Performance analysis of planetary boundary layer parameterization schemes in WRF modeling set up over Southern Italy

Predictions of boundary layer meteorological parameters with accuracy are essential for achieving good weather and air quality regional forecast. In the present work, we have analyzed seven planetary boundary layer (PBL) parameterization schemes in aWeather Research and Forecasting (WRF) model over the Naples-Caserta region of Southern Italy. WRF model simulations were performed with 1-km horizontal resolution, and the results were compared against data collected by the small aircraft Sky Arrow Environmental Research Aircraft (ERA) during 7-9 October 2014. The selected PBL schemes include three first-order closure PBL schemes (ACM2, MRF, YSU) and four turbulent kinetic energy (TKE) closure schemes (MYJ, UW, MYNN2, and BouLac). A performance analysis of these PBL schemes has been investigated by validating them with aircraft measurements of meteorological parameters profiles (air temperature, specific humidity, wind speed, wind direction) and PBL height to assess their efficiency in terms of the reproduction of observed weather conditions. Results suggested that the TKE closure schemes perform better than first-order closure schemes, and theMYNN2 closure scheme is close to observed values most of the time. It is observed that the inland locations are better simulated than sea locations, and themorning periods are better simulated than those in the afternoon. The results are emphasizing that meteorology-induced variability is larger than the variability in PBL schemes

Meteorological and air quality forecasting using the WRF-STEM model during the 2008 ARCTAS field campaign

In this study, the University of Iowa’s Chemical Weather Forecasting System comprising meteorological predictions using the WRF model, and off-line chemical weather predictions using tracer and full chemistry versions of the STEM model, designed to support the flight planning during the ARCTAS 2008 mission is described and evaluated. The system includes tracers representing biomass burning and anthropogenic emissions from different geographical emissions source regions, as well as air mass age indicators. We demonstrate how this forecasting system was used in flight planning and in the interpretation of the experimental data obtained through the case study of the summer mission ARCTAS DC-8 flight executed on July 9 2008 that sampled near the North Pole. The comparison of predicted meteorological variables including temperature, pressure, wind speed and wind direction against the flight observations shows that the WRF model is able to correctly describe the synoptic circulation and cloud coverage in the Arctic region The absolute values of predicted CO match the measured CO closely suggesting that the STEM model is able to capture the variability in observations within the Arctic region. The time–altitude cross sections of source region tagged CO tracers along the flight track helped in identifying biomass burning (from North Asia) and anthropogenic (largely China) as major sources contributing to the observed CO along this flight. The difference between forecast and post analysis biomass burning emissions can lead to significant changes (∼10–50%) in primary CO predictions reflecting the large uncertainty associated with biomass burning estimates and the need to reduce this uncertainty for effective flight planning