux sites (30+ site years of data) spanning from the cool and wet northeast to the warm and dry southwest United States, with sites including: Howland Forest (Maine), Morgan Monroe State Forest (Indiana), Kansas Field Station (Kansas), Southern Great Plains (Oklahoma), and Kendall Grasslands (Arizona). The goal of this study is to analyze the role of seasonal surface EC fluxes (latent and sensible heat) and phenology (PhenoCam) on ABL dynamics (mixing layer and cloud heights and frequencies) at the selected flux tower sites. This study will help to improve the understanding of land-atmosphere interactions and the associated feedback by providing a unique observational dataset, which may benefit the upscaling of fluxes to regional scales and support data needed for land-atmosphere models.