Abstract:
Since the year 2000, CSIRO’s The Air Pollution Model (TAPM) has been used to generate prognostic meteorological data as input to air dispersion models. However, TAPM has several shortcomings when compared to observational data, such as underpredicting calm conditions, which are associated with poorer pollutant dispersion from ground level sources. As a result, while employing TAPM produced prognostic data, it is critical to assimilate weather station observational data for dispersion modelling.
The Weather Research and Forecasting (WRF) model has grown in prominence in recent years for providing useful predictive data.
This paper presents prognostic modelling method and results using both the TAPM and the WRF models for the northern and inner suburbs of Brisbane, Queensland. Statistical comparisons of wind roses from model produced data and measured data from neighbouring weather stations are presented to illustrate similarities and differences of these two models with measured data.
Authors: S M Ashrafur Rahman, Andrew P Martin, Samuel Wong, GM Hasan Shahariar
Theme: Air quality dispersion modelling and assessment
Keywords: TAPM, WRF, prognostic, dispersion
Award nomination: Emerging Air Quality Professional Award
Presented at: Clean Air Society of Australia and New Zealand (CASANZ)’s International Clean Air and Environment Conference, September 2022
