Assimilation of Satellite Ozone Measurements during the 1999 Southern

Oxidants Study: Impact on Continental US Regional Air

Quality Predictions

R. Bradley Pierce1, Todd Schaack2, Jassim A. Al-Saadi1, Ivanka Stajner3, Hiroo Hayashi3, Steven Pawson3, Martin D. Mueller3, Don Johnson2, Jack Fishman1, Jim Szykman4

1NASA/LaRC, 2UW/SSEC, 3NASA/GMAO, 4EPA/OAQPS

NASA ESENational Applications

NASA LaRC/USEPAAir Quality Applications

GroupDoreen.O.Neil@nasa.gov

757. 864.8171

NASA Air Quality Applications*

*From NASA Earth Science Enterprise Applications Plan

Goal: Improved capability to Air Quality managers to assess, plan & implement sound-science, emissions control strategies, policy, & air quality forecasts.

The primary partners for the Air Quality Management program are the US Environmental Protection Agency (EPA) and the National Oceanic and Atmospheric Administration (NOAA).

SOS99 O3 Assimilation Study

•Two Chemical Data Assimilation Systems (DAS) are evaluated in a precursor study for Chemical DAS using NASA AURA measurements.

•FvDAS1 uses the NASA GMAO2 operational O3 DAS [Stajner et al., 1999], with parameterized chemistry (provided by RAQMS) to assimilate SBUV data.

•RAQMS3 uses the Statistical Digital Filter (SFD) [Stobie, 2000] (an Optimal Interpolation approach) and online chemical predictions, to evaluate the feasibility of assimilating trajectory mapped solar occultation and TOMS total column measurements.

1Finite Volume Data Assimilation System2Global Modeling and Assimilation Office

3Regional Air Quality Modeling System

The challenge for space based ozone measurements is separation of the stratosphere from troposphere to isolate a tropospheric component

Constituent Assimilation in GMAOStratospheric Ozone: mature system, ability to assimilate different

types of data from multiple platforms (PI: Ivanka Stajner)Aerosol: evolving system, focusing initially on MODIS data with

GOCART aerosol modules (PI: Arlindo da Silva)Carbon species: CO starting (AIRS, TES); CO2 under

development (PI: Steven Pawson)Foci: Research-based assimilation efforts are the main focus (e.g., data

impacts; confronting models)New: development of ozone modules for GEOS-5Involvement in NASA (and other) field missions (NRT products)

– pre-AVE (Jan 2004); INTEX (summer 2004), …

Regional Air Quality Modeling System (RAQMS)A NASA Langley/UW-Madison Cooperative Research Effort*

Public Impact

ScientificUnderstanding

RAQMS Ozone Assimilation/Prediction February 27, 2001

Global Assimilation

RegionalPrediction

NASA SatelliteProducts

*RAQMS includes online chemistry from the NASA LaRC unified (troposphere/stratosphere) chemical mechanism driven by the UW-Hybrid (global isentropic/sigma coordinates) and UWNMS (regional Non-Hydrostatic) dynamical cores.

RAQMS [Pierce et al., 2003] is a nested global- to regional-scale meteorological and chemical modeling system for assimilating and predicting the chemical state of the atmosphere (air quality).

NASA operational chemical DAS

Prototyping NASA chemical DAS

JCSDA (NASA, NESDIS1, OAR2, NCEP3 Joint Center for Satellite Data Assimilation)

GMI (NASA Global Modeling Initiative)

Strat/Tropchemical mechanism Development

GMAO (NASA Global Modeling and Assimilation Office)

Prototype chemical DAS

RAQMS (Regional Air Quality

Modeling System)

1 NOAA National Environmental Satellite Data and Information Service2 NOAA Office of Oceanic and Atmospheric Research3 NOAA National Center for

Environmental Prediction

15

Satellite data used in RAQMS SOS99 O3 Assimilation

Solar Backscatter column measurements

V6.1

Trajectory mapped Solar Occultation limb measurements:

4

RAQMS6hr FxFvDAS IC

SDF occultationAssimilation

SDF columnAssimilation

RAQMS Assimilation Procedure

P (mb)

O3

Time

Five Day Stratospheric Trajectories

RAQMSFirst GuessT+6hr

RAQMSFirst GuessT+12hr

OccultationMeasurement

Troposphere

RAQMS6hr FxFvDAS IC

SDF occultationAssimilation

SDF columnAssimilation

RAQMS6hr FxFvDAS IC

SDF occultationAssimilation

SDF columnAssimilation

RAQMSFirst GuessT+18hr

AssimilationCycle

5

Trajectory mapped solar occultation measurements constrain stratospheric O3 assimilation. Mass weighted column ozone analysis increment (TOMS-background) provides constraint on tropospheric column.

•Daily ozone profiles from Global Ozone Monitoring Experiment (GOME*) Neural Network Ozone Retrieval System (NNORSY) [Muller et al., 2003]

Data Sets used for SOS99 evaluation

* GOME is onboard the European Remote Sensing Satellite (ERS-2) PI, John Burrows Institute for Environmental Physics, University of Bremen, Germany

•Global WMO ozone sondes

GOME NNORSY absolute and relative error profile

GOME NNORSY Stratospheric ComparisonJune-July, 1999 Zonal Means

FvDAS and RAQMS show similar difference patterns in the upper (above 10mb) stratosphere. FvDAS shows additional differences in the Northern Hemisphere lower stratosphere.

Both RAQMS and FvDAS show high biases of 10-15 ppbv relative to the tropical GOMENNORSY retrievals. FvDAS shows an additional low bias of 10-15 ppbv relative to the mid-latitude GOME NNORSY retrievals.

GOME NNORSY Tropospheric ComparisonJune-July, 1999 Zonal Means

Tropospheric Ozone Column (TOC)TOMS/SBUV TOC is derived using the residual techique [Fishman and Balock, 1999]

GOME NNORSY and FvDAS Northern Hemisphere TOC are low relative to TOMS/SBUV.

RAQMS is lower than TOMS/SBUV over Northern Hemisphere industrial areas (Europe, Eastern US, E. Asia)

6

Comparison with Sonde derived TOC(Huntsville, AL)

Both RAQMS and FvDAS capture daily variations inTropospheric O3 Column at Huntsville, AL. The single GOME NNORSY data point significantly underestimates the observed tropospheric column*.

*Huntsville is not included in GOME NNORSY training set

June-July, 1999 Sonde profile comparison (Lat>30oN)

RAQMSG assimilation shows mean biases of <10% except in the mid troposphere (400mb). RAQMSG RMS errors reach ~50% at 400mb and the surface.

FvDAS assimilation shows mean positive biases of 50% in the lower stratosphere (100mb) and ~15% negative biases in the free troposphere. RMS errors are similar to RAQMSG with an additional peak in the lower stratosphere (100mb).

Contours: assimilated ozone in December 2002, using operational SBUV data

Adding MIPAS data results in large differences (shaded) in the Tropics, below the ozone peak, and in the polar night during December 2002.

(SBUV+MIPAS) - SBUV assimilation December 2002

Impact of MIPAS limb measurements on FvDAS Assimimation1

1 Wargan et al., sub. to Q. J. R. Meteorol. Soc., 2004

MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is a Fourier transform limb viewing spectrometer measuring in the near to mid infrared onboard the ESA ENVISAT.

FvDAS Dec 2002 assimilation vs Sondes (Lat>45oN)

N=59

FvDAS December 2002 Assimilation vs Sondes

Adding MIPAS 45oN, improves the agreement with WMO sonde measurements poleward of 40oN.

Such MIPAS impacts would lead to improvements in the SOS99 middle stratospheric FvDAS biases shown earlier.

Regional AQ Forecast BC impact StudyTwo regional (CONUS) 80km AQ forecasts for the period from June 11- July 18, 1999 were conducted using the nested component of RAQMS (RAQMSN) to evaluate the impact of large-scale boundary conditions (BC) during SOS99.

The “ASSIM-BC” forecast uses 3D chemical BC from the RAQMSG assimilation. The “CBC” forecast uses CONUS area averaged BC (on constant pressure surfaces) from the RAQMSG assimilation.

Both forecasts are constrained with NOAA EDAS meteorological fields.

Tropospheric Ozone Column (TOC)

Surface O3 from EPA NetworkJune 11 - July 18, 1999

A regional high ozone event occurred over the Midwest and Northeastern US during the SOS99 time period (June and July, 1999). The RAQMSN 80km CONUS grid is also shown by (+). The “interior” domain used for the BC

evaluation is indicated by ( )

8hr average >85 ppbv corresponds to an AQI “unhealthy for sensitive groups”

Comparison of ASSIM-BC Forecast with EPA Surface Network

June 11 - July 18, 1999

Correlations are generally high (>0.5) over Eastern US except for the extreme NE, Southern Florida and along the Appalachian Mountains.

Largest RMS forecast errors are in urban areas of California, NE due to inability of 80km forecast to capture local variations in precursors.

Biases are generally within (+/-) 10-15 ppbv except along the Gulf Coast and the Central Valley

Example of ASSIM-BC and CBC forecasts vs EPA Surface Timeseries

Cleveland, OH

The RAQMSN ASSIM-BC forecast for Cleveland, OH captures the observed decline in O3 near the 5th and 30th days of the forecast period better than the CBC-BC forecast resulting in slight increases in the correlation with surface measurements.

PDFs of RAQMSN vs EPA Statistics Interior sites June 11- July 18, 1999All local times Mid-day (Zenith<60)

systematic increases1 in mid-day correlations and decreases2 in mid-day RMS errors

1 > 25% increase in mid-day correlations for 27% of EPA sites. >25% decrease in mid-day correlations for 9% of EPA sites. 2 > 5% decrease in mid-day rms errors for 22% of the EPA sites. >5% increase in mid-day rms errors for 12% of the EPA sites. 3 > 5% decrease in overall mean biases for 20% of the EPA sites. >5% increase in overall mean biases for 44% of the EPA sites.

but systematic increases3 in overall

mean biases

ASSIM-BC forecast shows..

...relative to the CBC forecast.

but only small changes in overall

correlations and RMS errors,

only small changes in mid-day biasesEPA-RAQMS EPA-RAQMS

Future directions…...

Intercontinental Transport and Chemical Transformation, 2004 Lagrangian Mission

(ITCT-Lagrangian-2K4)

NOAA New England Air Quality Study (NEAQS)

mission

NASA Intercontinental Chemical Transport Experiment- North America (INTEX-NA)

mission

Coordinators:

David Parrish NOAA Aeronomy LabKathy Law IPSL Service Aéronomie

Goals:

To investigate intercontinental transport of manmade pollution and determine the chemical transformation that occurs during this transport.

EU Intercontinental

Transport of Ozone and Precursors –

(ITOP)

North Atlantic Study

RAQMS will provide daily on-line global chemical forecasts, initialized with assimilated ozone distributions, to the NASA INTEX-NA science team for mission flight planning.

•Assimilation of trajectory mapped solar occultation measurements reduces biases in the lower stratosphere/upper troposphere relative to assimilation of SBUV measurements.

•RAQMSN AQ forecast correlations and RMS errors are systematically improved relative to mid-day EPA surface O3 measurements during SOS99 when 3D large-scale BC are used to constrain the forecast.

•Knowledge gained from studies such as these can provide valuable guidance for the development of an operational chemical DAS and AQ forecasting system.

•The concurrent summer 2004 NEAQS and INTEX-NA missions provide an ideal opportunity for NASA/NOAA collaborative studies of the impact of large-scale BC on AQ forecasts.

Conclusions:

Contact Information: R. Bradley Pierce, NASA/LaRCr.b.pierce@larc.nasa.gov

Extra Figures

(55 species/families explicitly transported, 86 calculated, PCE assumptions for “fast” species)

Chemical familiesOx=O(1D)+O(3P)+O3+NO2+HNO3+2(NO3)+3(N2O5)+HNO4+PAN+MPANNOy=N+NO+NO2+NO3+2(N2O5)+HNO3+HNO4+BrNO3+ClNO3+PAN+ONIT+MPANCly=HCl+ClONO2+ClO+2(Cl2O2)+OClO+ClO2+2(Cl2)+BrCl+HOCl+ClBry=HBr+BrONO2+BrO+BrCl+HOBr+Br

1) Ox2) Noy3) Cly4) Bry5) HNO36) N2O57) H2O28) HCl9) ClONO210) OClO11) N2O12) CFCl3 (F11)13) CF2Cl2 (F12)14) CCl415) CH3Cl16) CH3CCl3 (MTCFM)17) CH3Br18) CF3Br (H1301)

19) CF2ClBr (H1211)20) HF21) CFClO22) CF2O23) CH424) HNO425) HOCl26) H2O27) NO328) NO229) CH2O30) CH3OOH31) CO32) HBr33) BrONO234) HOBr35) BrCl36) Cl2

37) C2H6 (ethane, 2C)38) ALD2 (acetaldehyde+higher group, 2C)39) ETHOOH (ethyl hydrogen peroxide, 2C)40) PAN (2C)41) PAR (paraffin carbon bond group, 1C)42) ONIT (organic nitrate group, 1C)43) AONE (acetone, 3C)44) ROOH (C3+hydrogen peroxides group, 1C)45) MGLY (methylglyoxal, 3C)46) ETH (ethene, 2C)47) XOLET (terminal olefin carbon group, 2C)48) XOLEI (internal olefin carbon group, 2C)49) XISOP (isoprene, 5C)50) XISOPRD (isoprene oxidation product-long lived, 5C)51) PROP_PAR (propane paraffin, 1C)52) CH3OH (methanol)53) XMVK (methyl vinyl ketone, 4C)54) XMACR (methacrolein, 4C)55) XMPAN (peroxymethacryloyl nitrate, 4C)

RAQMS unified (strat/trop) chemistry

Stratosphere+CH4&CO oxidationNMHC Chemistry

RAQMS NMHC Treatment Explicit treatment of C2H6 (ethane), C2H4 (ethene) and CH3OH (methanol) oxidation

[Sander et al., 2003]. C3H8 (propane) is handled semi-explicitly. C4 and larger alkanes and C3 and larger alkenes are lumped via a carbon-bond

approach [Zaveri and Peters, 1999] which accounts for long-lived species and their intermediates based on the Carbon Bond Mechanism IV [Gery et al., 1989].

Isoprene is modeled after the Carter 4-product mechanism as modified for RADM2.

July, Med O3, High NOx

•Standard• Revised 1: Remove NO3 + peroxy radical rxns• Revised 2: Revised 1 + ...

LaRC Run Versions

•Peroxide oxidation branching matched to GMI• Organic nitrate production matched to GMI• RO2 + NO branching matched to GMI

GMIHarvard mechanism [Bey et al., 2001]with Gear solver for 80 species (all transported in GMI)

10-day diurnal equilibrium runs with/without NMHC conducted as part of the NASA Global Modeling Initiative (GMI) unified chemistry development.

Each of the Auras instrument team's Algorithm Theoretical Basis Documents (ATBD) are now available after having gone through peer review. They can be found at: http://eospso.gsfc.nasa.gov/atbd/pg1.html

High Resolution Dynamics Limb Sounder (HIRDLS)•limb scans in the vertical at multiple azimuth angles, •measures infrared emissions in 21 channels ranging from 6.12 mm to 17.76 mm.

Microwave Limb Sounder (MLS)• 5 microwave channels (118, 190, 240, 640 GHz, and 2.5THz•Ability to see through upper tropospheric clouds

NASA Earth Observing System (EOS) Aura Satellite

Ozone Monitoring Instrument (OMI)•hyperspectral (740 wavelength bands)imaging solar backscatter (visible and ultraviolet) radiometer •Large swath large provides global coverage in 14 orbits (1

day) at 13 x 24 km Tropospheric Emission Spectrometer (TES) •high-resolution infrared-imaging Fourier transform spectrometer

•capability to make both limb and nadir observations.

The GMAO ozone DAS is running in near-real-time as a part of the GMAO's first and late look assimilation system configurations in support of the EOS Terra satellite. The GMAO ozone DAS uses the Finite-Volume Data Assimilation System (fvDAS) dynamical core and Physical-space Statistical Analysis System (PSAS1) assimilation. Operational DAO's ozone assimilation is currently using NOAA SBUV/2 data.1Cohn, S., A. da Silva, J. Guo, M. Sienkiewicz, and D. Lamich. Assessing the effects of data selection with DAO PSAS. Mon. Wea. Rev., 126:2913-26, 1998.

GOME NNORSY Sonde profile comparison (Lat>30oN)

P (mb)

PercentO3 (ppbv)

GOME overestimates ozone in the planetary boundary layer. Note: 1999 WMO sonde profiles and HALOE solar occultation measurements were used in NNORSY training set.

TOC Probability Density Functions1

1Comparison of distributions removes time and space coincidence criteria between the sonde and assimilation/retrieval. Inferred RMS errors are based on Monte Carlo estimates of random error associated with KS significance.

Comparison with EPA surface measurementsHuntsville, AL

Online chemistry in the RAQMS assimilation significantly improves representation of peak amplitudes and diurnal variability in surface ozone.

Example of RAQMSG ASSIM and RAQMSN ASSIM-BC Fx vs EPA Surface Timeseries

Huntsville, AL

The 80km RAQMSN ASSIM-BC forecast for Huntsville, AL captures the observed decline in O3 near the 30th day of the forecast period better than the RAQMSG 2x2.5o ASSIM but underestimates mid-day peaks between days 5-10 resulting in a slight decrease in the correlation with surface measurements.