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Aerosol_cci ECV Major improvements over precursor AOD datasets Regional scoring differences between both versions (scoring grows with increased spatial + temporal ... – PowerPoint PPT presentation

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1
Aerosol_cci ECV
2
Major improvements over precursor AOD datasets
Regional scoring differences between both
versions (scoring grows with increased spatial
temporal correlations and decreased bias based
on daily data)
Precursor dataset 2008 Aerosol Optical Depth
maps Aerosol_cci final dataset
3
First ever high level AOD time series from AATSR
ENVISAT-AATSR (CCI)
(150 stations)
no significant global trend (agrees with other
datasets)
Terra-MODIS (NASA)equivalent evaluation
4
Stability RMS
5
Pixel level uncertainties
6
Cloud mask consistency Aerosol_cci / Cloud_cci
5 selected days Sep 2008 safety zone included
by Aerosol_cci
12,4 21,1 0,5
66,0
7
Science-driven system
8
MACC-II assimilation test
  • A test to assimilate Aerosol CCI products into
    the ECMWF IFS model was already conducted 1 month

No assim R0.623
AATSR assim Only R0.741
Modis assim Only R0.755
AATSR MODIS assim Both bias corrected R0.769
9
Major improvements
  • Significant algorithm improvement towards GCOS
    requirements
  • Aerosol optical depth (AATSR over ocean also
    MERIS)
  • AOD uncertainty improved from 0.18
    (GlobAerosol) to 0.09
  • Stratospheric extinction (GOMOS)
  • Extinction uncertainty improved from 25
    (AERGOM) to 10-25
  • Several pathfinder products demonstrated for
    phase 2
  • AATSR time series 7/2002 4/2012 consistent with
    AERONET
  • Improved product content and auxiliary
    information
  • Individual pixel-level uncertainties in products
  • Consistency with Cloud_cci
  • Model simulator for absorbing aerosol index
  • International Satellite Aerosol Science Network
    http//aero-sat.org initiated

10
User assessmentphase 1 achievements
  • basic algorithm development (for AOD
    Angstrom)
  • review a-priori assumptions
  • aerosol type (help from global modeling)
  • surface albedo
  • cloud-screening
  • round robin among competing teams
  • long-term processing with best ATSR retrieval
  • supplementary products
  • stratospheric aerosol (minor contribution, less
    variable)
  • aerosol absorbing index (only qualitative)

11
ATSR vs MODIS
overall score
spatial sub-score
bias sub-score
temp. sub-score
ATSR has still catching up to MODIS
12
ATSR vs MODIS
AOD gt 0.2
overall score
spatial sub-score
bias sub-score
temp. sub-score
but does not even
get close to MODIS
13
User assessment summary
  • major advancements in the first three years in
    improving ATSR aerosol retrievals of AOD
  • significant improvements were achieved in terms
    of bias, spatial correlation and temporal
    correlation yielding in a better overall score
  • the most recent ATSR retrieval version has still
    to catch up to MODIS in most regions / high AOD
  • pixel uncertainty detail (CCI aerosol requirem.)
    is unique but still needs refinement
  • aside from accuracy also spatial coverage matters
    ... with MERIS more competitive here.
  • total AOD is not enough
  • separate AOD in coarse and fine-mode contribution
  • quantitative info on absorption (AAOD) would be
    nice
  • produce long-term data records for all products

14
Phase 1 products
focus on the best ATSR product
  • tropospheric
  • AOD (amount)
  • Angstrom (size)
  • with local errors

ATSR-2 SU
AATSR SU
3 ATSR
3 MERIS
  • absorbing
  • aerosol index
  • (qualitative)

OMI
  • stratospheric
  • extinction/AOD
  • effective radius

GOMOS
1985
1995
2005
2015
2008
15
Phase 2 plans
AOD Angstrom fine-mode AOD aerosol type
ATSR-2
AATSR (3 algorithms)
SCIAMACHY/AATSR
more reference AOD (3 selected. regions)
POLDER
IASI
dust AOD
GOMOS
stratospheric ext (?AOD)
absorbing aerosol index (use in case study)
TOMS / GOME / SCIAMACHY / GOME-2 / OMI
1985
1995
2005
2015
2008
16
Continued from P1
  • Extend Climate Research group (stratosphere,
    aerosol cloud interaction data assimialtion
    through CMUG GoeMIP indirect)
  • Valdiation tools and concepts (add assessing
    stability and aerosol type)
  • Round robin exercises where appropriate (IASI,
    several options)
  • Consistency analysis (extended, with other ECV
    projects)
  • Uncertainties (harmonized, with metrologists, new
    WG)
  • WGs clouds (extend with international
    inter-comparison exercise, surface, components

17
New in P2
  • Long time series production
  • Fill mission time series for all datasets
  • Add IASI
  • POLDER reference sites
  • User case studies
  • Sustainable but distributed system
  • System engineering working group
  • Common standards and tools (e.g. Versioning)
  • Obs4MIPS
  • More
  • Sentinel perparation
  • Joint aerosol-cloud retrieval

18
New in P2 case studies
simulated regional aerosol direct radiative
forcing (Kinne et al., 2013)
EMAC moldel radiative forcing of stratospheric
aerosol (Brühl et al., 2012/3
AAI record for West-Africa (Tilstra et al.,
2011). Red GOME-1, Brown SCIAMACHY blue GOME-2A
Changes in liquid water path due to anthropogenic
aerosol (ECHAM6-HAM2 Lohmann, et al. 2010)
19
Consistency analysis
20
WP plan
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