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AeroCom

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

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  1. AeroCom … in the context of GEMS S. Kinne

  2. Overview • what is AeroCom ? • Goals • what does AeroCom do ? • Activites • how does GEMS benefit from AeroCom? • Initialization • Evaluation

  3. 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)

  4. 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)

  5. http://nansen.ipsl.jussieu.fr/AEROCOM/DATA/surfobs.html local network comparisons time-series selection menu SO4 aot distribution-plots scatter- plots

  6. 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)

  7. aot – sat. retrievals vs.AERONET sat - Anet R = -------------- Anet …but can local data expanded in regions as here ?

  8. 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?

  9. 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)

  10. 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?

  11. model diversity of emission and mass emission emission Exp A Exp B mass mass Exp A Exp B

  12. diversity – in aot simulations total aot diversity < aot sub-component diversity ! total aot OC aot SS aot SU aot BC aot DU aot

  13. 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

  14. a case for S* (the retrieval composite) composite a still no global cover!

  15. 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

  16. climatology - aot / w0 / Angstrom

  17. 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

  18. 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

  19. 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

  20. 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?

  21. extras

  22. 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

  23. 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?

  24. 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

  25. aot ssa clima-tology with medians aot model satellite

  26. AERONET Cape Verde aot 3/5/2004

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