1Deutscher Wetterdienst, 2 RAL Space, 3SMHI, 4LMD

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Presentation transcript:

1Deutscher Wetterdienst, 2 RAL Space, 3SMHI, 4LMD Cloud_cci R. Hollmann1, C. Poulsen2, U. Willen3, C. Stubenrauch4, M. Stengel1, and the Cloud CCI consortium 1Deutscher Wetterdienst, 2 RAL Space, 3SMHI, 4LMD

Cloud_cci: Available data phase 2 Two multi-decadal global data sets for the GCOS cloud property ECVs including uncertainty estimates. multi-decadal multi-instrument product from (A)ATSR – AVHRR – MODIS (1982-2012 (2014) decadal product that uses complimentary information from AATSR and MERIS on-board of ENVISAT (2002-2012) Processing has started, first data available May 2016

Cloud_cci: Available data FAME-C decadal product that uses complimentary information from AATSR and MERIS on-board of ENVISAT (2002-2012) Daytime orbits Swath width ~ 500 km Pixels of ~1 km

Evaluation: FAME-C Cloud Top Heights Comparison to ground-based radar and lidar observations: At 3 ARM sites covering various cloudy regimes: NSA, SGP, TWP Cloud boundary product ARSCL (Clothiaux et al., 2000) On a level-2 basis, 2007-2009 Single- and multi-layer clouds Main conclusions: AATSR better for higher clouds MERIS better for lower clouds Better results for single-layer clouds than multi-layer clouds

Level-3 products: FAME-C examples Level-3 products for: Cloud cover Cloud top height/temperature/pressure Ice water path, liquid water path Cloud phase Effective radius Optical thickness Cloud Albedo VIS and NIR

Cloud_cci: Available data CC4CL FAME-C decadal product that uses complimentary information from AATSR and MERIS on-board of ENVISAT (2002-2012) CC4CL multi-decadal multi-instrument product from (A)ATSR – AVHRR – MODIS (1982-2012 (2014)

Community Optimal Estimation Cloud Retrieval for Climate = CC4CL Cloud_cci: CC4CL OE Framework L1c AVHRR, MODIS, A(A)TSR + auxiliary data cf phasec Pre-processing τc pc reff Tsurf Retrieved products Tc hc LWP, IWP Derived products ρDHR1,2 L3C L3S L2toL3 L3U Community Optimal Estimation Cloud Retrieval for Climate = CC4CL

Cloud fraction day land (07/2008)

Joint Cloud Property Histograms for July 2008 ci cs cb ac as ns cu sc st JCP histograms for daytime retrievals due to the fact that COT is derived using VIS channels! Left figures show the dominating cloud type per grid cell (0.5 grid) in january and june 2008 for AVHRR NOAA18; Right figures show the relative occurrence of the cloud types w.r.t. ISCCP COT-CTP classification. Based on 2D histogram analysis: Im mittel haben wir signifikant weniger hohe Wolken (-17%). Vor allem weniger cirrus stratus (-10%) dann cirrus (-5%) und erst dann deep convectice (-2%). (das sah bei collection 5 noch anders aus , beide gemeinsam haben mehr cirrustratus) ;high clouds HIGH/all Ratio CC4CL-NOAA-18 : 27.89% HIGH/all Ratio Coll6-AQUA : 44.93% ;cirrus CI/all Ratio CC4CL-NOAA-18 : 11.07% CI/all Ratio Coll6-AQUA : 16.47% ; cirrus-stratus CS/all Ratio CC4CL-NOAA-18 : 11.60% CS/all Ratio Coll6-AQUA : 21.49% ; deep convective clouds CB/all Ratio CC4CL-NOAA-18 : 5.22% CB/all Ratio Coll6-AQUA : 6.96% Wir haben dafür mehr mittelhohe wolken (+9%) ; middle high clouds MID/all Ratio CC4CL-NOAA-18 : 22.44% MID/all Ratio Coll6-AQUA : 13.64% Auch mehr niedrige (+8%) ; low clouds LOW/all Ratio CC4CL-NOAA-18 : 49.67% LOW/all Ratio Coll6-AQUA : 41.44%

Cloud fraction day ocean (07/2008)

Cloud fraction night land (07/2008)

Cloud_cci: cross-cutting themes cloud & Aerosol interactions SST joint radiance Level 1 data set for AVHRR GAC data. Clouds feedback sea-ice, SST? Clouds - soil-moisture - precip

Thank you for your attention