2016InTech eBooksOpen access

An Operational Statistical Scheme for Tropical Cyclone-Induced Rainfall Forecast

Qinglan Li, Hongping Lan, Johnny C. L. Chan, Chunyan Cao, Cheng Li, Xingbao Wang

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Abstract

Nonparametric methods are used in this study to analyze and predict short-term rainfall due to tropical cyclones (TCs) in a coastal meteorological station. All 427 TCs during 1953–2011, which made landfall along the Southeast China coast with a distance less than 700 km to a certain meteorological station, Shenzhen, are analyzed and grouped according to their landfalling direction, distance, and intensity. The corresponding daily rainfall records at Shenzhen Meteorological Station (SMS) during TCs landfalling period (a couple of days before and after TC landfall) are collected. The maximum daily rainfall (R24) and maximum 3-day accumulative rainfall (R72) records at SMS for each TC category are analyzed by a nonparametric statistical method, percentile estimation. The results are plotted by statistical boxplot, expressing in the probability of precipitation. The performance of the statistical boxplots was evaluated to forecast the short-term rainfall at SMS during the TC seasons in 2012 and 2013. The results show that the boxplot scheme can be used as a valuable reference to predict the short-term rainfall at SMS due to TCs landfalling along the Southeast China coast.

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What this paper is about

Nonparametric methods are used in this study to analyze and predict short-term rainfall due to tropical cyclones (TCs) in a coastal meteorological station. All 427 TCs during 1953–2011, which made landfall along the Southeast China coast with a distance less than 700 km to a certain meteorological station, Shenzhen, are analyzed and grouped according to their landfalling direction, distance, and intensity. The corresponding daily rainfall records at Shenzhen Meteorological Station (SMS) during TCs landfalling period (a couple of days before and after TC landfall) are collected. The maximum daily rainfall (R24) and maximum 3-day accumulative rainfall (R72) records at SMS for each TC category are analyzed by a nonparametric statistical method, percentile estimation. The results are plotted by statistical boxplot, expressing in the probability of precipitation. The performance of the statistical boxplots was evaluated to forecast the short-term rainfall at SMS during the TC seasons in 2012 and 2013. The results show that the boxplot scheme can be used as a valuable reference to predict the short-term rainfall at SMS due to TCs landfalling along the Southeast China coast.

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Available abstract

Nonparametric methods are used in this study to analyze and predict short-term rainfall due to tropical cyclones (TCs) in a coastal meteorological station. All 427 TCs during 1953–2011, which made landfall along the Southeast China coast with a distance less than 700 km to a certain meteorological station, Shenzhen, are analyzed and grouped according to their landfalling direction, distance, and intensity. The corresponding daily rainfall records at Shenzhen Meteorological Station (SMS) during TCs landfalling period (a couple of days before and after TC landfall) are collected. The maximum daily rainfall (R24) and maximum 3-day accumulative rainfall (R72) records at SMS for each TC category are analyzed by a nonparametric statistical method, percentile estimation. The results are plotted by statistical boxplot, expressing in the probability of precipitation. The performance of the statistical boxplots was evaluated to forecast the short-term rainfall at SMS during the TC seasons in 2012 and 2013. The results show that the boxplot scheme can be used as a valuable reference to predict the short-term rainfall at SMS due to TCs landfalling along the Southeast China coast.

Key concepts: Landfall, Tropical cyclone, Environmental science, Percentile, Climatology, Meteorology, Precipitation, Nonparametric statistics

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