Next Article in Journal
Customization and Validation of a Regional Climate Model Using Satellite Data Over East Africa
Next Article in Special Issue
Characteristics of Oceanic Warm Cloud Layers within Multilevel Cloud Systems Derived by Satellite Measurements
Previous Article in Journal
Generation and Analysis of Gridded Visibility Data in the Arctic
Previous Article in Special Issue
Creating Truth Data to Quantify the Accuracy of Cloud Forecasts from Numerical Weather Prediction and Climate Models
Open AccessArticle

Comparison of SAFNWC/MSG Satellite Cloud Type with Vaisala CL51 Ceilometer-Detected Cloud Base Layer Using the Sky Condition Algorithm and Vaisala BL-View Software

1
Amper Meteo, S. R. O., Pobřežní 620/3, 186 00 Praha 8, Czech Republic
2
Global Change Research Institute CAS, Bělidla 986/4a, 60300 Brno, Czech Republic
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(6), 316; https://doi.org/10.3390/atmos10060316
Received: 11 April 2019 / Revised: 4 June 2019 / Accepted: 5 June 2019 / Published: 7 June 2019
(This article belongs to the Special Issue Remote Sensing of Clouds)
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. View Full-Text
Keywords: cloud type; ceilometer; satellite; contingency table cloud type; ceilometer; satellite; contingency table
Show Figures

Figure 1

MDPI and ACS Style

Šálek, M.; Szabó-Takács, B. Comparison of SAFNWC/MSG Satellite Cloud Type with Vaisala CL51 Ceilometer-Detected Cloud Base Layer Using the Sky Condition Algorithm and Vaisala BL-View Software. Atmosphere 2019, 10, 316.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop