Diagnosing Tropical Cyclone Intensification Composite Variability using Reanalyses

Tropical-cyclone intensification, in particular rapid intensification, continues to be a major forecast challenge, primarily due to the lack of understanding of the physical processes that govern its onset. Recent work has considered composite analysis using the NCEP/NCAR reanalysis dataset as a method of identifying physical differences in these fields. However, it is well documented that reanalyses all have their own associated limitations, biases, etc., that can alter the interpretation of the physical state of the atmosphere at a given timestep. Recent work in compositing has revealed unique patterns for different atmospheric phenomena, including tropical cyclones, but has traditionally only considered one reanalysis dataset, treating that set as ground truth. This study will consider reanalysis data from the 20th century reanalysis, the NCEP/NCAR reanalysis, the MERRA dataset, the ERA-Interim reanalysis, and the NCEP-DOE reanalysis 2.

Composite files of rapidly intensifying and non-rapidly intensifying tropical cyclones using a T-mode kernel principal component analysis for each of the four reanalysis datasets were completed, centered on the NHC best-track position. Composites were formulated from 24-hours prior to the onset of the lowest surface pressure from the NHC best-track position. The resulting KPC loadings were clustered (since KPC loadings are indicative of physical similarities among cases), yielding composite map types for rapidly intensifying and non-rapidly intensifying tropical cyclones. These fields were diagnosed for similarities in magnitudes and patterns among the reanalysis products, and important features for intensification were identified using this process.