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Presented at: European Geoscience General Assembly Vienna, Austria - April, 2011 Authors:

Coupled NMM-CALMET Meteorology Development for the CALPUFF Air Dispersion Modelling in Complex Terrain and Shoreline Settings. Presented at: European Geoscience General Assembly Vienna, Austria - April, 2011 Authors:

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Presented at: European Geoscience General Assembly Vienna, Austria - April, 2011 Authors:

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  1. Coupled NMM-CALMET Meteorology Development for the CALPUFF Air Dispersion Modelling in Complex Terrain and Shoreline Settings Presented at: European Geoscience General Assembly Vienna, Austria - April, 2011 Authors: Zivorad Radonjic,* Dr. Douglas B. Chambers, Bosko Telenta and Dr. Zavisa Janjic * Contact: Zivorad Radonjic, zradonjic@senes.ca

  2. Overview • Introduction • Study Background • Approach To Simulations • Approach To Validation • Comparison of WRF-NMM Model Versions 3.1.1 and 3.2.1 • Effects of Horizontal Resolutions • Validation with Local Observations • One Year vs. Five Year Meteorological Datasets • Conclusions

  3. Introduction A study was undertaken to prepare and validate high-resolution three-dimensional meteorology suitable for use as input into the CALPUFF/CALMET air dispersion model system in complex terrain with a shoreline. The main goal was to demonstrate the good performance of CALMET in a setting that involves both complex terrain and a shoreline (land-water interface). Improvements in CALMET performance possible using fine resolution meso-scale model inputs were also demonstrated.

  4. Study Background • Meteorology required for CALPUFF modelling of industrial site in complex terrain with shoreline • A challenging meteorological environment • Site-specific meteorology required for both long- and short-range modelling • No local observational data available for time period in question

  5. Approach To Simulations • Weather Research and Forecasting - Nonhydrostatic Mesoscale Model (WRF-NMM) used as meso-scale model • WRF-NMM modelled on 6 km and 2 km horizontal resolution • WRF-NMM used to initialize CALMET modelled on 2 km and 250 m horizontal resolution • 2009 meteorology modelled Example Large Domain (6 km x 6 km resolution) for WRF-NMM Model Example Small Domain (2 km x 2 km resolution) for WRF-NMM – CALMET Model

  6. Approach To Validation • Simulations validated by: • Comparison of two versions of WRF-NMM • Comparison between models run of different horizontal resolutions • Comparison of simulations with observational data • Wind Rose Comparisons • Descriptive Statistics • All validations at 10 agl Select Meteorological Stations Used for Model Validation

  7. Comparison of WRF-NMM Model Versions • WRF-NMM Versions 3.1.1 and 3.2.1 compared • Versions yielded similar results • Good predictions of wind direction • Wind speeds over-predicted due to averaging / surface • Roughness over water causes higher wind speed predictions Wind Rose Comparison for Large WRF-NMM Domain (6 km resolution) - Charlo Airport

  8. Effects of Horizontal Resolutions - 1 • Both WRF-NMM simulations over-predict wind speed due to averaging / under-prediction of surface roughness over water / land interface • Improved accuracy with finer (2 km) resolution • WRF-NMM – CALMET simulation provides better prediction of wind speed due to better representation of surface characteristics and vertical resolution • No significant improvement in agreement with wind direction between the three models. Wind Rose Comparison for Gaspe Airport

  9. Effects of Horizontal Resolutions - 2 • Wind speed predictions improve with finer resolution (250 m) WRF-NMM- CALMET model • Slight under-prediction versus over-prediction for other models • No significant change in agreement with wind direction between the four models. Wind Rose Comparison for Bathurst Airport

  10. Effects of Horizontal Resolutions - 3 • Descriptive statistics used to evaluate simulation results Wind Speed Summary Statistics – Bathurst Station Q-Q Plot of Observed vs. Modelled Wind Speed – Bathurst Station

  11. Effects of Horizontal Resolutions - 4 • Finer resolution improves: • BIAS (average of all the differences between forecast and observation) • Mean Average Error (the average magnitude of errors between forecast and observation) • Root Mean Square Error (measures the average magnitude of the error in a set of forecasts, with increase weighting on larger errors) • Descriptive statistics consistent with wind rose data • Over-prediction of wind speeds at larger horizontal resolutions • Good agreement of wind speeds at smaller horizontal resolutions • More accurate predictions with higher horizontal resolutions • WRF-NMM/CALMET on 250 m resolution most accurate simulation

  12. Validation with Local Observations - 1 • WRF-NMM/CALMET on 250 m horizontal resolution run for 2009 meteorology • Observations from local (2.5 km away) meteorological station available for 1999 to 2003 • Good agreement noted between 2009 generated meteorology and observational data X - Site X – Nearby Site

  13. Validation with Local Observations - 2 CALMET Derived Site Wind Rose 2009 vs. Nearby Site 1999-2003 Observations

  14. One Year vs. Five Year Meteorological Datasets • WRF-NMM/CALMET on 250 m horizontal resolution run for 2009 meteorology compared to 2004 to 2008 meteorology • Differences between simulated meteorology for a 5-year period and a 1-year period are inconsequential For well simulated meteorological data sets a single year of the derived three-dimensional meteorology can, for most purposes, be considered to provide a reasonable description of on-site observations. CALMET Derived Site Wind Rose 2009 vs. Nearby Site 1999-2003 Observations

  15. Conclusions • Improvements in wind speeds predictions are achieved with use of finer resolution meso-scale meteorological modelling in shoreline complex terrain situations • Wind direction is not sensitive to effects of finer resolution modelling in these situations • Coupled WRF-NMM/CALMET system provides a sound alternate to costly and time consuming on-site data collection • One year of simulated meteorology corresponds closely to longer periods of record and can used satisfactorily in environmental assessments / air dispersion modelling if generated meteorology sufficiently represents on-site observations.

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