Field trial of an automated ground-based infrared cloud classification system

Meteorological applications

article

Emal Rumi¹  David Kerr²  Andrew Sandford¹  Jeremy Coupland²  Mike Brettle¹ 

[1] Campbell Scientific Ltd;Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University

关键词: cloud classification;    infrared;    pattern recognition;    image processing;    texture analysis;    convective cloud;    remote sensing;    cumulonimbus cloud;   

DOI  :  10.1002/met.1523

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

Automated classification of cloud types using a ground-based infrared (IR) imager can provide invaluable high-resolution and localized information for air traffic controllers. Observations can be made consistently, continuously in real time and accurately during both day and night operation. Details of a field trial of an automated, ground-based IR cloud classification system are presented. The system was designed at Campbell Scientific Ltd. in collaboration with Loughborough University, UK. The main objective of the trial was to assess the performance of an automated IR camera system with a lightning detector in classifying several types of clouds, specifically cumulonimbus and towering cumulus, during continuous day and night operation. Results from the classification system were compared with those obtained from Meteorological Aerodrome Reports (METAR) and with data generated by the UK Meteorological Office from their radar- and sferics-automated cloud reports system. In comparisons with METAR data, a probability of detection of up to 82% was achieved, together with a minimum probability of false detection of 18%.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND