J. Ogren 04/22/23

The WMO/GAW Integrated Global Aerosol Observing

and Analysis System

John A. OgrenEarth System Research Laboratory

National Oceanic and Atmospheric AdministrationBoulder, CO, USA

(with a lot of help from Len Barrie and Urs Baltensperger)

J. Ogren 04/22/23

OBJECTIVE

Improve climate and air quality assessments and predictions

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Approach: GAW Strategic Plan

• Develop a three-dimensional global atmospheric chemistry measurement network

• Develop coherent data processing chains• Implement near-real-time delivery of a few

measured parameters• Assimilate data into models• http://www.wmo.int/pages/prog/arep/gaw/

documents/gaw172-26sept07.pdf

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Components of Integrated System

• In-situ observations– Surface sites, ships, aircraft, balloons

• Remote sensing observations– Ground-based and satellite– Active and passive

• Models– Weather forecasting– Climate forcing predictions– Air quality

• Synthesis Products

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Model Calculation of Aerosol Optical Depth

aerosol processstudies

CHEMICALTRANSPORT

MODEL

spatial fields ofaerosol chemical

and physicalproperties

AEROSOLOPTICAL MODEL

(e.g., Miescattering)

spatial fields ofaerosol radiativeproperties (e.g.,optical depth)

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Model Assimilation of Satellite Observations

aerosol processstudies

CHEMICALTRANSPORT

MODEL

spatial fields ofaerosol chemical

and physicalproperties

satellite obs. of 3Ddist. of upwelling

radiances

AEROSOLOPTICAL MODEL

(e.g., Miescattering)

spatial fields ofaerosol radiativeproperties (e.g.,optical depth)

RADIATIVETRANSFER

MODEL

spatial fields ofaerosol forcing

GLOBALCLIMATEMODEL

climate responseto aerosol forcing

3DASSIMILATIONALGORITHM

modelled 3D dist.of upwellingradiances

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Integrated Approach to Evaluationof Aerosol Radiative Forcing

aerosol processstudies

CHEMICALTRANSPORT

MODEL

spatial fields ofaerosol chemical

and physicalproperties

satellite obs. of 3Ddist. of upwelling

radiances

measured aerosoloptical properties(e.g., refractive

index)

AEROSOLOPTICAL MODEL

(e.g., Miescattering)

spatial fields ofaerosol radiativeproperties (e.g.,optical depth)

measured aerosolradiative propertes

(e.g., single-scatterng albedo)

RADIATIVETRANSFER

MODEL

spatial fields ofaerosol forcing

radiative fluxeslinked to aerosolcolumn burdens

GLOBALCLIMATEMODEL

climate responseto aerosol forcing

CLOSURE

3DASSIMILATIONALGORITHM

modelled 3D dist.of upwellingradiances

measured aerosolchemical and

physical properties

CLOSURE CLOSURECLOSURE

Observations:All Sources

Global ProductsWorld Integrated

Data Network:e.g. WDC-Ispra

Sat. Centres (WDC-RSAT)AERONET, etc

Assimilation of Real-Time Data

By Forecast Models

(e.g. GEMS; WMO SDS-WAS)

GAW Calibration &

Quality Assurance

(GAWNET PFRs)

Data Uses/Applications1. Public Air Quality Warnings2. Public SDS Warnings3. Public Aerosol Bulletins4. Surface and air transport5. Scientific Assessments (IPCC,

Ozone, etc)6. Improved Weather Forecasts

Aircraft: MOZAIC/IAGOS

Surface-based: Remote sensingIn situ: PM & optical In situ: Chemistry

Satellite:MODIS, CALYPSO, GEOs

WMO Real-Time Data Distribution:WMO Information System (WIS)

Leaders: WMO/GAW & Satellite Orgs & ENV OrgsLeaders: WMO/GAW & Satellite Orgs & ENV Orgs

Reanalysis

IGACO-Aerosols

http://www.wmo.ch/pages/prog/arep/gaw/documents/gaw159.pdf

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GAW Aerosol Network Status• Many undersampled

regions• Many sampling sites not

in GAW network database

• Contributing partners needed!– Optical depth– Lidar– In-situ

• http://www.wmo.int/gaw/gawsis/

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GAWSIS Database is Incomplete

• Users will miss a lot if they only use GAWSIS

• Users today need to know who to ask to get more complete information on available data

USA IMPROVE net

China Atmos. Watch Network

Source: Zhang Xiao-Ye

GAW Aerosol Networks

• Aerosol optical depth– wait for Stefan Kinne's talk

• Vertical profiles– GALION (this workshop)

• In-situ– coming next...

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GAW In-situ Aerosol Network• Core, continuous measurements

– Mass concentration in two size fractions – Major chemical components in two size fractions – Light absorption coefficient – Light scattering coefficient at various wavelengths

• Other recommended measurements– Hemispheric backscattering coefficient at various

wavelengths – Aerosol number concentration – Cloud condensation nuclei at 0.5% supersaturation – Aerosol size distribution – Detailed size fractionated chemical composition – Dependence on relative humidity – CCN spectra (various supersaturations)

• http://www.wmo.ch/pages/prog/arep/gaw/documents/gaw153.pdf

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LegendNOAAaffiliatefuture sites

NOAA-federated Long-term Aerosol NetworkALT

SPO

SMO

MLO

BRW

BNDSGP

THD

CPT

WLG

CSJ

TIKSUM

LUL

KPOSPL

WHIBRM

EGBAMY

http://www.esrl.noaa.gov/gmd/aero/

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Ext

inct

ion

(Mm

-1)

Sin

gle

scat

terin

g al

bedo

Variations in Aerosol Amount and Type

AMOUNT

TYPE

A rich data set for evaluating chemical transport models

1 Mm-1 =1 mm2 m-3,extinction cross-section per cubic meter of air

Percentiles957550255

log

sca

le!

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US-GCOS Funds Placed in Trust to WMO GAW Used to Upgrade Aerosol Optical Measurements at Cape

Point and Mt. Waliguan.

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Installation at Mt. Waliguan, China

NASA A-Train

CALIPSO Aerosol Lidar GAW/AERONET Aerosol Remote Sensing Stations

18 UTC, 7 May 2002 30-hr forecast

Forecast

Integrated Products: Observations + Models

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Operational Research Dust Forecasting Centers

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Forecast of AOD with Data Assimilation

• Global and regional Earth-system (Atmosphere) Monitoring using Satellite and in-situ data (GEMS)

• MODIS AOD product assimilated with global CTM• http://gems.ecmwf.int/d/products/aer/realtime/

optical_depth_da/

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Challenges for Networks

• Increased coordination within each type of network– measured parameters– sampling protocols, QA/QC, data processing– find partners in undersampled regions

• Provide information on measurements to a common database– e.g., GAWSIS– need to keep information up-to-date

• Provide data in a common format to users– not necessary to have a common data center

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Challenges for Integration

• Enhanced interaction of the data generation and assimilation/modelling communities

• Coordination among different types of measurements

• Development of re-analysis products for combining different types of measurements– surface-based in-situ– surface-based remote sensing– satellite-based remote sensing– radiation budget