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  • 1.
    Håkansson, Nina
    et al.
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Adok, Claudia
    Thoss, Anke
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Scheirer, Ronald
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Hörnquist, Sara
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Neural network cloud top pressure and height for MODIS2018Inngår i: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, nr 5, s. 3177-3196Artikkel i tidsskrift (Fagfellevurdert)
  • 2.
    Karlsson, Karl-Göran
    et al.
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Anttila, Kati
    Trentmann, Jorg
    Stengel, Martin
    Meirink, Jan Fokke
    Devasthale, Abhay
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Hanschmann, Timo
    Kothe, Steffen
    Jaaskelainen, Emmihenna
    Sedlar, Joseph
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Benas, Nikos
    van Zadelhoff, Gerd-Jan
    Schlundt, Cornelia
    Stein, Diana
    Finkensieper, Stefan
    Håkansson, Nina
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Hollmann, Rainer
    CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data2017Inngår i: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, nr 9, s. 5809-5828Artikkel i tidsskrift (Fagfellevurdert)
  • 3.
    Karlsson, Karl-Göran
    et al.
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Håkansson, Nina
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record2018Inngår i: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, nr 1, s. 633-649Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50% of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50% over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid-to high latitudes where at least 50% of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts with the highest altitudes over Greenland and Antarctica. It is suggested to quantify the detection performance of other CDRs in terms of a sensitivity threshold of cloud optical thickness, which can be estimated using active lidar observations. Validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterization of various cloud CDRs from passive imagery.

  • 4.
    Karlsson, Karl-Göran
    et al.
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Håkansson, Nina
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Mittaz, Jonathan P. D.
    Hanschmann, Timo
    Devasthale, Abhay
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record2017Inngår i: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 9, nr 6, artikkel-id 568Artikkel i tidsskrift (Fagfellevurdert)
  • 5. Pfreundschuh, Simon
    et al.
    Eriksson, Patrick
    Duncan, David
    Rydberg, Bengt
    Håkansson, Nina
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Thoss, Anke
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems2018Inngår i: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, nr 8, s. 4627-4643Artikkel i tidsskrift (Fagfellevurdert)
  • 6. Sporre, Moa K.
    et al.
    O'Connor, Ewan J.
    Håkansson, Nina
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Thoss, Anke
    SMHI, Forskningsavdelningen, Atmosfärisk fjärranalys.
    Swietlicki, Erik
    Petaja, Tuukka
    Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland2016Inngår i: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 9, nr 7, s. 3193-3203Artikkel i tidsskrift (Fagfellevurdert)
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