scholarly journals Single cell and multiple cell clouds analysed with satellite data in and around Bangladesh

MAUSAM ◽  
2021 ◽  
Vol 50 (2) ◽  
pp. 177-180
Author(s):  
C. M. MUKAMMEL WARID ◽  
Md. REZAUR RAHMAN ◽  
Md. NAZRUL ISLAM
Keyword(s):  
Single Cell ◽  
Satellite Data ◽  
Mature Stage ◽  
Convective Component ◽  
Geostationary Meteorological Satellite ◽  
Multiple Cell ◽  
Meteorological Satellite

Multi-cell and single-cell clouds were analysed using Geostationary Meteorological Satellite (GMS-5) data on 6 and 13 August 1997 in and around Bangladesh. The multi-cell cloud moved NE with a speed of about 6 m/s and lasted approximately 21 hours. The single-cell cloud moved SE with a speed of about 13 m/s and lasted approximately 12 hours. Clouds move faster on oceans than on land. At the mature stage of the cloud, convective component was 40% and the rest was stratiform. The precipitable portion of the cloud was 74% and the rest was non-precipitable which differs from the reported value.

scholarly journals Assessment of Aircraft Icing Potential and Maximum Icing Altitude from Geostationary Meteorological Satellite Data

2007 ◽  
Vol 22 (1) ◽  
pp. 160-174 ◽  
Author(s):  
Gary P. Ellrod ◽  
Andrew A. Bailey
Keyword(s):  
United States ◽  
Satellite Data ◽  
The Internet ◽  
Aircraft Icing ◽  
Spatial Coverage ◽  
Geostationary Meteorological Satellite ◽  
Potential Component ◽  
Using Data ◽  
Meteorological Satellite ◽  
Satellite Product

Abstract A satellite product that displays regions of aircraft icing potential, along with corresponding cloud-top heights, has been developed using data from the Geostationary Operational Environmental Satellite (GOES) imager and sounder. The icing product, referred to as the Icing Enhanced Cloud-top Altitude Product (ICECAP), is created hourly for the continental United States and southern Canada, and is color coded to show cloud-top altitudes in 1.9-km (6000 ft) intervals. Experimental ICECAP images became routinely available on the Internet during the spring of 2004. Verification of separate ICECAP components (imager icing potential and sounder cloud-top heights) using aircraft pilot reports (PIREPs) indicates that the product provides useful guidance on the spatial coverage and maximum altitude of current icing conditions, but not icing intensity, stratification, or minimum altitude. The imager icing potential component of ICECAP was compared with the operational 40-km resolution National Weather Service (NWS) current icing potential and NWS Airman’s Meteorological Advisories via the NOAA Real-Time Verification System, while GOES cloud-top heights were compared with altitudes of moderate or greater icing from PIREPs. Benefits and deficiencies of the GOES icing product are discussed.

Geostationary Meteorological Satellite Data Processing System

2011 ◽  
Vol 181-182 ◽  
pp. 257-260
Author(s):  
Hong Tao Guo ◽  
Zhi Guo Chang ◽  
Shan Wei He
Keyword(s):  
Remote Sensing ◽  
Data Processing ◽  
Satellite Data ◽  
Processing System ◽  
Weather Forecast ◽  
Cloud Detection ◽  
Data Processing System ◽  
Dynamic Link Library ◽  
Geostationary Meteorological Satellite ◽  
Meteorological Satellite

In order to design a set of geostationary meteorological satellite data processing system，which have common data processing，practical remote sensing products and rich visual stylet，used VC++6.0 MFC and dynamic link library and the mature remote sensing products processing algorithms, to design it. Multi-satellite source geostationary meteorological satellite data are integrated, remote sensing products are generated, for example, cloud detection, cloud classification, cloud top height. The original cloud image, remote sensing and geographic information products are displayed vividly. The three-dimensional cloud image processing retrieval based on cloud detection product takes into account the visual effect, and also has a clear physical meaning, practicality is strong. The system makes geostationary meteorological satellite information play a more important role in the current weather forecast.

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