nam (wrf-nmm) meteorology

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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 1. I.M. Systems Group Inc., Camp Springs, MD 2. NOAA/NCEP/EMC 3. NOAA Air Resource Laboratory, Silver Spring, MD 4. NOAA Office of Science and Technology, Silver Spring, MD

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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. - PowerPoint PPT Presentation

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Page 1: 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 Tang1,2, Jeffery T. McQueen2, Marina Tsidulko1,2, Jianping Huang1,2, Pius Lee3, Ivanka Stajner4

and 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

Page 2: NAM (WRF-NMM) Meteorology

2

NAM (WRF-NMM) Meteorology

NAMB (NMM-B) Meteorology

CMAQ CB04 CMAQ CB05

Operational and Developmental 12km NAQFC Systems (July 2011)

CMAQ CB04 CMAQ CB05without wildfire emission

CMAQ CB05with wildfire emission

NOAA Hazard Mapping System (HMS) fire locations

BlueSky emission inventory

CMAQ/SMOKE for processing plume rise and generating gridded wildfire emissions

Page 3: NAM (WRF-NMM) Meteorology

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

Page 4: NAM (WRF-NMM) Meteorology
Page 5: NAM (WRF-NMM) Meteorology
Page 6: NAM (WRF-NMM) Meteorology

The models generally undepredicted biogenic emitted species, especially for terpenes. The bias is related to certain areas.

For all flights (July 1-29) below 1km

Page 7: NAM (WRF-NMM) Meteorology

Model predicted wildfire CO compared to HMS plumes

Page 8: NAM (WRF-NMM) Meteorology

Missed wildfire plumes On 07/01 identified by Acetontrile

Page 9: NAM (WRF-NMM) Meteorology

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.

For All flights above 1km

Page 10: NAM (WRF-NMM) Meteorology
Page 11: NAM (WRF-NMM) Meteorology
Page 12: NAM (WRF-NMM) Meteorology

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.

Page 13: NAM (WRF-NMM) Meteorology

The flight on 07/14. The model missed wildfire

plumes

The flight on 07/27. The model overpredicted wildfire

plumes below 3km

Page 14: NAM (WRF-NMM) Meteorology

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

Page 15: NAM (WRF-NMM) Meteorology

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.

Page 16: NAM (WRF-NMM) Meteorology

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

Page 17: NAM (WRF-NMM) Meteorology

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).