Application of spatiotemporal pattern recognition techniques on predicting extratropical transition (and reintensification) of tropical cyclones
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
A Multivariable Pattern Recognition Technique to Predict Extratropical Transition of Tropical Cyclones
Projection Pursuit algorithms have been used ex- tensively to reduce the dimensionality of large data sets finding interesting low-dimensional projections. We are utilizing a mul- tivariate projection pursuit algorithm to find the variabilities to differentiate the tropical cyclones that complete and fail to complete the extratropical transition in the Western North Pacific. The NOGAPS 500-mb geopotential height analyses and 250-mb wind vorticity fields have been used in the system as two variables. It has been found that addition of the vorticity variable improved the forecasting performance of the system compared to the use of 500-mb heights alone.
Seasonality in the Associations between Surface Temperatures over the United States and the North Pacific Ocean
Abstract Thirty-one years of monthly data are used to evaluate the seasonal dependence of the associations between large-scale temperature anomalies over the United States and the North Pacific Ocean. Both station (grid-point) values and empirical orthogonal functions of temperature are used in the correlative analysis. The North Pacific sea surface temperature (SST) anomalies correlate most highly with temperature fluctuations over the southeastern and the far western states. Correlations with the SST anomalies have opposite signs in the two portions of the United States. The associations with the SST anomalies are independent of season only in the western states. The association involving the southeastern states is strongest during the winter and insignificant during the summer. The pattern of North Pacific SST that correlates most highly with the United States temperature is an east-west SST gradient between the West Coast and 35°N, 160°W. Statistically significant fractions of temperature variance ove...