Title :
Automatic Rain and Wind Measurement Fault Identification in Mesoscale Weather Station Networks
Author :
Hasu, Vesa ; Koivo, Heikki
Author_Institution :
Dept. of Autom. & Syst. Technol., TKK Helsinki Univ. of Technol., Helsinki
Abstract :
Future increase in short-term weather forecasting, i.e. nowcasting, products requires denser surface weather station networks than in before. Thus number of measurement stations and points increases also and their fault identification must be more accurate - the fault identification tests must be tailor-made for dense measurement networks. This paper proposes several automatic rain and wind measurement fault identification algorithms for surface weather station networks with station spacing around 10-20 km.
Keywords :
atmospheric techniques; fault diagnosis; rain; weather forecasting; wind; automatic rain measurement; fault identification; mesoscale weather station network; short-term weather forecasting; wind measurement; Fault diagnosis; Humans; Meteorology; Quality control; Rain; Sampling methods; Testing; Ultrasonic variables measurement; Weather forecasting; Wind; Automated diagnostic systems; rain measurements; wind measurements;
Conference_Titel :
Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4244-1540-3
Electronic_ISBN :
1091-5281
DOI :
10.1109/IMTC.2008.4547085