Abstract:
Traditional spatial decompositions such as application of Empirical Orthogonal Functions and Principal Components Analysis (PCA) of meteorological field data have receive...Show MoreMetadata
Abstract:
Traditional spatial decompositions such as application of Empirical Orthogonal Functions and Principal Components Analysis (PCA) of meteorological field data have received wide attention in numerous forecasting and analysis applications. The method has been used to identify the important spatial patterns in meteorological fields. Defining the variability between various cases of tropical cyclones is another application of the method. We are utilizing spatial and temporal data as a tool to differentiate the TCs that complete and fail to complete extratropical transition in the western North Pacific. It has been shown that EOF Analysis is a promising tool in the prediction of reintensification of TCs after ET
Date of Conference: 20-24 September 2004
Date Added to IEEE Xplore: 27 December 2004
Print ISBN:0-7803-8742-2
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- IEEE Keywords
- Index Terms
- Spatial Patterns ,
- Hurricane ,
- Pattern Recognition Techniques ,
- Extratropical Transition ,
- Temporal Data ,
- Attention For Applications ,
- Western North Pacific ,
- Empirical Orthogonal Function ,
- Meteorological Fields ,
- Empirical Orthogonal Function Analysis ,
- Spatial Decomposition ,
- Dissipation ,
- Large Datasets ,
- Eigenvalues ,
- Receiver Operating Characteristic Curve ,
- Covariance Matrix ,
- Atmospheric Pressure ,
- Positive Cases ,
- Sea Surface Temperature ,
- Negative Cases ,
- Negative Ones ,
- Cyclogenesis ,
- Optimization Step ,
- Projection Distance
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Spatial Patterns ,
- Hurricane ,
- Pattern Recognition Techniques ,
- Extratropical Transition ,
- Temporal Data ,
- Attention For Applications ,
- Western North Pacific ,
- Empirical Orthogonal Function ,
- Meteorological Fields ,
- Empirical Orthogonal Function Analysis ,
- Spatial Decomposition ,
- Dissipation ,
- Large Datasets ,
- Eigenvalues ,
- Receiver Operating Characteristic Curve ,
- Covariance Matrix ,
- Atmospheric Pressure ,
- Positive Cases ,
- Sea Surface Temperature ,
- Negative Cases ,
- Negative Ones ,
- Cyclogenesis ,
- Optimization Step ,
- Projection Distance