English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Forecasts of rapid intensification (RI) within tropical cyclones continue to be a major challenge, primarily due to difficulty in determining the processes that distinguish RI and non-RI storms. In this study, the aim was to identify the most important RI/non-RI discriminatory variables in the North Atlantic basin, not only by level, but also spatial location relative to the tropical cyclone center. These important variables, identified using rotated principal component analysis on one-dimensional and three-dimensional GEFS reforecast base-state variables from 1985 to 2009, led to the identification of diagnostic fields with the largest variability between RI and non-RI events. Hierarchical clustering techniques performed on rotated PC loadings provided map types of RI and non-RI cyclones. Analysis of these composite map types, as well as composite derived fields including divergence, relative vorticity, equivalent potential temperature, static stability, and vertical shear, revealed interesting distinguishing characteristics between RI and non-RI events. Results suggested that vorticity in the mid-levels, divergence in the upper-levels, equivalent potential temperature, and specific humidity play critical roles in successfully discriminating between RI and non-RI storms. These findings give key insights to which variables should be used in developing a prognostic classification scheme to assist with operational forecasts of tropical cyclone RI.

Diagnosing Tropical Cyclone Rapid Intensification Through Rotated Principal Component Analysis of Synoptic-Scale Diagnostic Fields