1 / 30

East Texas Air Quality Forecasting Systems (ETAQ-F) Evaluation of Summer 2006 Simulations for TexAQS-II and Transition

East Texas Air Quality Forecasting Systems (ETAQ-F) Evaluation of Summer 2006 Simulations for TexAQS-II and Transition to Assessment Study. Daewon W. Byun F. Ngan, X. Li, D. Lee, S. T. Kim, H.C. Kim, I.B. Oh, and F. Cheng Institute for Multi-dimensional Air Quality Studies (IMAQS)

royal
Download Presentation

East Texas Air Quality Forecasting Systems (ETAQ-F) Evaluation of Summer 2006 Simulations for TexAQS-II and Transition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. East Texas Air Quality Forecasting Systems (ETAQ-F)Evaluation of Summer 2006 Simulationsfor TexAQS-II and Transition to Assessment Study Daewon W. Byun F. Ngan, X. Li, D. Lee, S. T. Kim, H.C. Kim, I.B. Oh, and F. Cheng Institute for Multi-dimensional Air Quality Studies (IMAQS) University of Houston (UH)

  2. http://www.imaqs.uh.edu/

  3. AQF Modeling Domains – F1 (June 2005 – Current)

  4. Multi CPU Single CPU Data Flow 2005/2006 UH AQF systems (F-1 & F-2) Download ETA Forecast F1=2000 imputed, Houston; F-2=2005 projected, E-Texas MM5 simulations (24 CPUs) 36 km domain 36 km domain 12 km domain 12 km domain 04 km domain 04 km domain st nd st nd st nd 1 day 2 day 1 day 2 day 1 day 2 day 1 CPU 1 CPU 1 CPU 1 CPU 1 CPU 1 CPU 54 hr forecasting simulation MCIP 36 km MCIP 36 km MCIP 12 km MCIP 12 km MCIP 04 km MCIP 04 km st nd st st st st 1 day 2 day 1 day 1 day 1 day 1 day SMOKE 36 km SMOKE 36 km SMOKE 12 km SMOKE 12 km SMOKE 04 km SMOKE 04 km st 1 day nd nd nd 2 day 1st day 2 day 1st day 2 day Post-Process Visualization Statistics Web Display 36 km domain 36 km domain st nd 1 day 2 day Batch mode operation with minimal intervention 12 km domain 12 km domain nd 2 day st 1 day 04 km domain 04 km domain nd 2 day st 1 day CMAQ simulations (36 CPUs)

  5. Time series of regional daily max ozone June 2005 – May 2006

  6. 2006 June – 2006 Oct (TexAQS-II)UH (Univ. of Houston)AQF (Air Quality Forecasting) Systems Spatial Resolution 36 km : U.S. Continent 12 km : East Texas (2005) State of TX, LA, OK, AR, and MS (2006) 04 km : Houston and Galveston Area (F1) / HGA & DFW (F2 & F3) MM5 – 43 layers, CMAQ-23 layers Operation Period and Duration (May 2005 ~ Current) Spin-up : 6 hrs (0th day 18 CST – 0th day 23 CST) Forecasting : 46 hrs (1st day 00 CST – 2nd day 23 CST) Different Air Quality Forecasting Systems Forecast 1 (F1) : MM5 modified by UH + TEI imputed for 2000 + CMAQ v4.4 Forecast 2 (F2) : MM5 modified by UH + TEI imputed & projected for 2005 + CMAQ v4.4

  7. Modeling Domains – F2, TexAQS-II

  8. Anthropogenic Emissions: for F1 (2005 & 2006) • TEI 2000 Base5b • TexAQS 2000 episode used for State Implementation Plan • The day of Week • Aug. 25th Friday, Aug. 26th  Saturday, Aug. 27th  Sunday, Aug. 30th  Monday ~ Thursday • CB4, SAPRC99, and RADM2 • Area & Non-road: 2000 Emissions Inventory • NEI99 (Final version 3) • CONUS 36-km domain • Particulate matters and precursors (NH3, SO2) • Processor: SMOKE version 2.1 • Internal database: TCEQ’s (for spatial and temporal allocation) Default & TCEQ’s for chemical speciation

  9. Anthropogenic Emissions for F2 (2006)Projected Texas EGU NOx emissionsafter State Implementation Plan (SIP) 2000 2005 2007 • 2007 emissions inventory were projected from 2000 EI with growth and control factors from TCEQ. • For HG NOx emissions for 2005, a factor of 1.747 was applied on 2007 EI based on the 2005/2007 MECT (Mass Emission Cap and Trade) allowances.

  10. Anthropogenic Emissions: for F2 (2006) VOC emissions for imputation after SIP 2000 2007 • UH AQF system uses additional VOC emissions at the 2007 level.

  11. MOBILE6 NOx emissions for 2000 and 2007 2000 2007 • The emissions amounts for each county, vehicle type, hour and species were determined for 2005 based on those for 2000 and 2007. • Then, the factor was applied on 2007 MOBILE6 emissions to get 2003 emissions.

  12. ETAQF 2006 F1 & F2 Meteorology (F1 & F2 used UH MM5) * improved LULC * improved MRF for stable PBL and transition times (under development) * cloud; both the subgrid scale explicit scheme at 4-km * satellite observed sea surface temperature (in preparation for sensitivity testing) Emissions (F1 = 2000 SIP imputed TEI vs. F2 = 2005* projected) * 2005 TEI (projected from 2000 & 2007) * 2000 HRVOC (instead of 2005 projected) * Mobile projected for 2003 * satellite-observed fire events (in preparation) CMAQ (F1 = HGB 4-km vs. F2 = Extended 4-km (HGB + DFW) * with and w/o cloud attenuation * CB4 for forecasting and SAPRC99 for evaluation (on-going) * Better regional characterization at 12-km resolution What Configurations were used for ETAQ-F 2006?

  13. Monitoring site on Houston-Galveston domain F1 Model: F1

  14. Monitoring sites for Dallas & Houston domain F2 Model: F2

  15. June 2006 July 2006 rain missed August 2006 September 2006 Aug 19 - pcpn 9/14 upset event 8/23 rain missed

  16. NOx daily mean time series for F1 & F2 Aug 23rd rain missed in AQF 2000 TEI “projected” 2005 TEI Started using projected emissions (July 17)

  17. O3 Scatter plot for F2 (daily max) F1 F2

  18. MM5 re-simulation Improving wind simulation is the most important factor for better AQM performance • FDDA is a proven technique to improve the meteorology reanalysis • Using IMAQS MM5-based Real-Time data assimilation framework, multiple observational datasets from Meteorological Assimilation Data Ingest System (MADIS) and CAMS met data. • A comprehensive surface obs. (SFC – from ASOS by NOAA/NWS) • Improved radiosonde observations (RAOB) • Aircraft sounding (ACARS) winds • Improved NOAA Profiler Network (NPN) data • Tested a variety of assimilation configurations to identify the best combination to arrive at “TMNS11”  Start from 36km MM5 simulation using EDAS (to provide BC for nest domain)  nest down to 12-kmMADIS & CAMS data to improve MM5 to improve

  19. Data sets used for FDDA Pink dots: CAMS Black dots: MADIS SFC (not shown) Upper air data Profiler data Sounding data Aircraft data Satellite data Multi-step FDDA Grid Nudging 3 hourly – 12 km Hourly – 4km

  20. Multi-Step FDDA with MM5 36km & 12km (3D nudging for u,v for everywhere, T & RH nudging in free atmosphere) 4-km domain  grid & surface nudging for wind components only Multi-step FDDA 12-, 4-km domain Multi-step nest-down assimilation Grid Nudging 3 hourly – 12 km Hourly – 4km SFC nudging

  21. 8/15 8/16 front 80 ppb front 8/17 110 ppb H 140 ppb H 150 ppb 8/18 high O3 background 8/21 8/20 120 ppb 8/19 Rainfall at 9 – 11 CST 8/14 90 ppb 110 ppb 70 ppb Overview of weather patterns and O3 levels

  22. Does the Assimilation Improve Met Simulations? 8/14 TMNS11 AQF 8/16

  23. Does the Assimilation Improve Met Simulations? 8/17 TMNS11 AQF 8/18

  24. Does the Assimilation Improve Met Simulations?

  25. CMAQ re-simulation summary • Better Met.  Better Air Quality simulation? AQFn (F2 emissions) vs. TMNS11n • CMAQ re-simulation nickname & description 1) AQFn  F1 MM5 fcst + F2 level AQF emission 2) TMNS11n  TMNS11/MCIPn + F2 level AQF emission AQFn TMNS11n

  26. August 16, 2006 AQFn vs TMNS11n : High O3 day - Met. changes in AQM  changed O3 level & spatial distribution significantly - TMNS11 reproduced O3 conc. better than AQF

  27. August 17, 2006 (1)AQFn vs TMNS11n : High O3 day

  28. August 14, 2006 AQFn vs TMNS11n : Low O3 day - TMNS11 didn’t reproduce O3 conc. better than AQF

  29. Evaluation of CMAQ Assessment Runs < TMNS11,c90,c91 > - Stats. : no big difference - high R,IOA(except 8/19) Mean Bias - low emiss.  - bias - high emiss.  + bias - all positive (except 8/19) - need further improvement

  30. Summary • MM5 re-simulation results To improve Met simulation : several assimilation methods/data tested  TMNS11 provides better met. - removal of some not observed T-storm development - reduction of WD bias - more realistic wind variations overall -but still unwanted flow patterns occurred : 8/18~19 • CMAQ re-simulation results - Assimilation provides better O3 level & spatial distributions more often - Not always improve met & air quality simulation results  Careful evaluation with various data necessary for each day to find causes of discrepancy Acknowledgement: HARC, TCEQ, EPA, NASA • http://www.imaqs.uh.edu/

More Related