Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

Shimada, Udai; Owada, Hiromi; Yamaguchi, Munehiko; Iriguchi, Takeshi; Sawada, Masahiro; Aonashi, Kazumasa; DeMaria, Mark; Musgrave, Kate D.

doi:10.1175/WAF-D-18-0021.1

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

2018
By Shimada, Udai ; Owada, Hiromi ; Yamaguchi, Munehiko ; ...
Source: Weather and Forecasting, 33(6), 1587-1603

[PDF-2.64 MB]

Details You May Also Like

Details:

Journal Title:

Weather and Forecasting
Personal Author:

Shimada, Udai ; Owada, Hiromi ; Yamaguchi, Munehiko ; Iriguchi, Takeshi ; Sawada, Masahiro ; ... More +

Shimada, Udai ; Owada, Hiromi ; Yamaguchi, Munehiko ; Iriguchi, Takeshi ; Sawada, Masahiro ; Aonashi, Kazumasa ; DeMaria, Mark ; Musgrave, Kate D. Less -
NOAA Program & Office:

NWS (National Weather Service) ; NHC (National Hurricane Center) ; CIRA (Cooperative Institute for Research in the Atmosphere)

NWS (National Weather Service) ; NHC (National Hurricane Center) ; CIRA (Cooperative Institute for Research in the Atmosphere) Less -
Description:

The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%–5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.
Keywords:

[+]

Cyclones Statistical Weather Forecasting Weather Forecasting Forecasting Techniques Forecast Verification Operational Forecasting Statistical Forecasting Statistical Hurricane Intensity Prediction Scheme (SHIPS) Tropical Cyclones
Source:

Weather and Forecasting, 33(6), 1587-1603
DOI:

https://doi.org/10.1175/WAF-D-18-0021.1
Document Type:

Journal Article
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:aa14bc7add8002e003842636786cbf0c63a487c5d036899b023b49ba20025934
Download URL:

https://repository.library.noaa.gov/view/noaa/46396/noaa_46396_DS1.pdf
File Type:

No Additional Files

More +

Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

Details:

Supporting Files

You May Also Like