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Dynamic model for space-time weather...

Xu, Gang.

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Dynamic model for space-time weather radar observation and nowcasting.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Dynamic model for space-time weather radar observation and nowcasting./
作者:	Xu, Gang.
面頁冊數:	154 p.
附註:	Adviser: Venkatachalam Chandrasekar.
Contained By:	Dissertation Abstracts International68-06B.
標題:	Atmospheric Sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3266342
ISBN:	9780549039426

Dynamic model for space-time weather radar observation and nowcasting.
Xu, Gang.

Dynamic model for space-time weather radar observation and nowcasting. - 154 p.

Adviser: Venkatachalam Chandrasekar.

Thesis (Ph.D.)--Colorado State University, 2007.

A general framework of the dynamic model for space-time radar observations has been developed in the current research. There exist three difficulties in modeling space-time radar observations: (1) high dimensionality due to the high-resolution radar measurements over a large area, (2) non-stationarity due to the storm motion, and (3) nonstationarity due to evolution (growth and decay). These difficulties are addressed in this research. To deal with the storm motion, an efficient radar storm tracking algorithm is developed in the spectral domain. Based on this new technique, the Dynamic and Adaptive Radar Tracking of Storms (DARTS) is developed and evaluated using the synthesized and the observed radar reflectivity. To tackle the high dimensionality and model the spatial variability of radar observations, a general modeling framework is formulated and the singular value decomposition (SVD) is used for dimension reduction. To deal with the dynamic evolution and model the temporal variability of radar observations, the motion-compensated temporal alignment (MCTA) transformation is developed. In this analysis the evolution of radar storm fields is modeled by the linear dynamic system (LDS) in the low-dimensional subspace. The applications of the dynamic model for space-time radar observations are further demonstrated. Spatial and dynamic characteristics are obtained based on the estimated model parameters using three months of radar observations. The characteristic temporal scales are quantified for this dataset. The correlation between the temporal characterization and the spatial characterization of observed radar fields are explored. The simulation capability of different spatiotemporal radar reflectivity fields is demonstrated. Evaluation of the space time variability is particularly important in the context of adaptive scanning of storm systems. The short-term prediction of radar reflectivity fields based on the space-time dynamic model is evaluated using observed radar data. The simulations of the DARTS for real-time applications are also conducted and evaluated.

ISBN: 9780549039426Subjects--Topical Terms:

1019179
Atmospheric Sciences.

Dynamic model for space-time weather radar observation and nowcasting.
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