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| abstract
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| 1 | Ackerman | Steve | University of Wisconsin-Madison | USA |  | Keynotes passive instruments
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| 2 | Baum | Bryan | University of Wisconsin-Madison | USA | | MODIS Collection 6 Cloud Top Height and IR Thermodynamic Phase
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| 3 | Bennartz | Ralf | University of Wisconsin-Madison | USA | | Cloud liquid water path of warm clouds from passive microwave and visible/near-infrared imagers
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| 4 | Bojkov | Bojan | ESA/ESRIN | Europe |  | -
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| 5 | Borbas | Eva | University of Wisconsin-Madison | USA | | -
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| 6 | Bugliaro | Luca | DLR Oberpfaffenhofen | Germany |  | Realistic Simulations of MSG/SEVIRI Scenes for Cloud Algorithm Validation
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| 7 | Carbajal Henken | Cintia | Free University of Berlin | Germany | | Synergistic MERIS-AATSR cloud properties retrievals using optimal estimation technique
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| 8 | Chang | Fu-Lung | NASA, Science Systems & Applications Inc. | USA | | Using CALIPSO/CloudSat Data to Evaluate the Multilayer Cloud Properties Retrieved from MODIS and SEVIRI Data
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| 9 | Deneke | Hartwig | Leibniz Institute for Tropospheric Research | Germany | | Cloud analyses with passive satellite imagery viewed from the radiative perspective
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| 10 | Derrien | Marcel | Météo France | France |  | coauther
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| 11 | Dewitte | Steven | KMI | Belgium |  | Session chair
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| 12 | Doelling | Dave | NASA, Langley | USA | | The calibration of geostationary visible sensors using MODIS as a reference
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| 13 | Doppler | Lionel | LATMOS | France | | -
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| 14 | Frey | Richard | University of Wisconsin-Madison | USA | | -
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| 15 | Hamann | Ulrich | KNMI | Netherlands |  | The CREW workshop: an overview
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| 16 | Heck | Patrick W. | University of Wisconsin-Madison | USA | | Improved Methods for and Validation of Nighttime Cloud Property Retrievals from SEVIRI, GOES and MODIS
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| 17 | Heidinger | Andrew | NASA, Nesdis | USA | | State of the NOAA AWG Cloud Algorithms and their application in the Great Lakes Region
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| 18 | Holz | Bob | University of Wisconsin-Madison | USA | | -
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| 19 | Horváth | Ákos | MPI, Hamburg | Germany | | Evaluation of MISR Stereo Cloud-Top Height Retrievals
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| 20 | Hünerbein | Anja | Leibniz Institute for Tropospheric Research | Germany | | Synergetic cloud top height retrieval for a passive and an active sensor
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| 21 | Jonkheid | Bastiaan | KNMI | Netherlands | | A MSG/SEVIRI simulator for the validation of climate models
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| 22 | Joro | Sauli | Eumetsat | Europe | | -
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| 23 | Kahn | Brian | NASA, JPL | USA | | New AIRS Version 6 cloud retrievals: cloud thermodynamic phase, cirrus cloud optical thickness and effective diameter
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| 24 | Karlsson | Karl-Göran | SMHI | Sweden |  | Adding uncertainty information to cloud mask products – impact on Level 2 and Level 3 products
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| 25 | King | Michael | University of Colorado | USA | | Session chair
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| 26 | Kinne | Stefan | University Hamburg | Germany | | GEWEX Cloud Assessment: a review
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| 27 | Kokhanovsky | Alexander | University of Bremen | Germany | | Retrieval of cloud properties using synthetic datasets
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| 28 | Le Gleau | Hervé | Météo France | France | | SAFNWC / MSG cloud products
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| 29 | Lockhoff | Maarit | DWD | Germany | | Accuracy Assessment of SEVIRI Cloud Detection and Cloud Top Height Retrievals Using Active Remote Sensing Data from CloudSat and CALIPSO
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| 30 | Lutz | Hans Joachim | Eumetsat | Europe | | Multi-layer cloud detection within the SCE/CLA algorithm
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| 31 | Macke | Andreas | Leibniz Institute for Tropospheric Research | Germany | | Session chair
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| 32 | Maddux | Brent | KNMI | Netherlands | | Modis climatology
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| 33 | Marchant | Benjamin | NASA Goddard Space Flight Center | USA | | Optical Property Cloud Phase Retrievals for MODIS Collection 6: assessment from CALIOP/CALIPSO
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| 34 | May | Catherine | NASA, Jet Propulsion Laboratory | USA | | -
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| 35 | Meirink | Jan-Fokke | KNMI | Netherlands | | Using MSG-SEVIRI for the inter-calibration of visible and near-infrared reflectance from polar imagers
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| 36 | Menzel | Paul | University of Wisconsin-Madison | USA | | Keynote presenter
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| 37 | Minnis | Patrick | NASA, LaRC | USA | | Updated NASA Langley Cloud Property Retrievals
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| 38 | Müller | Jennifer | Institute for Space Science | Germany | | Integrating Cloud Observations from Ground and Space – a Way to Combine Time and Space Information
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| 39 | Musial | Jan | University of Bern | Switzerland |  | An Enhanced cloud classification scheme based on radiative transfer simulations and aggregated ratings
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| 40 | Nasiri | Shaima | Texas A&M University, College Station | USA | | -
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| 41 | Palikonda | Rabindra | NASA, Langley | USA | | LaRC real-time satellite derived products – Overview: Applications and Limitations
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| 42 | Pavolonis | Michael | NOAA/NESDIS/STAR | USA | | Cloud phase determination using infrared absorption optical depth ratios
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| 43 | Pincus | Robert | University of Colorado | USA | | Small decisions with big impacts: MODIS, ISCCP, and the evaluation of clouds in climate models
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| 44 | Placidi | Simone | TU Delft | Netherlands | | A novel technique for validating liquid water cloud properties
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| 45 | Platnick | Steven | NASA, GSFC | USA | | Overview of the MODIS Collection 6 Optical Property Algorithm
MODIS Optical Property Pixel-Level Uncertainty Estimates in Collection 6
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| 46 | Preusker | Rene | Free University Berlin | Germany | | Keynote lecture
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| 47 | Puygrenier | Vincent | Météo France | France | | A new spectrally consistent adiabatic method to derive cloud properties from MODIS measurement
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| 48 | Rausch | John | University of Wisconsin-Madison | USA | | Estimation of cloud properties though a spectrally consistent adiabatic model
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| 49 | Riedi | Jérôme | University of Lille 1 | France | | Intercomparison of liquid cloud properties retrieved from POLDER/PARASOL, MODIS/AQUA and SEVIRI/MSG
Use of A-Train observations to assess cloud phase retrievals from SEVIRI/MSG
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| 50 | Roebeling | Rob | KNMI | Netherlands | | The CREW workshop: an overview
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| 51 | Scheirer | Ronald | SMHI | Sweden | | Adding uncertainty tbc
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| 52 | Sèze | Geneviève | LMD | France | | Evaluation of the global cloud cover distribution obtained from multi-geostationary data in the frame of the MEGHA-TROPIQUES mission with CALIPSO lidar observations
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| 53 | Smith | Nadia | University of Wisconsin-Madison | USA | | -
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| 54 | Smith | William L Jr. | NASA, Langley | USA | | Improved Methods To Resolve The Vertical Distribution Of Cloud Water From Passive Satellite Data
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| 55 | Stengel | Martin | DWD | Germany | | The inter-comparison of retrieved cloud properties within the ESA Cloud CCI project
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| 56 | Stephens | Graeme | Atmosphere Colorado State University | USA | | Keynote lecture active sensors
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| 57 | Strabala | Kathy | University of Wisconsin-Madison | USA | | -
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| 58 | Thomas | Gareth | University of Oxford | UK |  | Application and evaluation of the Oxford-RAL Retrieval of Aerosol and Cloud algorithm to MODIS data
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| 59 | Thoss | Anke | SMHI | Sweden | | tbc
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| 60 | Trepte | Qing | Science Systems & Application Inc. | USA | | A Comparison of Cloud Detection between CERES Ed4 Cloud Mask and CALIPSO Version 3 Vertical Feature Mask
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| 61 | Vidot | Jerome | Météo France | France | | -
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| 62 | Walther | Andi | University of Wisconsin-Madison | USA | | Sources of error in satellite derived cloud products
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| 63 | Watts | Philip | Eumetsat | Europe | | Progress on optimal estimation cloud property retrieval from SEVIRI observations
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| 64 | Wind | Gala | NASA GSFC / SSAI, Inc | USA | | Improvements in Night-time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI
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| 65 | Winker | Dave | NASA | USA | | Current status Calipso cloud products
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| 66 | Wolters | Erwin | KNMI | Netherlands | | Evaluation of a 30-year NOAA-AVHRR cloud property climate data record
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| 67 | Xiong | Xianxiong (Jack) | NASA GSFC | USA | | MODIS Radiometric Calibration and Uncertainty Assessment
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| 68 | Yang | Ping | Texas A&M University | USA | | -
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| 69 | Zhang | Zhibo | University of Maryland | USA | | An assessment of differences between cloud effective particle radius retrievals for marine water clouds from three MODIS spectral bands: observational and modeling studies
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