Publications

Observational constraints and modeling limitations have hindered comprehensive understanding and model parameterization of heterogeneity driven flow. This study introduces a framework combining satellite remote sensing and Doppler LiDAR to quantify heterogeneity-driven mesoscale flows in the atmospheric boundary layer.

Monin–Obukhov similarity theory (MOST) has long served as the basis for parameterizations of turbulence exchange between the surface and the atmospheric boundary layer in models for weather and climate prediction. Decades of research, however, have illuminated some of the limitations of MOST-based surface-layer parameterizations … in this work, we examine the performance of a new, anisotropy-generalized MOST scaling across 7 years of data at the 47 towers in the National Ecological Observation Network

In large-scale Earth system models (ESMs) used to study climate processes, surface heterogeneity that is subgrid to the larger atmospheric grid is often represented by a number of land tiles, effectively providing a higher resolution land surface to a coarser resolution overlying atmosphere. ESMs, however, average the surface fluxes before they are communicated to the atmosphere. In this study, we examine the impact of this flux averaging through 257 two-day summer WRF simulations