1 air quality reanalysis (configuration for 2010 htap production) aqast-9 june 2-4, 2015, st louis,...

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Air Quality Reanalysis (Configuration for 2010 HTAP production)

AQAST-9 June 2-4, 2015, St Louis, MO

Greg Carmichael1, Pius Lee2 , Brad Pierce3, Dick McNider4, Ted Russell5, Edward Hyer6, Yang Liu7, Arastoo Pour Biazar4,

Yongtao Hu5, Talat Odman5, Scott Spak1, David Edwards8, Ken Pickering9, Youhua Tang2, Li Pan2, Hyuncheol Kim2, Daniel Tong2

1 College of Engineering, University of Iowa, Iowa City, IA2Air Resources Lab., NOAA Center for Weather and Climate Prediction, College Park, MD

3National Environmental Satellite and Information Service (NESDIS), Madison, WI4Department of Atmospheric Science, University Alabama, Huntsville AL

5School of Civil and Environmental Engr., Georgia Institute of Technology, Atlanta, GA6Naval Research Laboratory, Monterey, CA

7Department of Environmental Health, Emory University, Atlanta, GA 8 Corporation for Atmospheric Research, Boulder, CO

9Atmospheric Chemistry and Dynamics Lab., NASA, Greenbelt MD

Courtesy: Dan Costa “New Directions in Air Quality Research at the US EPA”

2AQAST-9 June 2-4, 2015, St Louis, MO

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Outline on progress The Regional Chemical Analysis TT started in 2013: Deliverable in 2014: Analysis fields for July 2011

provided for GaTech and UMD for SIP modelingo Assimilated exo-domain wild fire, O3 using RAQMo Upgrade emission based on NEI2011o Assimilated wild-fire using NESDIS obs, PM2.5

constraints using MODIS AOD & AQS PM2.5

o Assimilated cloud attenuated photolytic rateo Mimicked SIP reduced RMSE by 400% for PM2.5

Deliverable in 2015: Analysis fields for 2010, support HTAPo Assimilate lightning NOx, PAR, DYNAMO Isoprene

User friendly portal and archive for chemical analysis fields over Continental U.S.


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Constrained

SatelliteProducts

Global Assimilation

+ AQ Assessments

+ State Implementation Plan Modeling

+ Rapid deployment of on-demand rapid-response forecasting; e.g., new fuel type,…, etc.

+ Health Impacts assessments

+ Demonstration of the impact of observations on AQ distributions

+ Ingestion of new AQAST products into operations

http://acmg.seas.harvard.edu/aqast/projects.html

AQAST Project: Air Quality Reanalysis (Translating Research to Services)

3:30-5:00 Session Yang Liu: MODIS C6Alvarado & Hegarty: NH3

Huang, McNide, Lee : TSkin


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Applications of Reanalysis

Reanalysis would be able to provide PM2.5 speciation data with national coverage at county level


NOMADS

RSIG .

NOAA Service: A user friendly downloadable archive

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analysisNew


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Comparison of Wind along flight track of P3B on July 20 2011

Spirals over Wilmington and Edgewood

Model under-predicted wind shear

Lee & Liu, 2014Int.J.Environ. Res. Public H.

Time labels in transactPickering and Lee, 2014Environ. Manager


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Lightning NOx

AIRNow

Cloud-obs Photolysis rates

Isoprene& PAR

done

done

done

Yet to doNew


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Lightning Process currently used in CMAQ 5.0*

*CMAQ Version 5.0 and higher contains a scheme based on Allen et al. (2012, ACP) that was funded under NASA Applied Sciences Air Quality Program project (Ken Pickering, PI):

Method for estimating lightning flash rates LNOx production per flash Method of allocating LNOx production in the vertical

NLDN (National Lightning Detection Network) data

Map to CMAQ grid

Calculate Total monthly Lightning flash Count over each grid

Model’s convective Precipitation rate

Model’s strike count (monthly total)

Mean LTratio used in CMAQ NLDN/Model


July 1-10, 2011 NO2 (Left) Base (Right) with LNOx, (Bottom) Difference

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98100

Midwest convections. GOES13

AQAST-9 June 2-4, 2015, St Louis, MO 10

July 1-10, 2011 O3 (Left) Base (Right) with LNOx, (Bottom) Verification


O3 10 days avg Stations Obs mean Mean bias RMSE Corr. Coef.

Base 3222 36.45 -0.17 15.81 0.6636.45 2.90 24.54 0.53

O3 10 days avg (RM) Stations Obs mean Mean bias RMSE Corr. Coef.

Base 483 42.36 1.32 13.32 0.61Include LNOx 42.36 6.61 29.60 0.48

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July 1-10, 2011 PM2.5 (Left) Base (Right) with LNOx, (Bottom) Verification

PM2.5 10 days avg Stations Obs mean Mean bias RMSE Corr. Coef.

Base 1801 12.67 -3.47 13.22 0.2512.67 -3.07 13.58 0.24

PM2.5 10 days avg (UM) Stations Obs mean Mean bias RMSE Corr. Coef.

Base 276 17.71 -3.66 16.40 0.23Include LNOx 17.71 -2.61 17.08 0.22

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The analysis forward model is tested and used to generate July 2011 analysis fields. July 2011 analysis fields was used by Georgia Tech for a 14-day SIP

simulation and showed significant improvement in RMSE Data Set assimilated: RAQMS (MLS, OMI O3, MODIS AOD); HMS Fire; GOES

cloud fraction for photolytic rate correction; MODIS AOD; AQS O3, PM2.5

Assimilate lightning NOx: Use NOAA hourly reporting of the National Lightning Detection Network to derive and distribute LNOx

Preliminary surface NOx and O3 verification showed over-estimation Further improvement of LNOx assimilation algorithm is being test Analysis configuration also includes observation set on biogenic emission

from the DYNAMO team Production FY2010 in conjunction with HTAP support Portal via RSIG is being tested

Summary


Tong and Lee et al. 2015: “NOx trends over large cities”, Atmos. Environ

Pan and Lee et al. 2014: “Forecasting performance of NAQFC”, Atmos. Environ

7th International Workshop onAir Quality Forecasting Research

September 1-3 2015 NOAA NCWCP, College Park, MD

Deep Convective Clouds and Chemistry (DC3) Case Study – May 29-30, 2012

Multicell storm inNW Oklahoma inearly evening of May 29 sampled byNASA DC-8 and NCAR G-V; stormsimulated usingWRF-Chem at 1-kmresolutionModel-calculated reflectivity and aircraft tracks

Trajectories show transport of storm outflow to Southern Appalachians by early afternoon May 30, where NO2 peak was detected by OMI and DC3 research aircraft

Courtesy: Pickering, Cummings, Allen

WRF-Chem -- Vertical Cross Section for NOxWRF-Chem (cloud-resolved) 0100 UTC


LNOx Production Per Flash:• 500 moles NOx per flash assumed for continental US based on

INTEX-A GEOS-Chem results (e.g., Hudman et al., 2007, JGR)

and cloud-resolved model simulations for individual stormsconstrained by anvil aircraft observations from severalfield programs (Ott et al., 2010, JGR)

• However, estimates of LNOx production from OMI observations over the Gulf of Mexico and surrounding coastal regionsare ~190 to 250 moles per flash (Pickering et al., 2015, JGR,to be submitted)

• User can modify moles per flash for IC and CG flashes

Vertical Distribution of LNOx Production:• Based on Koshak et al. (2014, Atmos. Res.) vertical distributions of lightning channel lengths from Northern Alabama Lightning Mapping Array -- work sponsored by NASA Applied Science Air Quality Program


MODIS (Moderate Resolution Imaging Spectroradiometer) AOD

http://terra.nasa.gov/About/Orbit: 705 km, 10:30 a.m. descending

node (Terra) or 1:30 p.m. ascending node (Aqua)

Swath Dimensions:

2330 km (cross track) by 10 km (along track at nadir)

Spatial Resolution:

250 m (bands 1-2)500 m (bands 3-7)1000 m (bands 8-36)

Courtesy :NESDIS

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National correlation map between AIRNow measurement and MODIS AOD

Typically good correlation betweensurface PM2.5 and AOD retrievedby MODIS


Optimal Interpolation (OI)OI simplifies the extended Kalman filter formulation

(Dee et al. Q. J. R. Meteor. Soc. 1998) by limiting the analysis problem to a subset of obs.

Obs far away (beyond background error correlation length scale) have no effect in the analysis.

Injection of Obs through OI takes place at 1800 UTC daily.

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18AQAST-9 June 2-4, 2015, St Louis, MO

1 air quality reanalysis (configuration for 2010 htap production) aqast-9 june 2-4, 2015, st louis,...

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atmospheric research

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