The Use of High Resolution Mesoscale Model Fields with the CALPUFF Dispersion Modelling System in Prince George

BC

Bryan McEwenMaster’s project 2000-2002

Atmospheric Science GroupDr. Peter L. JacksonUniversity of Northern British Columbia

Funding supplied by the Oil and Gas Commission’s Environmental Fund

Study conducted with the High PerformanceComputing Facility at UNBC with an SGI Origin 3400.

CALPUFF

• A Dispersion modelling system composed of 3 separate modules:

– CALMET – a meteorological model, constructs 3-dimensional fields of wind, temperature and other variables from local observations. Deterministic in nature. Requires upper air data as well as data from at least one surface station.

– CALPUFF – a Gaussian Puff dispersion model, predicts 3-dimensional fields of pollutant concentrations. Requires CALMET fields and an inventory of pollutant sources and emission rates.

– CALPOST – a post processor that extracts pollutant concentrations from CALPUFF fields.

RAMS

• A prognostic (forecasting) mesoscale model, able to simulate circulations from hemispheric in scale down to 100’s of metres.

• Smaller grids are nested within larger parent grids when higher resolution is required.

• Calculates meteorological variables each time step. Smaller grid sizing requires a smaller time step and therefore more calculations.

• Significant computer resources needed. SGI Origin 3400 ‘Fraser’ used at the HPC facility at UNBC.

A “HINDCAST” instead of a “FORECAST”

• For regulatory modelling, a meteorological period in the past is used for dispersion analysis.

• RAMS is therefore used to make a “hindcast” of what the atmosphere was like during the period.

• ‘Nearby’ observations are used as boundary conditions to guide RAMS’ simulations. Predictions are periodically ‘corrected’ on the large scale.

• Numerical models such as RAMS are able to ‘telescope down’ from the large scale motions to predict circulations on a local scale. The influence of topography, vegetation, bodies of water, radiation etc. are accounted for by the model.

Research Objectives(Can simulated meteorology (RAMS fields) be used in lieu of meteorological observations to

perform dispersion modelling in an area of complex terrain??)

• To assess the use of RAMS fields in producing high quality CALMET meteorological fields.

• To assess the use of RAMS fields in producing high quality CALPUFF pollutant concentration estimates.

Methodology

-SO2 chosen to model, within a 24.5km by24.5 km domain surrounding Prince George.

-Three 5-day periods in 1999 of moderate to high levels of SO2 chosen to analyze.

- 6 surface meteorological stations available. - 1 upper air meteorological station available.- 4 SO2 monitoring stations available.

Surface meteorological station

Upper air meteorological station

Significant SO2 source

SO2 monitoring station

Methodology cont’d CALPUFF FLOWCHART

INITIALIZING Geophysical Data(topographical heights, vegetation)

INITIALIZING Upper Air Data Surface Station Data(winds, temp, RH, cloud….)

METEOROLOGICAL PROCESSING CALMET3-d fields of wind and other variables

DISPERSION MODELLING CALPUFF

Methodology cont’d MODEL CONFIGURATION

"RAMS-CALMET" "CALMET-1" "CALMET-3" "CALMET-6"

RAMS generated 1 upper air station, 1 upper air station, 1 upper air station,surface and upper air 1 surface station 3 surface stations 6 surface stations

stations'

CALMET CALMET CALMET CALMET

CALPUFF CALPUFF CALPUFF CALPUFF

RAMS Initialization

The National Centers for Environmental Prediction (NCEP) coarse gridded datasets were used to initialize and nudge RAMSforecasts.These gridded fields at 2.5o

lat. by 2.5o long, with 17 pressure levels in the vertical

Analysis of CALMET Meteorological Modelling

Analysis of Results – WIND FIELDS

- Wind data from 5 of the 6 surface stations used to test each model’s wind fields(heavy arrows indicate stationlocations)

- CALMET-3 used two of these5 stations in its analysis, hencetesting for this model is favourably biased.

- CALMET-6 used all surface stations in its analysis, so no test of its wind fields was possible.

Analysis of Results – WIND FIELDS

Average Root Mean Square Vector Error (RMSVE), modelled surface winds compared to observed winds at 5 station locations.

MODEL JANUARY APRIL JUNE

CALMET-1 2.66 1.74 1.90

CALMET-3 1.48 1.30 1.74

RAMS-CALMET 2.35 2.01 2.01

 

Analysis of Results – WIND FIELDS

Analysis of Results – WIND FIELDSWindrose diagram showing RAMS-CALMET modelled wind direction at

Plaza during January Period.

Analysis of Results – WIND FIELDSWindrose diagram showing CALMET-3 modelled wind direction at Plaza

during January period.

Analysis of Results – BOUNDARY LAYER

Inversions conditions, developing overnight, exacerbate poor air quality by limiting vertical mixing

During several evenings of the threeperiods examined, strong inversionconditions existed.

RAMS consistently did not develop accurate temperature profiles within the boundary layer. (extreme case shown)

Analysis of CALPUFF Dispersion Modelling

Analysis of Results – SO2 CONCENTRATIONS

CALMET-1 CALMET-3 CALMET-6 RAMS-CALMET

JANUARY 99 98 61 67

APRIL 97 97 71 68

JUNE 79 97 83 84

Mean Relative Error (MRE) (%), modelled 24-hr SO2 concentrations from observedconcentrations at 4 monitoring sites.

Conclusions

• There is evidence that RAMS accounted for much of the influence of topographical heights on the regional winds.

• The use of RAMS fields with CALMET, although possessing errors, produced meteorological fields as good or better than CALMET using 1 or 3 surface stations.

• CALPUFF dispersion estimates of SO2 made with RAMS input were more representative of observed concentrations than those made with 1 or 3 station CALMET fields.