Evaluating an Atmospheric Dynamic Downscaling Approach from Mesoscale to the Neighborhood Scale Using Large-Eddy Simulations

Understanding and modeling conditions at the neighborhood scale is essential for addressing weather and climate impacts on urban communities. Mesoscale weather models provide information at horizontal resolutions of a few kilometers. Such resolutions are still too coarse to represent environmental conditions at neighborhood scales of tens of meters or smaller experienced by individual residents. On the other hand, microscale urban simulations are often limited by stationary boundary conditions from mesoscale weather models and relatively small spatial extents. We evaluate a dynamic downscaling approach that bridges the gap between mesoscale and neighborhood scales using multi-nested WRF-LES model simulations. Our simulations implement recently developed or updated meter-resolution static (land cover, soil, building, topographic, etc.) data to represent the unique urban environments within Baltimore, MD. We then assess model performance using remote sensing, surface weather, surface flux, soil, biophysical, and boundary layer profile observations affiliated with the Baltimore Social-Environmental Collaborative (BSEC) and Coastal Urban-Rural Atmospheric Gradient Experiment (CoURAGE), paying particular attention to surface layer turbulence profiles. We will share lessons learned through our model development and validation efforts, especially the impacts of the description of the complex urban land surface on atmospheric turbulence and neighborhood-level climate conditions. We endeavor to contribute to the ongoing effort to improve urban modeling across scales.