1 / 17

NAM (WRF-NMM) Meteorology

Evaluation of Real-time Air Quality Forecasts from WRF-NMM/CMAQ and NMMB/CMAQ Using Discover-AQ P-3B Airborne Measurements Youhua Tang 1,2 , Jeffery T. McQueen 2 , Marina Tsidulko 1,2 , Jianping Huang 1,2 , Pius Lee 3 , Ivanka Stajner 4 and NASA Discover-AQ Measurement Team.

marvin
Download Presentation

NAM (WRF-NMM) Meteorology

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. Evaluation of Real-time Air Quality Forecasts from WRF-NMM/CMAQ and NMMB/CMAQ Using Discover-AQ P-3B Airborne MeasurementsYouhua Tang1,2, Jeffery T. McQueen2, Marina Tsidulko1,2, Jianping Huang1,2, Pius Lee3, Ivanka Stajner4and NASA Discover-AQ Measurement Team 1. I.M. Systems Group Inc., Camp Springs, MD2. NOAA/NCEP/EMC3. NOAA Air Resource Laboratory, Silver Spring, MD4. NOAA Office of Science and Technology, Silver Spring, MD

  2. Operational and Developmental 12km NAQFC Systems (July 2011) NAM (WRF-NMM) Meteorology NAMB (NMM-B) Meteorology CMAQ CB04 CMAQ CB05 CMAQ CB04 CMAQ CB05 without wildfire emission CMAQ/SMOKE for processing plume rise and generating gridded wildfire emissions CMAQ CB05 with wildfire emission BlueSky emission inventory NOAA Hazard Mapping System (HMS) fire locations

  3. Discover-AQ P-3B Flight on 07/01

  4. For all flights (July 1-29) below 1km The models generally undepredicted biogenic emitted species, especially for terpenes. The bias is related to certain areas.

  5. Model predicted wildfire CO compared to HMS plumes

  6. Missed wildfire plumes On 07/01 identified by Acetontrile

  7. For All flights above 1km Acetonitrile is highly correlated with CO enhancement in wildfire plumes. Black carbon or aerosol absorption seems not a good tracer for long-range transported fire plumes as it could be wet removed.

  8. WRF-NMM and NMM-B yield very different background CO concentrations over the east coast. NMM-B has slightly higher PBL heights (black-and-white lines show the PBL heights). The wildfire run yields remarkable fire-emitted CO, but tends to be too diffusive.

  9. The flight on 07/14. The model missed wildfire plumes The flight on 07/27. The model overpredicted wildfire plumes below 3km

  10. The model overpredicted the wildfire emissions in Northern Virginia/Maryland and missed those in Tennessee and Carolinas.

  11. Meteorology change has significant impact on transported species. NMM-B/CMAQ yield lower concentrations than the WRF-NMM/CMAQ for almost all species for both CB4 and CB05 mechanism.

  12. The models have relatively poor performance during wildfire events, especially for fire-emitted species, like CO.

  13. Summary • Meteorology has a large impact on CMAQ predictions. • NMM-B/CMAQ yields lower concentrations than the WRF-NMM/CMAQ for almost all species, • Most pronounced for long-lived and long-range transported species, like CO and NOy. • In July 2011, there were many wildfire events that through long-range transport affected forecasts along P3-B flight tracks: • Underprediction (07/01 and 07/14) • Good prediction (07/11), • Overpredicted for a nearby fire event (07/27). • In general, poorer predictions for wildfire events than for no-fire events. • There are some systematic biases for primary emitted species • toluene, black carbon (high bias), • methanol (low bias) • isoprene and monoterpenes (low bias in certain non-urban areas).

More Related