Improvements in the Probabilistic Prediction of Tropical Cyclone Rapid Intensification with Passive Microwave Observations

Details

• Journal Title:
  Weather and Forecasting
• Personal Author:
  Rozoff, Christopher M. ; Velden, Christopher S. ; Kaplan, John ; Kossin, James P. ; Wimmers, Anthony J.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; NESDIS (National Environmental Satellite, Data, and Information Service)
• Description:
  The probabilistic prediction of tropical cyclone (TC) rapid intensification (RI) in the Atlantic and eastern Pacific Ocean basins is examined here using a series of logistic regression models trained on environmental and infrared satellite-derived features. The environmental predictors are based on averaged values over a 24-h period following the forecast time. These models are compared against equivalent models enhanced with additional TC predictors created from passive satellite microwave imagery (MI). Leave-one-year-out cross validation on the developmental dataset shows that the inclusion of MI-based predictors yields more skillful RI models for a variety of RI and intensity thresholds. Compared with the baseline forecast skill of the non-MI-based RI models, the relative skill improvements from including MI-based predictors range from 10.6% to 44.9%. Using archived real-time data during the period 2004-13, evaluation of simulated real-time models is also carried out. Unlike in the model development stage, the simulated real-time setting involves using Global Forecast System forecasts for the non-satellite-based predictors instead of "perfect" observational-based predictors in the developmental data. In this case, the MI-based RI models still generate superior skill to the baseline RI models lacking MI-based predictors. The relative improvements gained in adding MI-based predictors are most notable in the Atlantic, where the non-MI versions of the models suffer acutely from the use of imperfect real-time data. In the Atlantic, relative skill improvements provided from the inclusion of MI-based predictors range from 53.5% to 103.0%. The eastern Pacific relative improvements are less impressive but are still uniformly positive.
• Source:
  Weather and Forecasting, 30(4), 1016-1038.
• DOI:
  https://doi.org/10.1175/WAF-D-14-00109.1
• Document Type:
  Journal Article
• Funding:
  Grant no. NA10NES4400013 ; Grant no. NA11OAR4310200
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:ee54217503415a351099314ab71d9246eeb899a43cf395730da03d3e915e9257
• Download URL:
  https://repository.library.noaa.gov/view/noaa/16179/noaa_16179_DS1.pdf
• File Type:
  [PDF - 7.90 MB ]