Meteorological Modeling Using the WRF-ARW Model for Grand Bay Intensive Studies of Atmospheric Mercury

Abstract

Measurements at the Grand Bay National Estuarine Research Reserve support a range of research activities aimed at improving the understanding of the atmospheric fate and transport of mercury. Routine monitoring was enhanced by two intensive measurement periods conducted at the site in summer 2010 and spring 2011. Detailed meteorological data are required to properly represent the weather conditions, to determine the transport and dispersion of plumes and to understand the wet and dry deposition of mercury. To describe the mesoscale features that might influence future plume calculations for mercury episodes during the Grand Bay Intensive campaigns, fine-resolution meteorological simulations using the Weather Research and Forecasting (WRF) model were conducted with various initialization and nudging configurations. The WRF simulations with nudging generated reasonable results in comparison with conventional observations in the region and measurements obtained at the Grand Bay site, including surface and sounding data. The grid nudging, together with observational nudging, had a positive effect on wind prediction. However, the nudging of mass fields (temperature and moisture) led to overestimates of precipitation, which may introduce significant inaccuracies if the data were to be used for subsequent atmospheric mercury modeling. The regional flow prediction was also influenced by the reanalysis data used to initialize the WRF simulations. Even with observational Atmosphere 2015, 6 210 nudging, the summer case simulation results in the fine resolution domain inherited features of the reanalysis data, resulting in different regional wind patterns. By contrast, the spring intensive period showed less influence from the reanalysis data.

Mercury Speciation at a Coastal Site in the Northern Gulf of Mexico: Results from the Grand Bay Intensive Studies in Summer 2010 and Spring 2011

“…The back trajectories were simulated using the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT, v4.9) [42] and high resolution meteorological data simulated using the WRF-ARW model (Version 3.2, [43]), with a horizontal resolution of 4 km and a time resolution of 3 h. Trajectories were initialized from the Grand Bay surface at the middle point of the mixing layer for the hours when the high and low GOM were observed.…”

Performance Assessment of Dynamic Downscaling of WRF to Simulate Convective Conditions during Sagebrush Phase 1 Tracer Experiments

“…The initial and boundary conditions for the WRF model can be improved by subjecting the initial datasets to objective analysis process [21]. Several studies [22][23][24][25][26][27][28] have used different configurations for nudging at various levels and show that nudging has improved the model performance considerably. Lo et al [22] has observed that nudging improves the generation of realistic regional-scale patterns by the model.…”

“…Otte [23], Ngan et al [24], Gilliam et al [25] and Rogers et al [26] have observed the improvement in Air Quality predictions when the background meteorological fields were generated by nudging the available observations. Ngan et al [27] and Li et al [28] have observed that performing nudging even when using re-analyses datasets significantly improved the wind direction predictions that are crucial for atmospheric transport and dispersion. Another challenge of running the LES for realistic ABL is the lack of observations to validate the model performance in regards of mixing and stability parameters.…”

Use of Gold Nanoparticles as Substrate for Diffusive Monitoring of Gaseous Mercury

“…The atmosphere is the most significant means for the diffusion of gaseous mercury, therefore monitoring atmospheric concentrations is important to understand its impact on the environment and its pollutions cycles [13,14].…”