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contributor authorNa, Wei
contributor authorMcBride, John L.
contributor authorZhang, Xing-Hai
contributor authorDuan, Yi-Hong
date accessioned2019-09-19T10:05:16Z
date available2019-09-19T10:05:16Z
date copyright12/7/2017 12:00:00 AM
date issued2017
identifier otherwaf-d-17-0106.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261374
description abstractAbstractThe 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.
publisherAmerican Meteorological Society
titleUnderstanding Biases in Tropical Cyclone Intensity Forecast Error
typeJournal Paper
journal volume33
journal issue1
journal titleWeather and Forecasting
identifier doi10.1175/WAF-D-17-0106.1
journal fristpage129
journal lastpage138
treeWeather and Forecasting:;2017:;volume 033:;issue 001
contenttypeFulltext


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