Understanding Biases in Tropical Cyclone Intensity Forecast ErrorSource: Weather and Forecasting:;2017:;volume 033:;issue 001::page 129DOI: 10.1175/WAF-D-17-0106.1Publisher: American Meteorological Society
Abstract: AbstractThe characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of ?0.77, ?0.77, and ?0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ? of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity?time curve. The occurrence of large negative (positive) errors indicates the intensity?time curve is concave upward (downward) in nature during the TC?s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity?time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity?time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI.
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contributor author | Na, Wei | |
contributor author | McBride, John L. | |
contributor author | Zhang, Xing-Hai | |
contributor author | Duan, Yi-Hong | |
date accessioned | 2019-09-19T10:05:16Z | |
date available | 2019-09-19T10:05:16Z | |
date copyright | 12/7/2017 12:00:00 AM | |
date issued | 2017 | |
identifier other | waf-d-17-0106.1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4261374 | |
description abstract | AbstractThe characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of ?0.77, ?0.77, and ?0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ? of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity?time curve. The occurrence of large negative (positive) errors indicates the intensity?time curve is concave upward (downward) in nature during the TC?s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity?time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity?time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI. | |
publisher | American Meteorological Society | |
title | Understanding Biases in Tropical Cyclone Intensity Forecast Error | |
type | Journal Paper | |
journal volume | 33 | |
journal issue | 1 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-17-0106.1 | |
journal fristpage | 129 | |
journal lastpage | 138 | |
tree | Weather and Forecasting:;2017:;volume 033:;issue 001 | |
contenttype | Fulltext |