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Evaluation of Regional Air Quality Models over Sydney and Australia: Part 1—Meteorological Model Comparison

1
Department of Planning, Industry and Environment (Formerly New South Wales Office of Environment and Heritage), PO Box 29, Lidcombe, Sydney 1825, Australia
2
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong 2522, Australia
3
School of Earth Sciences, University of Melbourne, Melbourne 3010, Australia
4
Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organization (CSIRO), Aspendale 3195, Australia
5
Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA
6
Environmental Research, Australian Nuclear Science and Technology Organisation (ANSTO), Sydney 2232, Australia
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(7), 374; https://doi.org/10.3390/atmos10070374
Received: 11 June 2019 / Revised: 29 June 2019 / Accepted: 1 July 2019 / Published: 4 July 2019
(This article belongs to the Special Issue Air Quality in New South Wales, Australia)
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Abstract

The ability of meteorological models to accurately characterise regional meteorology plays a crucial role in the performance of photochemical simulations of air pollution. As part of the research funded by the Australian government’s Department of the Environment Clean Air and Urban Landscape hub, this study set out to complete an intercomparison of air quality models over the Sydney region. This intercomparison would test existing modelling capabilities, identify any problems and provide the necessary validation of models in the region. The first component of the intercomparison study was to assess the ability of the models to reproduce meteorological observations, since it is a significant driver of air quality. To evaluate the meteorological component of these air quality modelling systems, seven different simulations based on varying configurations of inputs, integrations and physical parameterizations of two meteorological models (the Weather Research and Forecasting (WRF) and Conformal Cubic Atmospheric Model (CCAM)) were examined. The modelling was conducted for three periods coinciding with comprehensive air quality measurement campaigns (the Sydney Particle Studies (SPS) 1 and 2 and the Measurement of Urban, Marine and Biogenic Air (MUMBA)). The analysis focuses on meteorological variables (temperature, mixing ratio of water, wind (via wind speed and zonal wind components), precipitation and planetary boundary layer height), that are relevant to air quality. The surface meteorology simulations were evaluated against observations from seven Bureau of Meteorology (BoM) Automatic Weather Stations through composite diurnal plots, Taylor plots and paired mean bias plots. Simulated vertical profiles of temperature, mixing ratio of water and wind (via wind speed and zonal wind components) were assessed through comparison with radiosonde data from the Sydney Airport BoM site. The statistical comparisons with observations identified systematic overestimations of wind speeds that were more pronounced overnight. The temperature was well simulated, with biases generally between ±2 °C and the largest biases seen overnight (up to 4 °C). The models tend to have a drier lower atmosphere than observed, implying that better representations of soil moisture and surface moisture fluxes would improve the subsequent air quality simulations. On average the models captured local-scale meteorological features, like the sea breeze, which is a critical feature driving ozone formation in the Sydney Basin. The overall performance and model biases were generally within the recommended benchmark values (e.g., ±1 °C mean bias in temperature, ±1 g/kg mean bias of water vapour mixing ratio and ±1.5 m s−1 mean bias of wind speed) except at either end of the scale, where the bias tends to be larger. The model biases reported here are similar to those seen in other model intercomparisons. View Full-Text
Keywords: model evaluation; meteorological modelling; air quality modelling; Clean Air and Urban Landscapes Hub; NSW Australia model evaluation; meteorological modelling; air quality modelling; Clean Air and Urban Landscapes Hub; NSW Australia
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Monk, K.; Guérette, E.-A.; Paton-Walsh, C.; Silver, J.D.; Emmerson, K.M.; Utembe, S.R.; Zhang, Y.; Griffiths, A.D.; Chang, L. .-C.; Duc, H.N.; Trieu, T.; Scorgie, Y.; Cope, M.E. Evaluation of Regional Air Quality Models over Sydney and Australia: Part 1—Meteorological Model Comparison. Atmosphere 2019, 10, 374.

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