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AeroCom. … in the context of GEMS S. Kinne. Overview. what is AeroCom ? Goals what does AeroCom do ? Activites how does GEMS benefit from AeroCom? Initialization Evaluation. what is AeroCom ?. AeroCom “ Com parisons of Aero sol simulations to DATA ”

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Aerocom

AeroCom

… in the context of GEMS

S. Kinne


Overview
Overview

  • what is AeroCom ?

    • Goals

  • what does AeroCom do ?

    • Activites

  • how does GEMS benefit from AeroCom?

    • Initialization

    • Evaluation


  • What is aerocom
    what is AeroCom ?

    • AeroCom

      “Comparisons of Aerosol simulations to DATA”

      • co-organized by LSCE and MPI-Met

        • not officially funded (major problem)

        • supported by global aerosol modeling worldwide

  • AeroCom Goals

    • document module differences

    • investigate sub-step and sub-processes

    • assemble useful (quality!) data-sets

    • intensify links between groups (model, data)


  • Aerocom activities 1
    AeroCom - Activities (1)

    • organize regular workshops

      • Paris 6/03, Ispra 3/04, N.York 12/04, Oslo 6/05

  • maintain a website http://nansen.ipsl.jussieu.fr/AEROCOM

    • Information

      • conference summaries / papers

    • Protocol

      • data-format / data-request (Experiments) / input

    • Interactive diagnosis tool

      • Evaluations (Model vs Data)

      • Diversity / Outliers (Model vs Model)


  • Http nansen ipsl jussieu fr aerocom data surfobs html
    http://nansen.ipsl.jussieu.fr/AEROCOM/DATA/surfobs.html

    local network

    comparisons

    time-series

    selection

    menu

    SO4

    aot

    distribution-plots

    scatter-

    plots


    Aerocom activities 2
    AeroCom - Activities (2)

    • define common ‘Experiments’

      • A: ‘best as you can’ – simulation

      • B: year 2000 with prescribed 2000 emissions*

      • C: year 2000 with prescribed 1750 emissions* B minus C: address anthropogenic ‘forcing’

      • INDI: sensitivity studies for indirect effects

        * ftp://ftp.ei.jrc.it/pub/Aerocom/

  • prepare useful data-sets (for data-base)

    • Evaluate – beyond downloading (satellite combo)

    • Combine/ Process – for added value (AERONET)


  • Aot sat retrievals vs aeronet
    aot – sat. retrievals vs.AERONET

    sat - Anet

    R = --------------

    Anet

    …but can

    local data

    expanded

    in regions

    as here ?


    Aerocom questions
    AeroCom - Questions

    MODELING

    • are component modules consistent ?

      • where is model diversity largest ?

      • what do prescribed scenarios reveal?

        DATA

  • are there data to determine skill ?

    • are (operational, global) data available ?

    • are data (sufficiently) accurate?

    • can data correlations provide clues?

    • are data applicable to scales in modeling?


  • Aerocom participants
    AeroCom - Participants

    LO LOA 3.8/2.5 yr 2000 Reddy / Boucher

    LS LSCE 3.8/2.5 yr 2000 Schulz / Balkanski

    UL ULAQ 22.5/10 yr 2000 Pitari / Montenaro

    SP SPRINTARS 1.1/1.1 yr 2000 Takemura

    CT CANADA 2.8/2.8 yr 2000 Gong

    MIMIRAGE 2.5/2.0 1yr avg Ghan / Easter

    EHECHAM5 HAM 1.8/1.8 3yr avg Stier / Feichter

    NF NCAR MATCH 1.9/1.9 yr 2000 Fillmore / Collins

    OC OSLO-CTM 2.8/2.8 yr 1996 Myhre / Isaksen

    OG OSLO-GCM 2.8/2.8 3yr avg Iversen et al.

    IM IMPACT 2.5/2.0 yr 2000 Liu / Penner

    GM GFDL MOZART 2.5/2.0 yr 2000 Ginoux / Horowitz

    GO GOCART 2.0/2.5 yr 2000 Chin / Diehl

    GI GISS 4.0/5.0 yr 2000 Koch / Bauer

    TM TM5 4.0/6.0 yr 2000 Krol / Dentener

    EM ECHAM4 MADE 3.8/3.8 10yr avg Lauer / Hendricks

    GR GRANTOUR 5.0/5.0 1yr avg Herzog / Penner

    NM NCAR MOZART 1.9/1.9 1yr avg Tie / Brasseur

    NC NCAR CAM 2.8/2.8 1yr avg Mahonwald

    ELECHAM4 3.8/3.8 3yr avg Lohmann / Feichter

    all models separate by aerosol species (SU,BC,OC,DU,SS)


    First results model diversity
    first results – model diversity

    • differences in mass-fields are dominated by differences in aerosol processing

      • year-to year variations are much smaller

      • impact of ‘streamlined’ emissions is minor

  • differences among individual components (SU,BC,OC,DU,SS) are larger than for their sum

    • data constraint usually only for (sum-) totals

    • comp-mix diversity means absorption diversity

  • large differences in aerosol water

    • module (humidification) or GCM (envir) related?


  • model diversity of emission and mass

    emission

    emission

    Exp A

    Exp B

    mass

    mass

    Exp A

    Exp B


    Diversity in aot simulations
    diversity – in aot simulations

    total aot diversity < aot sub-component diversity !

    total

    aot

    OC

    aot

    SS

    aot

    SU

    aot

    BC

    aot

    DU

    aot


    First results data
    first results - data

    • BAD data: an assimilator’s / evaluator’s nightmare

      • do not trust given error estimates

      • compare with quality references

  • data of global data-sets are not globally of equal accuracy

    • focus on regional strength, establish composites

    • a local samples can differ from its regional value

  • correlation can provide clues with the immediate need for absolute accuracy

    • aerosol and other atmospheric properties


  • A case for s the retrieval composite
    a case for S* (the retrieval composite)

    composite a

    still no

    global

    cover!


    Aerocom and gems
    AeroCom – and GEMS

    INITIALIZATION

    • provide datasets on aerosol

      • data from ground-based networks

        • AERONET, EARLINET, EMEP, IMPROVE

      • data derived from space sensors

        • satellite data and retrieval composites

  • provide reference from modeling

    • global and complete data-sets from the AeroCom model median

  • collaborate on aerosol emissions


  • Climatology aot w 0 angstrom
    climatology - aot / w0 / Angstrom


    Aerocom and gems1
    AeroCom – and GEMS

    • EVALUATION

    • build on AeroCom evaluation web tools

      • diganostics and scores (e.g Taylor plots)

  • provide a reference from global modeling

    • statistics on simulated fields (average, diversity)

  • provide (independent) data for evaluation

    • quality data not used in assimilations


  • Aerocom and gems2
    AeroCom and GEMS

    • both activities are complementary !

      • AeroCom dignostic tools will provide immediate feedback on simulation performance (score ?)

      • GEMS can build on AeroCom efforts to establish global quality data on aerosol

      • GEMS can build on the AeroCom effort to harmonize and update aerosol emissions

      • GEMS is expected to accelerate access to new quality data-sets for AeroCom model evalutions


    Aerocom current data base
    AeroCom - current ‘data’ base

    • Remote sensing – space

      • satellites (Modis, Misr, Toms, Avhrr, Polder …)

        • aot (individual + composite best), Angstrom

        • aot associated atmos properties (clouds)

  • Remote sensing – ground

    • AERONET (sun/sky-photometers)

      • aot, size-dist., (ssa), Angstrom

    • EARLINET (lidar)

      • vertical profile, extinction

  • In-situ ground data

    • IMPROVE

      • SU, OC, BC, extinction

    • EMEP

      • SU, PM (?)

  • data priority

    for year 2000


    General questions to gems
    General Questions to GEMS

    • what are the priorities / GEMS needs ?

      …relating to AeroCom activities I can think of

      • data aquization

      • data assessment

      • data integration

      • comparisons to other modeling efforts

      • evaluating and scoring

  • who is going to do it / what ?

    • extra techn. (wo)man-power for AeroCom?

    • many GEMS participants are ready to contribute with little pieces of the puzzles. Who integrates?



  • Up scaling of local aot
    up-scaling- of local ‘aot’

    with satellite data !

    a

    50% larger than the regional value level

    at GSFC:

    local aots are

    ca. 20% above

    regional mean

    50% smaller than the regional value level


    Data correlations aerosol cloud
    data correlationsaerosol - cloud

    do higher cloud tops offset solar albedo losses?

    key

    a – aot

    A – aot (<1mm)

    t – cld top T

    L – lwc (T> 260K)

    x(y) – x function of y

    what process: aerosol acloud? or cloud aaerosol?


    Model diversity
    model-diversity

    a- aot -S sulfate ab absorption aot

    m- dry mass -O part.o matter w0 ss-albedo

    r- mee (=a/m)-B black carbon cr bc/oc ratio

    -N seasalt -f frac of sizes <1 mm

    -D dust An Angstrom param.

    max / min factors of central 66% of aer.modules

    despite better

    agreement for

    annual global aot …

    large diversity in

    modeling remains

    June 2002

    June 2004


    Clima tology

    aot

    ssa

    clima-tology

    with medians

    aot

    model satellite


    Aeronet cape verde aot 3 5 2004
    AERONET Cape Verde aot 3/5/2004