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Using Satellite Data to Improve Operational Using Satellite Data to Improve Operational Atmospheric Constituents Forecasting Atmospheric Constituents Forecasting

CapabilitiesCapabilities

Shobha KondraguntaShobha Kondragunta,, NOAA/NESDIS/STARNOAA/NESDIS/STARXiaoyang Zhang, UMD - CICS @ NOAA/NESDIS/STARXiaoyang Zhang, UMD - CICS @ NOAA/NESDIS/STAR

Arlindo da Silva, NASA Goddard Space Flight CenterArlindo da Silva, NASA Goddard Space Flight CenterSarah Lu, Sarah Lu, IMSG @ NOAA/NWS/NCEPIMSG @ NOAA/NWS/NCEP

Hyun Cheol Kim, NOAA/ARLHyun Cheol Kim, NOAA/ARL

Project OverviewProject Overview

Joint NASA/GMAO, NESDIS/STAR, and NWS/NCEP project to:Joint NASA/GMAO, NESDIS/STAR, and NWS/NCEP project to:» Develop near real time biomass burning emissions product covering Develop near real time biomass burning emissions product covering

the whole globe from polar and geostationary satellites for NEMS-the whole globe from polar and geostationary satellites for NEMS-GFS-GOCARTGFS-GOCART

– Globally, biomass burning is one of the primary sources of Globally, biomass burning is one of the primary sources of aerosols; burning varies seasonally, geographically and is either aerosols; burning varies seasonally, geographically and is either natural (e.g., forest fires induced by lightning) or human induced natural (e.g., forest fires induced by lightning) or human induced (e.g., agricultural burning for land clearing). Satellites can provide (e.g., agricultural burning for land clearing). Satellites can provide this information on a real time basis. this information on a real time basis.

» Develop and deploy a global aerosol prediction system that can in the Develop and deploy a global aerosol prediction system that can in the future assimilate satellite-derived atmospheric composition parametersfuture assimilate satellite-derived atmospheric composition parameters

Meet Research (NASA) to Operations (NOAA) goals of the JCSDA Meet Research (NASA) to Operations (NOAA) goals of the JCSDA

» QFED code transition from NASA to NOAAQFED code transition from NASA to NOAA

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Blended Polar and Geo Blended Polar and Geo BBEP FlowchartBBEP Flowchart

Terra+Aqua MODIS fire detections

QFEDv2

Blended global biomass burning emission

Simulating AOD using NEMS-GFS-GOCART

Geostationary satellite fire detections

MODIS fire FRP with cloud adjustment

MODIS fire emissions

MODIS AOD

Calibrating Fire emissions

Scaling MODIS fire emissions

Simulating diurnal FRP

Fire emissions

Scaling fire emissions

GBBEP-GeoQFED: Quick Fire Emission Dataset from MODIS fire data

GBBEP-Geo: Global Biomass Burning Emissions Product from Multiple Geostationary Satellites

FRP Datasets from MODIS and FRP Datasets from MODIS and Geostationary Satellites Geostationary Satellites

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Satellite/Sensor Algorithm Version

Spatial Resolution

Temporal Resolution

Terra/MODIS & Aqua/MODIS

Collection 5 1 km Daily (4 times)

GOES-E and -W

V65 4 km nadir 30 min

Metosat-9 SEVIRI

V65 3 km 15 min

MTSAT Imager V65 4 km 30 min

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Biomass Burning Emission Biomass Burning Emission Derived from Fire Radiative Derived from Fire Radiative

Power Power

Fire Radiative Power (FRP)Fire Radiative Power (FRP)

FRP can also be empirically derived from 3.9 um radianceFRP can also be empirically derived from 3.9 um radiance

Fire Radiative EnergyFire Radiative Energy

Biomass combustedBiomass combusted

EmissionsEmissions

MIRbkLMIRhLa

sampAFRP ,,

FRP = AσT4

dtFRPFREt

t2

1

BC = FRE*β

E = BC*EF

σ -- 5.67x10-8 Js-1K-4

A – area brunedT – fire temperature-- 0.368±0.015 kg/MJ Lh – radiance at 3.9 umLbk – background radianceEF – emissions factorsa -- constant

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Scaling factors determined by comparing model simulated AOD with observed MODIS AOD

CEterra=a1Eterra

CEaqua=a2Eaqua

CEgoes_E=a3Egoes_E

CEgoes_w=a4Egoes_W

CEmetosat=a5Emetosat

CEmtsat=a6Emtsat

Calibration of Multiple Calibration of Multiple Satellite-based Fire Satellite-based Fire

Emissions Emissions

CE represents scaled emissions and E is satellite-dependent fire emissions. Parameters a1-a6 are scaling factors calculated by comparing year-long model-simulated AOD and MODIS AOD

NASA Quick Fire NASA Quick Fire Emission Dataset (QFED)Emission Dataset (QFED)

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QFEDv2—Calculated from MODIS FRP for various biome types and tuned using scaling factors which are obtained by comparing GFS-GOCART-modeled AOD with MODIS observed AOD.Emissions are tuned respectively for Terra MODIS and Aqua MODIS, which are then combined to produce daily global emissions.

Final QFED product at 0.25x0.3125 degree is merged from Terra and Aqua daily fire emissions of BC, OC, SO2, CO, CO2, PM2.5

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GBBEP-Geo: Simulating GBBEP-Geo: Simulating Diurnal FRP from Diurnal FRP from

Geostationary SatellitesGeostationary Satellites

Averaged from DOY 257-305, 2009

GOES-E and GOES-W

METEOSAT MTSAT

Diurnal FRP patterns are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems

Climatological diurnal patterns of GOES FRP

GBBEP-Geo: Global Biomass GBBEP-Geo: Global Biomass Burning Emissions Product from Burning Emissions Product from Multiple Geostationary SatellitesMultiple Geostationary Satellites

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Hourly fire emissions for CO, OC, BC, CO2, SO2, PM2.5Limited coverage in high latitudes and no coverage in most regions across India and parts of boreal Asia

No spatial coverage

MODIS AOD for MODIS AOD for Comparison with Comparison with

Modeled AODModeled AOD

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Spatial patterns of MODIS AOD and Hazard Mapping System (HMS) fire hot spots.

Calibration of Simulated Calibration of Simulated FRP between GOES-E and FRP between GOES-E and

GOES-WGOES-W

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Estimating satellite-scaling factor between GOES-E and GOES-W

Calibration of GBBEP-geo Calibration of GBBEP-geo with Scaled QFEDv2with Scaled QFEDv2

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GBBEP-geo can be calibrated to be equivalent to QFEDv2 to generate global blended fire emissions because the QFEDv2 has been scaled using MODIS AOD.

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• Model Configuration: Forecast model: Global Forecast System (GFS) based

on NOAA Environmental Modeling System (NEMS), NEMS-GFS

Aerosol model: NASA Goddard Chemistry Aerosol Radiation and Transport Model, GOCART

• Phased Implementation: Dust-only guidance is established in Q4FY12 Full-package aerosol forecast after real-time global

smoke emissions are available and tested (JSDI project)

• NRT Dust Forecasts 5-day dust forecast once per day (at 00Z), output

every 3 hour, at T126 L64 resolution ICs: Aerosols from previous day forecast and

meteorology from operational GDAS GRIB2 products in 1x1 degree: 3-d distribution of

dust aerosols (5 bins from 0.1 – 10 µm) and 2-d aerosol diagnosis fields (e.g., aerosol optical depth, surface mass concentration)

Operational since Sept 2012

NEMS GFS Aerosol Component (NGAC)NCEP’s global interactive atmosphere-aerosol

forecast system

Acknowledge: Development and operational implementation of NGAC represents a successful “research to operations” project sponsored by NASA Applied Science Program, JCSDA and NWS

NGAC experiments using smoke emissions from GFEDv2, QFEDv2, and GBBEP-Geo

for 2011

Seasonal variations: Surface mass concentration for dust aerosols (top) and carbonaceous aerosols using QFED2 (bottom) for different season (July on the left and March on the right).The model is still running for GBBEP-Geo results.

NGAC experiments using smoke emissions from GFEDv2, QFEDv2, and GBBEP for

2011 Biomass Burning: QFED V2 versus GFED (global map on the left and regional map over Africa on the right) and time series of OC/BC surface concentration over Africa (black for QFED2 and green for GFED)

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Summary and Ongoing Summary and Ongoing WorkWork

• NGAC model run with QFED2 emissions for 2011 completed• Model output will be compared to MODIS AOD to determine

scaling factors• NGAC model run with GBBEP-Geo emissions for 2011 is currently

ongoing • QFED code successfully implemented on STAR computers.• Other approaches to determine scaling factors (inter-satellite

calibration) will be used to minimize the model simulations needed.• Product validation is critical. Direct validation is currently not possible

because of the lack of reliable in-situ measurements. We will work on inter-comparison with other biomass burning emission products.

• Algorithm Critical Design Review (CDR) to be held in May 2013