A comprehensive assessment of land surface - atmosphere interactions in a WRF/Urban modeling system for Indianapolis, IN

Abstract:

The random and systematic errors of mesoscale atmospheric models are important to quantify due to the growing use of these models for atmospheric transport applications, such as atmospheric inversions. The main goal of the Indianapolis Flux (INFLUX) experiment is to estimate greenhouse gas (GHG) emissions from Indianapolis using high-resolution atmospheric inversions, which require the optimization and quantification of atmospheric transport errors. This study seeks to quantify the accuracy of the parameterization schemes used to represent boundary layer processes for simulations run for Indianapolis. INFLUX presents a unique opportunity to conduct an extensive observation-to-model comparison in order to assess model errors for latent heat and sensible heat fluxes, air temperature near the surface and in the atmospheric boundary layer (ABL), wind speed and direction, and ABL depth.

The mesoscale meteorological model used in this study was the Weather Research and Forecasting (WRF) model. In order to test the sensitivity of meteorological simulations to different model packages, an ensemble of runs was created by varying ABL schemes, urban canopy models, and an improved urban land cover definition algorithm, which was created in order to reduce an inherent model overestimation of urban land cover. Nine different model configurations were tested and the meteorological errors were assessed for a period in winter (February 15, 2013 - March 20, 2013) and a period in summer (June 15, 2013 - July 20, 2013). There was not one model configuration that consistently outperformed all other configurations; however, the model runs that used the Bougeault & Lacarrere ABL scheme coupled with the multi-layer urban canopy model and the improved urban land cover algorithm was the model configuration that most consistently had the least amount of errors for our experiment setup.