December 20th, 2016: The Outlier Analysis sub-page has been updated to include EP20 (Seymour) in the 2016 East Pacific D-SHIPS and LGEM graphs section.

December 1st, 2016: The Outlier Analysis sub-page has been updated to include AL16 (Otto) in the 2016 Atlantic D-SHIPS and LGEM graphs section.

November 7th, 2016: The Outlier Analysis sub-page has been fully updated and now includes 2016 data as well as D-SHIPS and LGEM graphs for the Atlantic and East Pacific basins.

June 15th, 2016: The 2016 SHIPS predictor file received error corrections.

May 17th, 2016: Data from the Atlantic, East Pacific, and Central Pacific basins for 2015 was added.

November 5th, 2015: Data from the Atlantic, East Pacific, and Central Pacific basins for 2014 was added.

September 11th, 2014: Data from the Atlantic, East Pacific, and Central Pacific basins for 2013 was added.

January 7th, 2014: The Developmental Data sub-page was updated with data from the Southern Hemisphere and the Northern Indian Ocean.

May 10th, 2013: The Central and East Pacific files are now separated. Atlantic, East Pacific, Central Pacific and Western Pacific files were updated and now include data from 2012.

September 4th, 2012: The Western Pacific developmental data file was updated to include data from 2000 to 2011.

Introduction to SHIPS

Tropical cyclone (TC) track forecast errors have decreased considerably over the past several decades. However, there have only been modest intensity forecast improvements. Because of the complex physical processes affecting intensity changes, statistical forecast models have remained competitive with much more general prediction systems. For this reason the National Hurricane Center (NHC) continues to run a hierarchy of operational intensity models that range from the simple Statistical Hurricane Intensity Prediction Scheme (SHIPS) to the fully-coupled atmosphere-ocean Hurricane Weather Research and Forecast (HWRF) system. Several projects are underway at CIRA and RAMMB to improve SHIPS and related statistical intensity forecast models. This website provides a summary of this work and links to publications and data sets used in this research.

A Brief History of SHIPS

The original motivation for developing the SHIPS model occurred in 1988 when John Kaplan from the Hurricane Research Division (HRD) participated in a visiting forecaster program at NHC during Hurricane Joan. It quickly became apparent that NHC had limited objective guidance for intensity prediction. Aware of these limitations, John worked with Mark DeMaria (also from HRD at that time) on a new project that led to the development of the Statistical Hurricane Intensity Prediction Scheme (SHIPS). The SHIPS model built on a previous effort at statistical intensity forecasting by Bob Merrill, and combines predictors from climatology, persistence, the atmosphere and ocean to estimate changes in the maximum sustained surface winds of tropical cyclones. The first real time runs of SHIPS were performed in 1990, and only provided forecasts to 48 hrs at 00 and 12 UTC. The output was available to NHC only in hardcopy format. Beginning in 1991, the digital forecasts were saved the Automated Tropical Cyclone Forecast (ATCF) A-decks, and are available from NHC’s archive at ftp://ftp.nhc.noaa.gov/atcf/archive. The model name in the ATCF is SHIP for the version without land effects (since 1991), DSHP for the version with land effects (since 2000) and LGEM for a related logistic growth equation model (since 2006). For the three year period 1996-1998, the ATCF model name for SHIP was changed to LBAR, which provided the track forecast for SHIPS at that time.

The original SHIPS model was "statistical-synoptic" where no information from large-scale forecast models were used. (all synoptic predictors were from model analyses) The model was converted to a "statistical-dynamical" model in 1997, where predictors were obtained from atmospheric forecast models, in addition to analyses. Table 1 shows a summary of the major milestones in the SHIPS and related models.

Although SHIPS forecasts since about 1997 have shown some skill compared to climatology and persistence forecasts, they have not performed well for rapidly intensifying cases. For this reason, the rapid intensity index (RII) was developed to provide an estimate of the probability of rapid intensification in the next 24 hr. The RII probabilities are provided as part of the SHIPS model text file, and use a subset of the SHIPS predictors most related to rapid intensification in a discriminant analysis algorithm. The SHIPS model provides intensity forecasts for the Atlantic, eastern and central North Pacific. A similar model called the Statistical Typhoon Intensity Prediction Scheme (STIPS) was developed for the western North Pacific, and later for the Indian Ocean and southern hemisphere.

The SHIPS and STIPS models use a linear regression technique, with the impacts of land applied as a correction in a post-processing step. To overcome some of the limitations of this formulation, the Logistic Growth Equation Model (LGEM) was developed. LGEM uses a simple nonlinear differential equation commonly used to model population growth to forecast intensity changes. LGEM is more sensitive to time variations in the predictors, and overcomes some of the limitations of the linear assumptions in the SHIPS model.

LGEM can be run with a much smaller number of predictors than SHIPS. A 2-predictor version is under development that provides a simple phase-space interpretation of the results. Further details are available here.

Current Research

Current research involves improving SHIPS, LGEM and RII by better utilizing GOES imagery, new information from satellite-based total precipitable water products, and surface flux estimates. Methods for using the adjoint of the LGEM model to better include persistence are also under development. Lightning data is also being examined for possible use in SHIPS, LGEM and RII. The projects are partially sponsored by the Joint Hurricane Testbed (JHT), GOES-R Risk Reduction Program and Hurricane Forecast Improvement Project (HFIP).

Milestones in the Operational SHIPS and Related Model Development

Disclaimer: These environmental data and related items of information have not been formally disseminated by NOAA and do not represent and should not be construed to represent any agency determination, view, or policy.