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    Evaluation of the shortwave cloud radiative effect over the ocean by use of ship and satellite observations
    (München : European Geopyhsical Union, 2012) Hanschmann, T.; Deneke, H.; Roebeling, R.; Macke, A.
    In this study the shortwave cloud radiative effect (SWCRE) over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR) and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.
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    Detection of convective initiation using Meteosat SEVIRI: Implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM
    (München : European Geopyhsical Union, 2013) Merk, D.; Zinner, T.
    In this paper a new detection scheme for convective initiation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting CI with geostationary satellite data. It uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared (IR) criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one high-resolution visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims to identify the typical development of quickly developing convective cells in an early stage. The different criteria include time trends of the 10.8 IR channel, and IR channel differences, as well as their time trends. To provide the trend fields an optical-flow-based method is used: the pyramidal matching algorithm, which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM, and is verified for seven days which comprise different weather situations in central Europe. Contrasted with the original early-stage detection scheme of Cb-TRAM, skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for the synoptic class "cold air" masses.
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    Multichannel analysis of correlation length of SEVIRI images around ground-based cloud observatories to determine their representativeness
    (München : European Geopyhsical Union, 2015) Slobodda, J.; Hünerbein, A.; Lindstrot, R.; Preusker, R.; Ebell, K.; Fischer, J.
    Images of measured radiance in different channels of the geostationary Meteosat-9 SEVIRI instrument are analysed with respect to the representativeness of the observations of eight cloud observatories in Europe (e.g. measurements from cloud radars or microwave radiometers). Cloudy situations are selected to get a time series for every pixel in a 300 km × 300 km area centred around each ground station. Then a cross correlation of each time series to the pixel nearest to the corresponding ground site is calculated. In the end a correlation length is calculated to define the representativeness. It is found that measurements in the visible and near infrared channels, which respond to cloud physical properties, are correlated in an area with a 1 to 4 km radius, while the thermal channels, that correspond to cloud top temperature, are correlated to a distance of about 20 km. This also points to a higher variability of the cloud microphysical properties inside a cloud than of the cloud top temperature. The correlation length even increases for the channels at 6.2, 7.3 and 9.7 μm. They respond to radiation from the upper atmospheric layers emitted by atmospheric gases and higher level clouds, which are more homogeneous than low-level clouds. Additionally, correlations at different distances, corresponding to the grid box sizes of forecast models, were compared. The results suggest the possibility of comparisons between instantaneous cloud observations from ground sites and regional forecast models and ground-based measurements. For larger distances typical for global models the correlations decrease, especially for short-wave measurements and corresponding cloud products. By comparing daily means, the correlation length of each station is increased to about 3 to 10 times the value of instantaneous measurements and also the comparability to models grows.