aerosol-cci: wp2220: cloud mask comparison gerrit de leeuw
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Aerosol-cci:WP2220: Cloud mask comparison
Gerrit de Leeuw
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 2
Phase 1
?
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 3
2000 Algorithm evolution FMI
2110 General algorithm work FMI DLR, UOx, RAL, SU, BIRA, ULB, LMD
2120 Cloud mask comparison (in parts coordinated with several CCI / Glob projects)
FMI DLR, UBre, RAL, SU, BIRA, ULB, LMD
2210 Individual algorithm evolution ATSR FMI DLR, UOx, SU, RAL
2220 Individual algorithm evolution GOMOS BIRA
2230 Individual algorithm evolution SYNAER DLR
2240 Individual algorithm evolution IASI DLR BIRA, ULB, LMD
2300 Sentinel preparations SU FMI, UOx, KNMI, RAL
2400 Aerosol type information DLR FMI, SU, UOx, KNMI, BIRA, ULB, RAL, LMD
2500 Uncertainties UOx DLR, FMI, SU, BIRA, ULB, LMD
2600 Consistency coordinated with several ECVs NILU
2700 Joint aerosol cloud retrieval coordinated with Cloud_cci UOx
WP2000
2000 Algorithms
2110 General algorithm work
2120 Cloud mask comparison
2210 Evolution - ATSR
2220 Evolution - GOMOS
2230 Evolution - SYNAER
2240 Evolution - IASI
2300 Sentinel
2400 Aerosol type
2500 Uncertainties
2600 Consistency
2700 Joint retrieval
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 4
Specific algorithm work: Cloud mask working group (2120; FMI) Surface treatment working group (2110; DLR)) Aerosol properties working group (chemical, physical >
optical) (2400; UOx) Uncertainty characterization working group (2500; Uox) Consistency – other ecv’s(2600; NILU) Joint aerosol/cloud retrieval (2700; Uox) Individual algorithm work:
ATSR (2210; FMI) GOMOS (2220; BIRA) SYNAER (2230; DLR) IASI (2240; DLR) Sentinels (2300; SU)
WP2000 Activities
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 5
•Cloud working group• cloud masking comparison and optimization between 4 ATSR and AVHRR/3 algorithms• -> reference for sensors with lower resolution or smaller spectral coverage
•Aerosol-cc & cloud-cci: consistency•
Cloud activities Phase 1
Cloud masking• compare different cloud masks
• various AATSR algorithms / AATSR versus MERIS / versus PARASOL
• transfer to larger spectrometer pixels
• prepare common cloud mask for selected inter-comparison
• compare to external reference datasets (SYNOP, MODIS/CALIPSO)
01 Sep, 2008AATSR operational
Cloud detection
Single scene analysis
Cloud mask analysis
Technical Note: Cloud Masking in Aerosol_CCIV1.0
Aerosol_CCI, 28 April 2011
Authors:Lars Klüser, Alexander Kokhanovsky, Caroline Poulsen and Larisa Sogacheva
Recommendations
Cloud mask group recommendations•APOLLO common cloud mask for AATSR RR
•Compromise between cloud masking and leaving enough pixels for aerosol retrieval•Conservative safety zone near cloud edges (5 pixels
•Too limited for MERIS (coverage)•No common MERIS cloud flag•MERIS cloud detection not reliable
•AATSR not transferable to PARASOL or OMI (A-train)
Table 1 Common cloud mask entries and their meanings0 cloud free ocean1 cloud free land2 sunglint area3 dust flag4 twilight zone5 cloud
12,4 % 21,1 % 0,5 % 66,0 %
Cloud mask consistencyAerosol_cci / Cloud_cci
5 selected days Sep 2008 – safety zone excluded by Aerosol_cci
Cloud mask consistency: Conclusions• Given the goal of assuring consistency between the outcome of Aerosol_cci
and Cloud_cci in terms of cloud masks, the overall numbers state only 0.3% inconsistency and 21.6% discarded pixels. Consequently the AATSR products from Aerosol_cci and Cloud_cci are consistent to a very high degree and can be used simultaneously in any climate applications. Moreover the analysis revealed the robustness of the consistency with respect to the cloud detection used, if an appropriate safety zone around surely cloudy pixels is applied in the aerosol retrieval.
• • It should be noted that this analysis for consistency does not at all involve any
external reference data to identify the truth. It is therefore also possible, that within those classes, which are consistent between both cloud and aerosol cloud masks important parts of the global aerosol or cloud distribution are hidden / miss-interpreted, which would influence global / and even more regional mean values of aerosol and cloud properties.
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 12
•Phase 1 progress
•Quality•Coverage•Cloud detection•Features•Uncertainties
FMI: ATSR Phase 2:•Quality:
•Use validation results for ’weaker’ areas•Improved cloud screening•Aerosol properties?
•Coverage: •bright surfaces: desert, snow/ice•Toward poles?
•Uncertainties: •Common definition and interpretation
•Discrimination clouds/high AOD:•Desert dust•Pollution•Forest fires
•Ångström Exponent•Contribute to applications
?
iLEAPS OSC 2011, Garmisch-Partenkirchen, 19-23 September, 2011
Fires in Russia August 2010
AATSR Dual View algorithm ADV & SACURA: aerosol & cloud properties
AOD COT Reff
LWP albedo CTH
AOD
COT
AOD
AOD
Reff
LWPLeft: AATSR maps run w separate cloud
and aerosol retrievalRight: transects with and w/o cloud mask:
continuous in transition zone
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 15
•Contribute to and work with Glob Temperature RR•Common approach and tools?
•Aerosol-cci specific activities (TBD with GT)•GT: ATSR only?•Other instruments: UV/VIS/IR vs VIS/IR
•MERIS, POLDER
•Heperspectral: IASI•GT over land: we also need ocean!•High AOD (desert dust, forest fire, industrial aerosol)•Postprocessing?•New instruments: SLSTR, OLCI
•Time schedule?
FMI: cloud working group
Aerosol-cci Phase 2 KO, Oxford, 20-21 May 2014 16
•ENVISAT lost 4/2012: no AATSR and MERIS data•Sentinel-3 launch window: summer 2015: commisioning and data available?•3-4 years lost!•Which other satellites can fill that gap:
•MODIS?•MISR?•PARASOL (until 12/2013)•NPP?•AVHRR?
•Considerations and criteria?
FMI: ENVISAT gap filling