DocumentCode :
2202663
Title :
Recent updates to the CASA nowcasting system
Author :
Ruzanski, Evan ; Chandrasekar, V.
Author_Institution :
Boulder Oper., Vaisala, Inc., Louisville, CO, USA
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
2426
Lastpage :
2429
Abstract :
The Collaborative Adaptive Sensing of the Atmosphere (CASA) nowcasting system currently provides 0-30 min automated forecasts (nowcasts) of precipitation to National Weather Service forecasters, emergency managers, and researchers using composite X-band weather radar data. Nowcasting is accomplished in two steps. First, the Fourier-based Dynamic and Adaptive Radar Tracking of Storms (DARTS) technique computes a motion vector field representing precipitation pattern motion using a recently observed sequence of radar reflectivity fields. Then, future reflectivity fields are estimated by recursively advecting the latest observed or predicted field according to this motion vector field using a sine kernel-based method. This paper presents potential upgrades to the CASA nowcasting system. The performance of the current sine kernel-based advection method is compared to that of a backward mapping technique in terms of categorical (rain/no rain) assessments of accuracy. Because computational efficiency is an important concern given the high-resolution (0.5 km/1 min) nature of the CASA data, the respective computational efficiencies are also compared. A technique to perform temporal interpolation within the DARTS model with the potential application to data fusion is also presented and assessed.
Keywords :
interpolation; pattern recognition; rain; sensor fusion; weather forecasting; CASA data; CASA nowcasting system; Collaborative Adaptive Sensing of the Atmosphere; DARTS technique; Fourier-based Dynamic and Adaptive Radar Tracking of Storms; National Weather Service; automated forecast; backward mapping technique; categorical assessment; composite X-band weather radar data; computational efficiency; data fusion; emergency management; kernel-based advection method; motion vector field; no rain assessment; precipitation nowcast; precipitation pattern motion representation; radar reflectivity field sequence; recursive advection; sine kernel-based method; temporal interpolation; Discrete Fourier transforms; interpolation; linear systems; meteorological radar; prediction methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6351001
Filename :
6351001
Link To Document :
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