Performance Analysis of Planetary Boundary Layer Parameterization Schemes in WRF Modeling Set Up over Southern Italy

Bhishma Tyagi,Pantaleone Carlucci,Daniele Gasbarra,Vincenzo Magliulo,Alessio D’Allura,Giuseppe Calori,Angelo Riccio,Beniamino Gioli,Alessandro Zaldei,Piero Toscano,Sandro Finardi

doi:10.3390/atmos9070272

Abstract

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 a Weather 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 the MYNN2 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 the morning 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.

Highlights

Regional scale meteorological modeling is important to improve our knowledge of the processes controlling atmospheric circulation, as well as actual air pollution levels and their impact on human health and ecosystems [1]
The model based on Reynolds-averaged Navier–Stokes (RANS) equations provide results that are representative of the space and time averages of the meteorological variables
The effective space and time resolution of Weather Research and Forecasting (WRF) depends on the computational domain grid spacing and the numerical advection scheme [61], and it is the usual practice to compare the results of model simulation with grid spacing of a few kilometers with the observed variables’ time averages of the order of 1 h, implicitly assuming that the averaging time window is large enough to sample the whole boundary layer turbulence spectrum

Summary

Introduction

Regional scale meteorological modeling is important to improve our knowledge of the processes controlling atmospheric circulation, as well as actual air pollution levels and their impact on human health and ecosystems [1]. Available meteorological and air quality observations are generally insufficient to properly identify the atmospheric phenomena driving severe air pollution conditions, Atmosphere 2018, 9, 272; doi:10.3390/atmos9070272 www.mdpi.com/journal/atmosphere. Air quality studies are usually supported by chemistry and transport models, which use emission inventories over the region of interest, boundary conditions from a global forecast model, and meteorological fields from a numerical weather prediction (NWP) model [2]. The performance of numerical models can be improved, among other factors, through using higher spatial and temporal grid resolutions, appropriate parameterizations, or the data assimilation of observed meteorological parameters [6,7,8]

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