Evaluating transport in the WRF model along the California coast
- 1Scripps Institution of Oceanography, UC San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0244, USA
- 2Atmospheric, Earth, and Energy Division; Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA94550, USA
Abstract. This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbons measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF) model at these sites is crucial for inverse modeling. The performance of the transport model has been investigated by comparing the wind direction and speed and temperature at four locations using aircraft weather reports as well at all METAR weather stations in our domain for hourly variations. Different planetary boundary layer (PBL) schemes, horizontal resolutions (achieved through nesting) and two meteorological datasets have been tested. Finally, simulated concentration of an inert tracer has been briefly investigated. All the PBL schemes present similar results that generally agree with observations, except in summer when the model sea breeze is too strong. At the coarse 12 km resolution, using ERA-interim (ECMWF Re-Analysis) as initial and boundary conditions leads to improvements compared to using the North American Model (NAM) dataset. Adding higher resolution nests also improves the match with the observations. However, no further improvement is observed from increasing the nest resolution from 4 km to 0.8 km. Once optimized, the model is able to reproduce tracer measurements during typical winter California large-scale events (Santa Ana). Furthermore, with the WRF/CHEM chemistry module and the European Database for Global Atmospheric Research (EDGAR) version 4.1 emissions for HFC-134a, we find that using a simple emission scaling factor is not sufficient to infer emissions, which highlights the need for more complex inversions.