Abstract
Ceilometer detection can be used to determine cloud type based on cloud layer height. Satellite observations provide images of clouds’ physical properties. During the summer and winter of 2017, Satellite Application Facility on support to Nowcasting/Very Short-Range Forecasting Meteosat Second Generation (SAFNWC/MSG) cloud type was compared to cloud base layers based upon a sky condition algorithm of Vaisala CL51 ceilometer and the BL-View applied range-variant smoothing backscatter profile at the National Atmospheric Observatory in Košetice, Czech Republic. This study investigated whether the larger measurement range of CL51 improved high cloud base detection and the effect of the range-variant smoothing on cloud base detection. The comparison utilized a multi-category contingency table wherein hit rate, false alarm ratio, frequency of bias, and proportion correct were evaluated. The accuracy of low-level and high cloud type detection by satellite was almost identical in both seasons compared to that using the sky condition algorithm. The occurrence of satellite high cloud detection was greatest when the ceilometer detected high cloud base above low and/or medium cloud base. The hit rate of high cloud detection increased significantly when the BL-View-produced cloud base layer was applied as a reference. We conclude that BL-View produces more accurate high cloud base detection.
Highlights
Clouds alter the short- and long-wave radiative flux divergence, which in turn modulates the boundary layer dynamics and plays a key role in the problem of climate change
On one cloud type with BL-View software-produced cloud base layer heights based on range-variant smoothing hand, this result points to the fact that the satellite cannot correctly detect multi-layer clouds, while, of the aerosol backscatter profile
SAFNWC/MSG satellite cloud type detection was compared with the cloud base layers of the Vaisala CL51 sky condition algorithm and with the BL-View-detected cloud layers by range-variant satellite type detection compared with cloudperiods
Summary
Clouds alter the short- and long-wave radiative flux divergence, which in turn modulates the boundary layer dynamics and plays a key role in the problem of climate change. According to Costa-Surós et al [8], when detecting cloud vertical structure using the CL31 ceilometer, difficulties occurred in retrieving a second cloud layer over a thick first layer This contributed to an inability to determine the cloud top. The Vaisala CL51 ceilometer cloud base height detection by raw and smoothed backscatter profiling was compared with detection using SAFNWC/MSG cloud type data in 2007 winter (DJF) and summer (JJA) periods to answer the following questions:.
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