Joint EPA/NASA/NOAA Workshop on Air Quality and …€¢ Challenges: measuring trace gases/aerosols in PBL, tropospheric profiles, cloud screening – Exploit instrument synergy: multi-sensor

NESDIS Office of Research and Applications

Joint EPA/NASA/NOAA Workshop Joint EPA/NASA/NOAA Workshop on Air Quality and Related Climate on Air Quality and Related Climate

Change IssuesChange Issues

Operational Monitoring of Operational Monitoring of Air Quality from SatellitesAir Quality from Satellites

and Research to Operationsand Research to Operations

Mitch GoldbergMitch Goldberg

Chief, Satellite Meteorology and Climatology DivisionChief, Satellite Meteorology and Climatology Division

September 14, 2004September 14, 2004(thanks to Shobha Kondragunta, Chris Barnet , Paul Menzel, and colleagues at CIMSS, UMBC)


NOAA/NESDIS ObjectiveNOAA/NESDIS Objective

Desired outcome:Desired outcome:

•• Build collaborative projects with NASA and EPA that are Build collaborative projects with NASA and EPA that are beneficial to the air quality forecast program.beneficial to the air quality forecast program.

•• Help define requirements for satellite derived air quality produHelp define requirements for satellite derived air quality productscts

•• Help propose new technologies.Help propose new technologies.

•• Help develop air quality products and implement them Help develop air quality products and implement them operationally.operationally.


NOAA’sNOAA’s SatellitesSatellitesTwo polar (POES) and two geostationary (GOES) Two polar (POES) and two geostationary (GOES) environmental satellitesenvironmental satellites


Contributions of Contributions of GEOsGEOs and and LEOsLEOs

GEOsGEOs (Geostationary satellites)(Geostationary satellites)Resolve diurnal cycleResolve diurnal cycleObserve at constant anglesObserve at constant angles

LEOsLEOs (Low Earth Orbiters(Low Earth Orbiters--polar orbiting polar orbiting satellites)satellites)Provide global coverageProvide global coverage


NOAA Satellite ProductsNOAA Satellite Products

AtmosphereAtmosphere•• Temperature soundingsTemperature soundings•• Moisture soundingsMoisture soundings•• WindsWinds•• CloudsClouds•• AerosolsAerosols•• Earth Radiation BudgetEarth Radiation Budget•• PrecipitationPrecipitation•• OzoneOzone

OceanOcean•• Surface temperatureSurface temperature•• Ice coverIce cover•• Surface windsSurface winds•• ColorColor•• Sea levelSea level

LandLand•• Vegetation conditionVegetation condition•• Snow pack characteristicsSnow pack characteristics•• Other land characteristics Other land characteristics

(e,g., (e,g., albedoalbedo, skin , skin temperature, temperature, soil wetnesssoil wetness, , insolation)insolation)

•• Fire locations/Smoke Fire locations/Smoke PlumesPlumes

Air Quality Related Products


Current Operational Satellite Products Useful for Air QualityCurrent Operational Satellite Products Useful for Air Quality

AVHRR vegetation, fires, smokeGOES-8 WF_ABBA fire

product, August 13, 2002

GOES-12 aerosol optical depth, July 15-19, 2004

Currently used in NCEP’sair quality forecast efforts


Looking ahead: the next 10 years and beyond Looking ahead: the next 10 years and beyond in the era of in the era of hyperspectralhyperspectral measurementsmeasurements

•• Exploit the current sensorsExploit the current sensors–– Demonstrate air quality applications of current satellite producDemonstrate air quality applications of current satellite products relevant to AQts relevant to AQ–– Improve the quality of the current products (algorithms and caliImprove the quality of the current products (algorithms and calibration)bration)–– Develop new products (e.g., emissions from biomass burning)Develop new products (e.g., emissions from biomass burning)–– Work with air quality forecast groups to utilize the satellite dWork with air quality forecast groups to utilize the satellite data in models (forecast ata in models (forecast

verification or improvements via assimilation)verification or improvements via assimilation)

•• Prepare for the future sensorsPrepare for the future sensors–– Collect requirements Collect requirements –– Invest in algorithm development workInvest in algorithm development work

•• Challenges: measuring trace gases/aerosols in PBL, Challenges: measuring trace gases/aerosols in PBL, tropospherictropospheric profiles, cloud profiles, cloud screeningscreening

–– Exploit instrument synergy: multiExploit instrument synergy: multi--sensor and / or multisensor and / or multi--platform approachesplatform approaches–– Active participation in ground campaignsActive participation in ground campaigns–– Develop capabilities to process NASA’s air quality products nearDevelop capabilities to process NASA’s air quality products near real time at NOAAreal time at NOAA


GOESGOES--R AQ products at 15 minute refresh rate R AQ products at 15 minute refresh rate over the Americasover the Americas

•• Aerosol optical depthAerosol optical depth•• Aerosol sizeAerosol size•• Aerosol typeAerosol type•• Biomass burning emissionsBiomass burning emissions•• Carbon monoxide Carbon monoxide •• Fire size and locationFire size and location•• Height of aerosol layerHeight of aerosol layer•• Methane Methane •• OzoneOzone

NPOESS and METOP will provide the same up to six times

per day but with global coverage


TroposphereTroposphereColumnColumnAPSAPSAerosol shape and Aerosol shape and refractive indexrefractive index

TroposphereTroposphereProfileProfileCALIPSOCALIPSOAerosol vertical profileAerosol vertical profile

TroposphereTroposphereColumnColumnTOMS, AVHRR, MODIS, TOMS, AVHRR, MODIS, SeaWIFSSeaWIFS, GOME, , GOME, SCIAMACHY, GOES, OMI, SCIAMACHY, GOES, OMI, OMPS, VIIRS, APS, GOESOMPS, VIIRS, APS, GOES--R/ABI, GOESR/ABI, GOES--R/HESR/HES

Aerosol optical depth as Aerosol optical depth as proxy for PM2.5proxy for PM2.5

TroposphereTroposphereColumnColumnMODISMODIS, APS, VIIRS, GOES, APS, VIIRS, GOES--R/ABIR/ABI

Particle typeParticle type

TOMS/SBUV, AIRS, OMI, TOMS/SBUV, AIRS, OMI, TES, TES, OMPS , OMPS , IASI, IASI, CrISCrIS

GOME, OMIGOME, OMI

MOPPIT, AIRS, MOPPIT, AIRS, IASI, IASI, CrISCrISGOESGOES--R/HESR/HES

TOMS, TOVS, AIRS,GOME, TOMS, TOVS, AIRS,GOME, SCIAMACHY, OMI, SCIAMACHY, OMI, OMPS, OMPS, IASI, IASI, CrISCrIS

Current/Current/Future Future Satellite SensorsSatellite Sensors

Troposphere*Troposphere*ProfileProfileOzone (O3)Ozone (O3)

TroposphereTroposphereColumnColumnNitrogen dioxide (NO2)Nitrogen dioxide (NO2)

TroposphereTroposphereColumnColumnCarbon monoxide (CO)Carbon monoxide (CO)

Troposphere/stratosphere Troposphere/stratosphere for volcanic eruptionsfor volcanic eruptions

ColumnColumnSulfur dioxide (SO2)Sulfur dioxide (SO2)

LocationLocationMeasurementMeasurementPollutantPollutant


NCEP has requirements for global analysis and forecast capability of:

Ozone (already in operations)Ozone (already in operations)Aerosols (Volcanic, Dust, Smoke, Aerosols (Volcanic, Dust, Smoke,

Urban/industrial)Urban/industrial)Carbon productsCarbon products

In addition to air quality, and climate applications, these In addition to air quality, and climate applications, these products are important for improving weather forecasts products are important for improving weather forecasts by accounting for these species in by accounting for these species in radiativeradiative transfer transfer calculationscalculations(e.g. direct radiance assimilation of (e.g. direct radiance assimilation of hyperspectralhyperspectralmeasurements, improved SSTs)measurements, improved SSTs)


Infrared SpectrumInfrared Spectrum

Products:Water vapor (soundings, fluxes, winds)

Temperature (sounding, stability)Carbon monoxide concentration (2 Layers) and total CO2 conc.

Methane concentration (total column)Ozone concentration (4 Layers)

Total SO2 concentration (volcanic eruptions)Surface Temperature and emissivity

Clouds (altitude, optical depth, microphysical properties, winds)Aerosol Concentration and Depth


Hyperspectral Dust/Aerosol ModelingHyperspectral Dust/Aerosol Modeling

kCARTA+DISORT, spectral resolution = 0.0025 cm-1

Negative slopeEffect of Dust Particle Sizes Effect of Dust Layer Location

Green – Clear Spectrum

Negative Slope – The Dust Signature

820 920 650 1000

( Sokolik, et al., 2002 - GRL)


10 May 2003 (1554 UT)

Anatahan Volcanoviewed with AIRS

SO2 signal1284-1345 cm-1

Ash signal1228-995 cm-1

Anatahan

10 11 12 13 1

transmission (total)transmission (scattering)transmission (absorption)

00.10.20.30.40.50.60.70.80.9

1

7

trans

miss

ion

9

4 5 Ash

AbsScatTot


Statistics of CO Retrieval Statistics of CO Retrieval from a simulation of a full from a simulation of a full dayday

IASI has most skill in lower troposphere

Background Variability

RMS BIAS


AIRS is Sensitive to CO from Biomass Burning. AIRS is Sensitive to CO from Biomass Burning. Cloud Clearing yield ≈ 70%.Cloud Clearing yield ≈ 70%.

On Sep. 9, 2002: low MODIS fire counts & low AIRS CO was measured.

On Sep. 24, 2002: high MODIS fire counts & high AIRS CO was measured


AIRS

MOPITT

(Wallace McMillan, UMBC


AIRS Global CO Movie(Wallace McMillan, UMBC)

18

Larrabee Strow, UMBC

19


OperationsOperations

Feedback

Observing SystemsModeling Systems

Products & Services

Observing SystemsModeling Systems

Products & Services

CustomersResearch to OperationsResearch to Operations

R&D CommunityResearchResearch


NESDIS Research to NESDIS Research to OperationsOperations

•• At NESDIS, ORA is the research office and At NESDIS, ORA is the research office and OSDPD is operations for satellite products.OSDPD is operations for satellite products.

••ORA is not just research, ORA also develop ORA is not just research, ORA also develop processing systems which are transferred to processing systems which are transferred to OSDPD.OSDPD.

•• We develop our processing systems on parallel We develop our processing systems on parallel machines which minimize the time for machines which minimize the time for operational implementation.operational implementation.


Case Study Case Study -- AIRS (How to get AIRS (How to get NASA products into NESDIS NASA products into NESDIS operations)operations)

•• NESDIS scientists on NASA AIRS science teamsNESDIS scientists on NASA AIRS science teams

••We contributed by providing algorithms and as an advocate for We contributed by providing algorithms and as an advocate for NOAA’sNOAA’suser community. (NCEP, Navy, ECMWF, UKMET)user community. (NCEP, Navy, ECMWF, UKMET)

•• User workshops to discuss data formats.User workshops to discuss data formats.

••One year before the scheduled launch, we started to simulated AIOne year before the scheduled launch, we started to simulated AIRS RS radiances and products in near realradiances and products in near real--time and provide products to NWP time and provide products to NWP communitycommunity

••NWP community worked on their data assimilation infrastructure.NWP community worked on their data assimilation infrastructure.

••AIRS launched in May 2002AIRS launched in May 2002

••AIRS level 1b validated by end of September.AIRS level 1b validated by end of September.

••AIRS radiance products delivered to NWP community in early OctoAIRS radiance products delivered to NWP community in early October.ber.


Case Study Case Study –– Joint Center for Joint Center for Satellite Data AssimilationSatellite Data Assimilation

Define a problem Define a problem ---- need to accelerate the assimilation of satellite need to accelerate the assimilation of satellite data and we need to get ready for the large satellite datasets fdata and we need to get ready for the large satellite datasets from rom EOS and NPOESS.EOS and NPOESS.

Solution Solution –– agencies need to work together and pull resources agencies need to work together and pull resources --ORA, NCEP, OAR, NASA, DODORA, NCEP, OAR, NASA, DOD

Mission:Mission: Accelerate and improve the quantitative use of research Accelerate and improve the quantitative use of research and operational satellite data in weather and climate predictionand operational satellite data in weather and climate predictionmodelsmodels

Vision:Vision: A weather and climate prediction community empowered to A weather and climate prediction community empowered to effectively assimilate increasing amounts of advanced satellite effectively assimilate increasing amounts of advanced satellite observationsobservations

International advisory panel, science steering committee, Board International advisory panel, science steering committee, Board of of Directors …Directors …


Summary Summary –– Successful Successful Research to OperationsResearch to Operations

Success depends on intelligent motivated Success depends on intelligent motivated people with the understanding of the big picture.people with the understanding of the big picture.

Must be supported by upper management by Must be supported by upper management by providing the necessary budget.providing the necessary budget.

Team work is extremely important.Team work is extremely important.

JCSDA JCSDA –– very good example of interagency very good example of interagency collaboration.collaboration.


SummarySummary

Satellite data coupled with routine groundSatellite data coupled with routine ground--based based observations are important for the monitoring observations are important for the monitoring and prediction of air pollution.and prediction of air pollution.

The high temporal frequency of observations The high temporal frequency of observations from geostationary orbit provides from geostationary orbit provides unprecedented tracking of air pollutants.unprecedented tracking of air pollutants.

PolarPolar--orbiters provide six observations per day, orbiters provide six observations per day, with higher refresh rates near the poles.with higher refresh rates near the poles.

Documents

Joint EPA/NASA/NOAA Workshop on Air Quality and …€¢ Challenges: measuring trace gases/aerosols in PBL, tropospheric profiles, cloud screening – Exploit instrument synergy: multi-sensor