Impacts of realistic land cover and crop phenology on simulated high-resolution surface flux heterogeneity in the Southern Great Plains
Authors
Justin Bagley — Lawrence Berkeley National Laboratory
Lara Kueppers — Lawrence Berkeley National Laboratory
Ian N. Williams — Lawrence Berkeley National Laboratory
Yaqiong Lu — National Center for Atmospheric Research
Sebastien Christophe Biraud — Lawrence Berkeley National Laboratory
Jovan Tadic — Lawrence Berkeley National Laboratory
Margaret S. Torn — Lawrence Berkeley National Laboratory
Category
Boundary layer structure, including land-atmosphere interactions and turbulence
Description
Idealized experiments have shown that different patterns of surface water and energy fluxes can influence the location and extent of cloud formation and precipitation in the Southern Great Plains (SGP). However, this influence depends on the scale of surface flux spatial heterogeneity. In the SGP, seasonal changes in surface fluxes are closely correlated with differences in land cover, with winter wheat and grassland/pasture being the dominant land cover types in the region. Grassland/pasture actively grows from March-October, while winter wheat is planted in early fall and harvested in late spring-early summer. This early harvest abruptly reduces latent and increases sensible heat fluxes from fields where winter wheat is planted, whereas latent heat flux continues to be high through the summer. In the SGP, winter wheat fields are interspersed with grassland/pasture, resulting in fine-scale heterogeneity. As a result, we expect the fine-scale surface flux heterogeneity to increase following harvest. In this study, we test how winter wheat’s harvest influences surface flux heterogeneity using high-resolution land surface simulations with realistic winter wheat growth and harvest and grassland/pasture growth. We assess the accuracy of the simulated fluxes and meteorological forcing data using multiple ARM surface energy flux observation towers near the Central Facility of the ARM-SGP site. Additionally, we develop statistics that evaluate the spatial variability and coherence of land cover patterns across our domain, and determine how land cover variability influences surface sensible and latent heat flux spatial heterogeneity before and after winter wheat harvest.
