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NOAA National Air Quality Forecast Guidance for Ozone and Particulate MatterDecember 9, 2009Daewon W. Byun1*Hsin-Mu Lin1, Daniel Tong1, Tianfeng Chai1, Ariel Stein1, Roland Draxler1, Hyun-Cheol Kim1, Fantine Ngan1, Pius Lee1, Rick Saylor1, Jeff McQueen2, Youhua Tang2, Jianping Huang2, Hochun Hwang2, Dong-Chul Kim2, Marina Tsidulko2, Rohit Mathur5, George Pouliot5, Shobha Kondragunta4, Jerry Gorline, Ivanka Stajner3, and Paula Davison31NOAA/Air Resources Laboratory2NOAA/NCEP, 3NOAA/OST, 4NOAA/NESDIS5EPA/Atmospheric and Modeling & Analysis Division
OutlineOverview of NOAA National Air Quality Forecasting SystemPerformance of ozone guidancePerformance of experimental PM forecastingFY10 & future developmental plans
*National Air Quality Forecast Capability
Improve model bases for AQ alertsProvide AQ information for people at risk
Near-term Operational Targets:Ozone, smoke coverage extended NationwideWhen NCEP is ready for CONUS 4-km NAM meteorology (NAM-B at 4-km) High resolution AQ prediction (4km) for CONUS
Longer range:Quantitative PM2.5 predictionExtend air quality forecast range to 48-72 hoursInclude broader range of significant pollutantsFY09 Prediction Capabilities: Operations at 12-km resolution: Ozone, expanded from EUS to CONUS, 9/07Smoke implemented over CONUS, 3/07Experimental testing:Ozone upgradesSmoke predictions over Alaska and HawaiiDevelopmental testing: Ozone over AK and HIComponents for particulate matter (PM) forecasts2009: smoke
142NAM-CMAQ NAQFC Current Configuration Ozone production & PM experimental http://www.weather.gov/aqEmissions: EPA CEM anthropogenic inventories 2005 base year projected to current year w/ EGUBEIS V3 Biogenic Emissions
Met Model: North American Model (NMM) Non-hydrostatic Multi-scale Model (NMM)12 km 60 Levels
AQ Model: EPA Community Model For Air QualityCMAQ V4.6: 12 km/L22 CONUS DomainOper: CB-IV gas-phaseExper/Dev: CB05/ Aero-4 aerosolsOutput available on National Digital Guidance Database48 hour forecasts from 06/12 UTC CyclesCONUS 5x DomainEastern US 3x DomainFY 06-07Data and Modeling Systems
Number of observed values higher than 76 ppb threshold 1200 UTC8-h ozone, by regionFewer cases in the East in 2009,compared to 2007 and 2008(except for CA) Performance of O3 forecastJerry Gorline
8-h ozone bias, three-year comparisonAugust 2007, 2008, 2009CONUS, 1200 UTC cycle (48 hour forecast mean) experimental:slightly higher bias in 20092007: CBIV2008: CB052009: CB05Jerry Gorline
NCEP Air Quality Forecast 2009 Verification (1 hr Max ozone for Day 2 for June, July, Aug)- Increasing Bias trend as Summer progressed for Eastern U.S. Max temp bias improves slightly by August but ozone errors increased in East U.S.RMSEBIASCB-IVCB-05*** CB-05 mechanism is used for improving SOA, etc for CMAQ4.7Jeff McQueenEastWest
Sept.Rock Mountain Upper MidwestNortheast USPacific Coast RegionLower MidwestSoutheast US1/1/-9/30 2009
Rock Mountain RegionUpper MidwestNortheast USPacific Coast RegionLower MidwestSoutheast US
Interim summary of NAQFS O3High O3 events decreased considerably 2007 2008 2009 except for CA. Also, CB05 high bias much more serious than CB-IV. CB05 high bias increased in 2009 compared to 2008High bias accumulates in Eastern USWould 2009 economic downturn cause higher model bias due to wrong emission projection (e.g., Bill Ryan)?Causes of CB05 high bias over CB-IV may be ???Addition of terpene emissions make more radicals available affecting formation of PAN species NOY recycling (additional NOx source)Inadequate removal processes (dry & aqueous deposition)Anything else (such as interaction of gas-, aerosol, and heterogeneous reactions)?
How dose PM behaves? Seasonal variation of activity8-h ozone vs. 1-h aerosols (June 2008 to August 2009)Threshold: 76 ppb (ozone) 35 ug/m3 (aerosols)Aerosols are active in both winter and summer
2009 AQFS Performance DevelopmentalPM2.5, US (CB05/Aero4, Daily Max)OBS meanCMAQ meanMean BiasNormalizedMean BiasRMSENormalized Mean ErrorCorrelation(hourly)
Correlation(daily max)1/1/-9/30 2009
Rock Mountain Upper MidwestNortheast USPacific Coast RegionLower MidwestSoutheast US1/1/-9/30 2009
Rock Mcountain RegionUpper MidwestNortheast USPacific Coast RegionLower MidwestSoutheast US
Regional performance of aerosols Fraction Correct (FC) Jan 2008 to Sept 2009, 35 ug/m3lower bias inwinter 2009 compared to winter 2008,except PC regionCB05AERO-41/1/-9/30 2009
Forecast and Obs (1 hr avg) for Oct 31-Nov 30, 2009(48 hour mean forecast vs. Obs)PC region show not much bias in Nov. 2009, but UM shows high bias (~ 10 ug/m3)UM PC Jerry Gorline
Underprediction prevalent in Eastern U. S. on Aug 16
Large area of overprediction by Aug 24
Preliminary SEARCH Data Jefferson St., Atlanta, GARain ?Rick Saylor
Preliminary SEARCH Data Yorkville, GAIntermittent RainRick SaylorComparison with AQFS model speciation output underway..
Investigation of model bias:
Study sulfate production by different mechanisms
Gas phase chemistry: CB-IV, CB05, SAPRC99, CB05 Cloud processes & Aqueous chemistry Scavenging and wet deposition Model domain Eastern US Horizontal: 12-km resolution Vertical: variable thickness 22 layers Study period: 14-23 July, 2004 (ICARRT case) 2004 ICARRTAriel Stein
Differences in Sulfate Production (by mechanism)Backward trajectoriesover source areasVariable & away from large sourcesTotal similar but CB-IV mostly from H2O2 & MHPCB05 & SAPRC show contributions from PE/MN & PAA
H2O2CB-IV formation rate 60% higher than CB05 and SAPRC-99. CB05 produces more new HO2 than SAPRC-99
MethylhydroperoxideCB-IV: XO2 + HO2 MHPCB05: MEO2 +HO2 MEPXMEPX + OH prodMEPX + hn prodHCO3 + HO2 MEPXSAPRC99:C_O2 + HO2 COOHCOOH + OH prodCOOH + hn prodobsMHP from CB-IV seriously over estimatedMEPX from CB05 & COOH from SAPRC well predicted butAriel Stein
CBIV: PACD well predictedPA + HO2 prod + 0.21 PACDPeroxyacetic acidSAPRC-99:PAA overpredictedPA + HO2 prod + 0.75 PAACB05:PACD overpredictedPA + HO2 prod + 0.8 PACDPACD + OH PACXO3 + HO2 prod +0.8 PACD
On-going work Include Fire Emissions: Link NESDIS HMS/USDA Bluesky/ARL HYSPLIT inputCMAQ ModelChemical-Transport ComputationNCEP Meteorological Model (NAM)PREMAQEPA Emissions InventoryHMS data & Bluesky(as in HYSPLIT)Fire Emission: EPA inv + Bluesky(CMAQ ready data)Emissions(CMAQ ready data)Met. Data(CMAQ ready data)1st step: Fire event process2nd step: Plume rise processEmission due to the FireHsin-Mu LinAriel Stein
HMS Case for 2009-05-09 1200Z runThe plot show the difference of PM2.5 between the CMAQ with and without Smoke ProductComparison with the satellite fire detection and HYSPLIT PM product are also providedHsin-Mu Lin
PM2.5 bias to observation (small circles) with & without fire emissions(* climatology fire emission is removed from the HMS/BlueSky/HYSPLIT emissions) CMAQ PM2.5 Difference(HMS PARA) in mg/m3Without fire emissions:CMAQ PM2.5 in mg/m3in mg/m3Bias here did not improve with the addition of fire emissions(Colors for circles and background Have no relations)Improved with fire emissionsCase for 2009-08-02(good model prediction if color between circles and background cells are close)Youhwa Tang
Major Dust Emission SourcesEPAs NEI includes anthropogenic dust sources (Road dust, mining, construction, tilting, etc)Anthropogenic sourcesCropland sources Natural dust not accounted for yet in NAQFS Owens flux equation Threshold friction velocities from field and wind tunnel measurements; USGS land use and soil data; Vegetation growth and near source enhanced deposition;Modeling Natural Dust requiresOn-going work to include Wind-Blown Dust EmissionsDust emissions most active in Spring Annual Emissions ~ 3 Tg/yrDaniel Tong
Testing algorithms -- Comparison with IMPROVE & MODIS(April 2003 Case Study)Improved, but not enough. MODISMODELDaniel Tong
NCEP FY10 Plans: Global-Regional LinkagesCMAQ Lateral Boundary Condition Impact Study : GOCART Global model w/ full aerosols (dust, biomass) coupled to CMAQ
Implement Real-time Global Dust Forecasts: Couple w/ para GFS fields to drive GOCART GFS T382-GOCART 1 real-time runs to 60 hours w/ 1 degree surface cover
Develop Chemical Data Assimilation & global aerosol interactions : GOCART aerosol analyses coupled to GSI & GFS/CFS radiationOnline NEMS GOCART module Adding AOD tracer to GSIPrefer on-line so forward guess at same timeHo-Chun HwangDong-Chul Kim
Chart8
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CALIPSO
MODEL
Aerosol Extinction (1/km)
Hight (km)
-12.6E 14.9N, 2006072214
2006072214a
TIME20060722
LON/LAT-12.6074409514.89016628
1-0.548.318401346.20E-02
2-0.379999995254.906826026.31E-020.1032252274
3-0.259999990562.372329716.35E-020.1655975571
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5-2.00E-0280.253845216.40E-020.3166418152
60.100000008990.848899846.43E-020.407490715
70.2199999988102.67633066.46E-020.5101670456
80.3400000036115.84648136.50E-020.6260135269
90.4600000083130.44396976.55E-020.7564574966
100.5799999833146.55015566.62E-020.9030076522
110.6999999881164.2347266.72E-021.0672423782
120.8199999928183.48315436.89E-021.2507255325
130.9399999976204.48776257.18E-021.455213295
141.059999943227.29096987.63E-021.6825042648
151.179999948252.78135689.20E-021.9352856216
161.299999952281.04388431.09E-012.2163295059
171.419999957309.94265750.12419841442.5262721634
181.539999962338.94763180.13197544222.8652197952
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211.899999976428.91604615.51E-024.0604526443
222.019999981459.87194821.36E-024.5203245925
232.1399998664.02E-02492.72708133.26E-035.0130516738
242.2599997521.23E-01525.51629642.43E-035.5385679702
252.3799996380.1533277035557.95471191.67E-036.0965226821
262.4999995230.1495400071588.31500241.46E-036.6848376845
272.6199994090.1482252032612.91784671.92E-037.2977555312
282.7399992940.1259313524636.08404542.15E-037.9338395766
292.859999186.40E-02658.55975343.11E-038.59239933
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313.0999989511.06E-01692.38183592.07E-039.9617161024
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353.5799984939.79E-02722.71752931.25E-0312.8271184462
363.6999983798.73E-02722.63061521.08E-0313.5497490614
373.8199982646.69E-02720.12231457.31E-0414.2698713759
383.939998153.33E-02719.79473885.15E-0414.9896661147
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404.179997921729.66125498.10E-0516.4454445571
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485.1399970053.55E-02929.92681885.83E-0923.1655673599
495.2599968911.41E-02962.98529053.96E-0924.1285526504
505.3799967771008.3787233.86E-0925.1369313734
2006072214a
CALIPSO
MODEL
Aerosol Extinction (1/km)
Hight (km)
-12.6E 14.9N, 2006072214
2006072214b
TIME20060722
LON/LAT-14.5997419423.50664139
1-0.548.952407843.30E-01
2-0.379999995255.608718873.23E-010.1045611267
3-0.259999990563.167167663.16E-010.1677282944
4-0.139999985771.691925053.10E-010.2394202194
5-2.00E-0281.272468573.03E-010.320692688
60.10000000890.110337510792.006301882.96E-010.4126989899
70.21999999880.4578230977103.96345522.88E-010.5166624451
80.34000000360.4701274931117.2448732.81E-010.6339073181
90.46000000834.24E-01132.00633242.73E-010.7659136505
100.57999998330.3681202233148.41081242.65E-010.9143244629
110.69999998810.2300999612166.52192692.56E-011.0808463898
120.81999999280.2029348165186.33993532.46E-011.2671863251
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141.0599999430.2460214943230.86366272.20E-011.7058476868
151.1799999480.2169344723255.49653632.10E-011.9613442231
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383.939998151.14E-01724.11706543.68E-0414.9337129059
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404.1799979218.79E-02732.40484622.27E-0416.3941646881
414.2999978077.67E-02750.4878546.07E-0517.1446525421
424.4199976927.48E-02771.71270752.60E-0517.9163652496
434.5399975781.03E-01796.84442149.13E-0618.713209671
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454.7799973497.02E-02852.42260743.94E-0720.3866201324
464.8999972343.97E-02881.84985357.46E-0821.2684699859
475.019997124.66E-02905.04577643.20E-0822.1735157623
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495.259996891961.35986331.77E-0824.0664389191
505.379996777996.47088621.63E-0825.0629098053
2006072214b
CALIPSO
MODEL
Aerosol Extinction (1/km)
Hight (km)
-14.6E 23.5N, 2006072214
2006072314a
TIME20060723
LON/LAT-22.81062317
1-0.546.952594761.53E-02
2-0.379999995253.431625371.54E-020.1003842201
3-0.259999990560.747241971.55E-020.1611314621
4-0.139999985768.992126461.55E-020.2301235886
5-2.00E-029.52E-0278.261619571.55E-020.3083852081
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100.5799999833143.82632451.70E-020.8822809372
110.6999999881161.58352661.68E-021.0438644638
120.8199999928181.16241461.65E-021.2250268784
130.9399999976202.68673711.82E-021.4277136155
141.059999943226.27883912.91E-021.6539924546
151.179999948251.86317445.42E-021.905855629
161.299999952279.13323978.32E-022.1849888687
171.419999957307.53359990.10915923122.4925224686
181.539999962337.15197750.13478143512.8296744461
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252.3799996380.1011383012559.83776865.28E-036.072219124
262.4999995230.1472731829593.1701054.53E-036.665389229
272.6199994090.1339015812619.76965332.19E-037.2851588823
282.7399992940.1176950186643.42974852.08E-037.9285886308
292.859999180.1212706193665.30816652.54E-038.5938967973
302.9799990650.1371465474683.0625613.35E-039.2769593583
313.0999989514.73E-02698.24456794.00E-039.9752039262
323.2199988370.1292796731709.25964364.68E-0310.6844635698
333.3399987220.1054983065717.52966316.14E-0311.4019932329
343.4599986088.69E-02722.01025395.75E-0312.1240034868
353.5799984937.52E-02724.2083743.75E-0312.8482118608
363.6999983798.39E-02725.92315672.68E-0313.5741350175
373.8199982645.46E-02726.66558841.32E-0314.3008006059
383.939998155.65E-02727.80169683.02E-0415.0286023027
394.0599980354.60E-02731.82781981.83E-0415.7604301225
404.1799979214.76E-02732.46789551.01E-0416.492898018
414.2999978073.55E-02752.17309575.42E-0517.2450711137
424.4199976923.56E-02769.29852292.51E-0518.0143696366
434.5399975784.59E-02798.28704831.18E-0518.8126566849
444.6599974632.01E-02834.59613041.48E-0619.6472528153
454.7799973493.19E-02866.1632082.88E-0720.5134160233
464.8999972342.92E-02871.8923952.32E-0721.3853084183
475.019997123.19E-02894.533029.45E-0822.2798414383
485.1399970051.34E-02925.54425051.60E-0823.2053856888
495.259996891959.69085693.47E-0924.1650765457
505.379996777995.4027713.91E-0925.1604793167
2006072314a
CALIPSO
MODEL
Aerosol Extinction (1/km)
Hight (km)
-22.8E 12.1N, 2006072314
2006072314b
TIME20060723
LON/LAT-23.2871513414.27466583
1-0.546.733661655.79E-02
2-0.379999995253.18145375.83E-020.0999151154
3-0.259999990560.463020325.83E-020.1603781357
4-0.139999985768.670852665.83E-020.2290489883
5-2.00E-0277.903884895.83E-020.3069528732
60.100000008988.269950875.86E-020.3952228241
70.219999998899.871215825.97E-020.4950940399
80.3400000036112.90171056.34E-020.6079957504
90.4600000083127.66490946.89E-020.7356606598
100.5799999833144.04856877.72E-020.8797092285
110.6999999881162.06999218.98E-021.0417792206
120.8199999928181.9188081.06E-011.2236980286
130.9399999976203.75071721.22E-011.4274487458
141.059999943227.65919491.31E-011.6551079407
151.179999948253.52883911.30E-011.9086367798
161.299999952281.24288941.24E-012.1898796692
171.419999957310.11041260.12264550482.4999900818
181.539999962339.98651120.12096203862.839976593
191.659999967370.52206420.10951463883.2104986572
201.779999971401.2143869.20E-023.6117130432
211.8999999760.1371763498431.58523566.49E-024.0432982788
222.0199999811.64E-01462.36059573.88E-024.5056588745
232.1399998661.96E-01494.00183111.50E-024.9996607056
242.2599997521.14E-01526.78485113.04E-035.5264455567
252.3799996389.19E-02559.29919432.44E-036.085744751
262.4999995230.2079082727594.55438232.29E-036.6802991333
272.6199994090.1910316497620.63818362.06E-037.3009373169
282.7399992940.1930202246643.46569822.49E-037.9444030151
292.859999180.1870443225665.30853272.78E-038.6097115478
302.9799990650.1047546044682.08227542.46E-039.2917938232
313.0999989518.26E-02696.9132691.98E-039.9887070922
323.2199988376.04E-02708.68206791.86E-0310.6973891601
333.3399987228.74E-02718.28558351.82E-0311.4156747436
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2006072314b
CALIPSO
MODEL
Aerosol Extinction (1/km)
Hight (km)
-23.3E 14.2N, 2006072314
Sheet2
Sheet3
Interim summary of NAQFS Experimental PM2.5Winter high bias and summer low bias in PM2.5 mass & regional differences not well understoodNH3 emission issues?NOy budget including dry & aqueous depositions?PM speciation information neededBetter understanding of dependence of PM speciation to gas-phase mechanism necessary gas, aerosol, heterogeneous reaction interactionsDevelop methods (data/algorithms) for including intermittent emissions from forest fire, wind-driven dust, (volcanic ashes, etc & BCs)Link with global models
**********Transition from model underprediction to overprediction observed in CONUS wide averages more-or-less reflected in all regional averages, although timing of transition is not identical.*On Aug 16, 2009, model underprediction is prevalent in the eastern U. S.*Character of model vs observation comparisons has changed dramatically by Aug 24. Analysis to focus on comparison of speciated PM2.5 model predictions vs observations to hopefully provide insight on causes of models seasonal PM2.5 biases.*Change in PM2.5 composition occurred after apparent rain and frontal passage. (Rain sensor at JST was not working during this period)*Character of PM2.5 composition also changed after precipitation and frontal passage. Model results to be compared to SEARCH data and eventually IMPROVE speciated data when it is available.*******Highlights:Dust is emitted from both anthropogenic and natural sources;EPA NEI includes six anthropogenic sources, such as fugitive dust from paved and unpaved road, mining, construction etc.The natural dust emissions, such as wind-blown dust from desert land and cropland, are not accounted for. Because natural dust could have a dramatic effect on air quality, esp. in the Southwest and over the agricultural area, we want to have the forecasting capability of predicting natural dust.The natural dust emission is calculated using the Owens flux equation, and threshold friction velocities from field and wind tunnel studies, mostly by Dale Gillette and colleagues. The land use and soil type data is from USGS, and soil moisture is obtained from real-time weather forecast model;We also simulate crop and vegetation growth over the US based on planting and harvesting information provided by USDA national agricultural statistical service (NASS);*Highlights:The addition of natural dust emissions improves CMAQ performance over the dust active area. Here are two examples of comparing the model with IMPROVE measurements. The green line is CMAQ without natural dust, the red line is CMAQ with dust, and the dash line is IMPROVE observation. At both GUMO and SACR sites, adding the dust emissions has significantly improved the model performance.The missing dust sources over the northern Mexico are responsible for the remaining discrepancy between the model and observation. 46Several NAM upgrades were made in 2006 and 2007 that I think also contributed to the AQF positive performance.
Retrospective experiments were done for all potential configurations followed by real time testing on May 16.Most important change included tight coupling of vertical coordinates and improvements to emissions for california