The Australian Air Quality Forecasting System (AAQFS)
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1 The Australian Air Quality Forecasting System (AAQFS) P.C. Manins 1, M.E.Cope 1,2, G.D Hess 3, K.J. Tory 3, Sunhee Lee 1, K.Puri 3, M.Young 4 1 CSIRO Atmospheric Research, 2 CSIRO Energy Technology, 3 Bureau of Meteorology Research Centre 4 Environment Protection Authority of NSW
2 GENERAL PROJECT OBJECTIVES Develop and implement a numerical air quality forecasting system in Melbourne and Sydney Australia Demonstrate the System in Sydney during the Olympics and Para-Olympics (2) AUSTRALIA MELBOURNE SYDNEY A project supported by Environment Australia through the Natural Heritage Trust.
3 Tomorrow will be fine and sunny -with moderate to heavy air pollution AIR AIR QUALITY FORECAST- MELBOURNE 584 INDEX INDEX NORTH EAST NORTH EAST NORTHING(km) PTH GLS GVD MTC PTC FTS PSY PORT PHILLIP BAY ALP PLP BXH BRI DND HEAVY MODERATE HOUR HOUR EASTING (km) LIGHT
4 Is a prognostic air pollution forecasting system worth the considerable effort? Why not a use a statistical forecasting system? More Are spatial and temporal information needed from the forecast? (e.g. hour-by by-hour, suburb-by by-suburb) Support air quality management & policy development? (e.g. VOC controls) Are monitoring data limited? (no extensive network)?
5 Levels of Complexity More 1. Embedded in a operational National Weather Forecasting System AAQFS 2. Extension of Numerical Weather Forecasting Capability e.g.,, Beijing, China 3. NMHS seeking to develop both a national numerical weather and pollution forecast Malaysia? 4. NMHS focussed on forecasting air pollution for a limited region others?
6 AAQFS DESIGN FEATURES Generate air quality forecasts twice per day for a period of hours: (3 pm and 9 am). Consider a range of air pollutants: NOx,, ROC, SO 2, O 3, aerosol, air toxics. Resolve air quality at regional and suburb level (5 km, 1 km). Generate a business as usual forecast and a greener emissions forecast.
7 The Need for High Resolution More Leads to improved weather forecasts Changes in space and time important Necessary to resolve regional flows For air pollution, wind trajectory vital Boundary layer must be resolved For air pollution levels, mixing height vital
8 SYSTEM- FEATURES MET ANALYSIS NWP GASP/LAPS Australian operational weather forecast models EMISSIONS DATABASE INVENTORY EMS-95 derivative AQ + MET OBS. CTM Custom-integrate into NWP EVALUATION AIR QUALITY FORECAST DATA PACKAGE
9 STUDY REGIONS Victoria-Melbourne AUSTRALIA VICTORIA SWANHILL 13 13; x ~5 km WODONGA WANGARATTA LATITUDE (deg. N) MELBOURNE 13 96; x ~1 km GEELONG GSTH GRVD BASS STRAIT SYDNEY Latitude (deg. N) MELBOURNE MTCL -39. ALPH RMIT PAIS BXHL PTCK PORT PHILLIP BAY -4. BRTN HORSHAM WARRNAMBOOL KING IS BENDIGO CASTLEMAINE GEELONG MELBOURNE BASS STRAIT WARRAGUL TASMANIA Longitude (deg. E) LONGITUDE (deg. E)
10 STUDY REGIONS New South Wales-Sydney AUSTRALIA -32. NSW 98 98; x ~5 km MUSWELLBROOK MELBOURNE SYDNEY Latitude (deg. N) SYDNEY 98 56; x ~1 km RICH PENRITH VYNE ORANGE NEWCASTLE LITHGOW SYDNEY WOLLONGONG LATITUDE (deg. N) BLAC LIND ST.M WSTM BRIN CAMD CAMP SYDNEY ROZE LIDC LIVE EARL MASCOT RAND CANBERRA TASMAN SEA LONGITUDE (deg. E) WOOL Longitude (deg. E) PACIFIC OCEAN
11 Data Flows for AAQFS SUPERCOMPUTERS GASP LAPS375 LAPS125 LAPS5 VIC EPA VIC EPA EPA NSW NSW CTM NSW CTM VIC LAPS5 NSW ARCHIVE WEB SITE FTP SITE POST- PROCESSING, ARCHIVING, GRAPHICS, VERIFICATION
12 EPA-Victoria AAQFS Web Page
13 15 March 21 Daily Validation NO y NO 2 VOC O 3
14 PERFORMANCE REVIEW Consider forecasts for some of 2/21 and all of 21/22 photochemical smog seasons 5 km forecasting domains Assess the limit of predictability for forecasts of peak daily 1-hour ozone concentration
15 Verification- Air Quality modelling Example: Sydney 7-day 7 ozone episode January 21 OZONE- HOUR 16, 21/1/21 23/1/21 25/1/21 27/1/ MUSWELLBROOK (ppb) NORTHING ORANGE CANBERRA NEWCASTLE LITHGOW SYDNEY WOLLONGONG PACIFIC OCEAN EASTING
16 CONCENTRATION (ppb) CONCENTRATION (ppb) VINEYARD- O OBS 1 CTM Example: Sydney 7-day 7 ozone episode January LIDCOMBE- O OBS CTM LIVERPOOL- 72 O TIME (hours) OBS 1 CTM WOOLOOWARE- 72 O TIME (hours) OBS 1 CTM CONCENTRATION (ppb) CONCENTRATION (ppb) NORTHING (km) TIME (hours) RICHMOND VINEYARD BLACKTOWN LINDFIELD WESTMEAD ROZELLE LIDCOMBE LIVERPOOL RANDWICK WOOLOOWARE CAMPBELLTOWN APPIN TIME (hours) BARGO EASTING (km)
17 PERFORMANCE REVIEW -32. MUSWELLBROOK REGIONAL FORECASTING -33. NEWCASTLE 2 PEAK 1-HOUR OZONE (Regional) Latitude (deg. N) -34. ORANGE LITHGOW SYDNEY WOLLONGONG FORECAST CONCENTRATION (ppb) CANBERRA PACIFIC OCEAN OBSERVED CONCENTRATION (ppb) Longitude (deg. E)
18 FORECAST CONCENTRATION (ppb) FORECAST CONCENTRATION (ppb) SYDNEY- Daily 1-hour 1 O 3 max SUB-REGIONAL FORECASTING SYDNEY NORTH WEST OBSERVED CONCENTRATION (ppb) SYDNEY SOUTH WEST OBSERVED CONCENTRATION (ppb) LATITUDE (deg. N) FORECAST CONCENTRATION (ppb) NW SW CAMD RICH PENRITH SYDNEY EAST OBSERVED CONCENTRATION (ppb) ST.M BRIN CAMP VYNE BLAC WSTM SYDNEY LIND ROZE LIDC LIVE EARL MASCOT RAND WOOL EAST TASMAN SEA LONGITUDE (deg. E)
19 SYDNEY- Daily 1-hour 1 O 3 max 2 PEAK 1-HOUR OZONE (Suburb) SUBURB-LEVEL FORECASTING FORECAST CONCENTRATION (ppb) LATITUDE (deg. N) NW SW CAMD RICH PENRITH ST.M BRIN CAMP VYNE BLAC WSTM SYDNEY LIND ROZE LIDC LIVE EARL MASCOT RAND WOOL EAST TASMAN SEA LONGITUDE (deg. E) OBSERVED CONCENTRATION (ppb)
20 SYDNEY- Daily 1-hour 1 O 3 max 2 PEAK 1-HOUR OZONE (Monitoring station) STATION-LEVEL FORECASTING FORECAST CONCENTRATION (ppb) LATITUDE (deg. N) NW SW CAMD RICH PENRITH ST.M BRIN CAMP VYNE BLAC WSTM SYDNEY LIND ROZE LIDC LIVE EARL MASCOT RAND WOOL EAST TASMAN SEA LONGITUDE (deg. E) OBSERVED CONCENTRATION (ppb)
21 MELBOURNE- Daily 1-hour 1 O 3 max REGIONAL FORECASTING LATITUDE (deg. N) GEELONG GSTH GRVD BASS STRAIT MTCL MELBOURNE PTCK PORT PHILLIP BAY ALPH RMIT PAIS BXHL BRTN LONGITUDE (deg. E) FORECAST CONCENTRATION (ppb) REGIONAL OBSERVED CONCENTRATION (ppb)
22 1 MELBOURNE- Daily 1-hour 1 O 3 max WEST FORECAST CONCENTRATION (ppb) FORECAST CONCENTRATION (ppb) OBSERVED CONCENTRATION (ppb) GEELONG LATITUDE (deg. N) SUB-REGIONAL FORECASTING GEELONG GSTH GRVD GEELONG BASS STRAIT WEST MTCL MELBOURNE PTCK PORT PHILLIP BAY ALPH RMIT PAIS BXHL BRTN EAST EAST LONGITUDE (deg. E) FORECAST CONCENTRATION (ppb) OBSERVED CONCENTRATION (ppb) OBSERVED CONCENTRATION (ppb)
23 MELBOURNE- Daily 1-hour 1 O 3 max SUBURB-LEVEL FORECASTING PEAK 1-HOUR OZONE (Suburb) LATITUDE (deg. N) GEELONG GSTH GRVD MTCL MELBOURNE PTCK PAIS PORT PHILLIP BAY ALPH RMIT BRTN BXHL FORECAST CONCENTRATION (ppb) BASS STRAIT OBSERVED CONCENTRATION (ppb) LONGITUDE (deg. E)
24 MELBOURNE- Daily 1-hour 1 O 3 max STATION-LEVEL FORECASTING PEAK 1-HOUR OZONE (Monitoring station) LATITUDE (deg. N) GEELONG GSTH GRVD MTCL MELBOURNE PTCK PAIS PORT PHILLIP BAY ALPH RMIT BRTN BXHL FORECAST CONCENTRATION (ppb) O 3 >5 ppb BASS STRAIT OBSERVED CONCENTRATION (ppb) LONGITUDE (deg. E)
25 PERFORMANCE INDICES (O > 3 5 ppb) SYDNEY- NORMALISED BIAS SYDNEY- NORMALISED GROSS ERROR 15 3 Percentage -15 Percentage Regional Suburb Station Regional Subregional Subregional Suburb Station 15 MELBOURNE- NORMALISED BIAS MELBOURNE- NORMALISED GROSS ERROR 3 Percentage -15 Percentage Regional Suburb Station Regional Subregional Subregional Suburb Station
26 AAQFS- PERFORMANCE M O Contingency Table Observed Model Yes No Total Yes d f f+d No m b m+b Total d+m f+b Detected = d/(d+m) correct forecasts False alarm = f/(f+d) missed events
27 SYDNEY MELBOURNE 1 OZONE DETECTION RATE- SYDNEY 1 OZONE DETECTION RATE- MELBOURNE 8 8 Rate (%) Region Sub-region Suburb Rate (%) Region Sub-region Suburb Rate (%) Exceedance concentration (ppb) OZONE FALSE ALARM RATE- SYDNEY Region Sub-region Suburb Exceedance concentration (ppb) Rate (%) Exceedance concentration (ppb) OZONE FALSE ALARM RATE- MELBOURNE Region Sub-region Suburb Exceedance concentration (ppb)
28 AAQFS vs. PERSISTENCE (Sub-regional) AAQFS / PERSISTENCE DETECTION RATE Sydney Melbourne AAQFS / PERSISTENCE FALSE ALARM RATE Sydney Melbourne Exceedance concentration (ppb) Exceedance concentration (ppb)
29 TWO-SCENARIO FORECAST DOSAGE TIME
30 Why is AAQFS special? Provides twice-daily forecasts of AQI and 18 pollutants for EPAs Shows the daily development of pollution (highly instructive/other applications) Because prognostic, unusual events handled Can explore results with off-line tools Alternative scenarios, special locations
31 Why is AAQFS unique? Resolution: 5 km Met, 1 km AQ Integral verification of yesterday s forecast Proven operational within a NMHS Responsive to daily changes in EPA-supplied emissions data Minimal demand on resources by EPAs Green scenarios can be run on special days
32 Experience with Generating Emissions Inventories More Population-based emissions can produce quite acceptable results (no industry) Industry must be treated explicitly Simple biogenics scheme works well Pollution inflows may be much more important in other national settings Seasonal, diurnal and weather-related related emissions changes should be done in-line for simplicity and speed.
33 Prognostic Model + Emissions Inventory Applications More Stand-alone alone applications useful (TAPM) Air quality management planning/scenarios Monitoring network designing Industrial complex emissions management Surveillance of urban pollution emissions Urban design applications Assessments of transport options/technologies Airshed emissions taxes/trading Wind-Power prospecting!
34 AAQFS Experiences More Emissions Inventories our biggest problem Wind-blown dust, other particle sources, difficult effort by Met. Service of Canada commendable Timeliness and quality of air pollution monitoring data is vital for warm starts (assimilation) GRS chemistry adequacy Routine verification of forecasts Backgrounds/domain-size size issue Cooperation between Agencies is important Uptake by others is slow patience!
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