1. Aerosol-cci: WP2220: Cloud mask comparison Gerrit de Leeuw

2. Aerosol-cci Phase 2 KO, Oxford, 20-21 May 20142 Phase 1 ?

3. 2000Algorithm evolutionFMI 2110 General algorithm work FMIDLR, UOx, RAL, SU, BIRA, ULB, LMD 2120 Cloud mask comparison (in parts coordinated with several CCI / Glob projects) FMIDLR, UBre, RAL, SU, BIRA, ULB, LMD 2210 Individual algorithm evolution ATSR FMIDLR, UOx, SU, RAL 2220 Individual algorithm evolution GOMOS BIRA 2230 Individual algorithm evolution SYNAER DLR 2240 Individual algorithm evolution IASI DLRBIRA, ULB, LMD 2300 Sentinel preparations SUFMI, UOx, KNMI, RAL 2400 Aerosol type information DLRFMI, SU, UOx, KNMI, BIRA, ULB, RAL, LMD 2500 Uncertainties UOxDLR, FMI, SU, BIRA, ULB, LMD 2600 Consistency coordinated with several ECVs NILU 2700Joint aerosol cloud retrieval coordinated with Cloud_cciUOx Aerosol-cci Phase 2 KO, Oxford, 20-21 May 20143 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

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) Aerosol-cci Phase 2 KO, Oxford, 20-21 May 20144 WP2000 Activities

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 Aerosol-cci Phase 2 KO, Oxford, 20-21 May 20145 Cloud activities Phase 1

6. 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, 2008 AATSR operational

7. Cloud detection Single scene analysis

8. Cloud mask analysis Technical Note: Cloud Masking in Aerosol_CCI V1.0 Aerosol_CCI, 28 April 2011 Authors: Lars Klüser, Alexander Kokhanovsky, Caroline Poulsen and Larisa Sogacheva Recommendations

9. 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 meanings 0 cloud free ocean 1 cloud free land 2 sunglint area 3 dust flag 4 twilight zone 5 cloud

10. 12,4 % 21,1 % 0,5 % 66,0 % Cloud mask consistency Aerosol_cci / Cloud_cci 5 selected days Sep 2008 – safety zone excluded by Aerosol_cci

11. 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.

12. Phase 1 progress Quality Coverage Cloud detection Features Uncertainties Aerosol-cci Phase 2 KO, Oxford, 20-21 May 201412 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 ?

13. iLEAPS OSC 2011, Garmisch-Partenkirchen, 19-23 September, 2011 Fires in Russia August 2010

14. AATSR Dual View algorithm ADV & SACURA: aerosol & cloud properties AODCOTReff LWP albedo CTH AOD COT AOD Reff LWP Left: AATSR maps run w separate cloud and aerosol retrieval Right: transects with and w/o cloud mask: continuous in transition zone

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? Aerosol-cci Phase 2 KO, Oxford, 20-21 May 201415 FMI: cloud working group

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? Aerosol-cci Phase 2 KO, Oxford, 20-21 May 201416 FMI: ENVISAT gap filling