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Examining El Niño–Southern Oscillation Effects in the Subtropical Zone to Forecast Long-Distance Total Rainfall from Typhoons: a Case Study in Taiwan

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Examining El Niño–Southern Oscillation Effects in the Subtropical Zone to Forecast Long-Distance Total Rainfall from Typhoons: a Case Study in Taiwan OCTOBER 2017 W E I 2141 Examining El Niño–Southern Oscillation Effects in the Subtropical Zone to Forecast Long-Distance Total Rainfall from Typhoons: A Case Study in Taiwan CHIH-CHIANG WEI Department of Marine Environmental Informatics, National Taiwan Ocean University, Keelung City, Taiwan (Manuscript received 4 November 2016, in final form 11 July 2017) ABSTRACT Typhoon rainfall predictions provide critical information that can be used for flood control and advanced disaster prevention preparations. However, total rainfall nowcasts (i.e., several days ahead) are not available in Taiwan when typhoons are distant. This paper proposes a long-distance total rainfall forecast (LTRF) model and presents a real-time forecasting process that can use the LTRF model to determine the formation and possible approach of typhoons in the future. The LTRF model was formulated using two designed climate scenarios. Scenario 1 considered El Niño–Southern Oscillation (ENSO) effects, whereas scenario 2 did not. Various raw sensor data, comprising climatological characteristics, sea surface temperature, satellite brightness temperatures, and total rainfall, were collected; moreover, attributes of the ENSO indices, in- cluding the Southern Oscillation index and the Niño-3.4 sea surface temperature anomaly, were reviewed. The scenario models were constructed using the C4.5 and random forest tree–based algorithms. Typhoon events occurring during 2001–13 and 2014–15 (specifically, Typhoons Matmo and Fung-Wong in 2014 and Soudelor and Dujuan in 2015) were examined for training and testing purposes, respectively. The Hualien Weather Station in Taiwan was selected as a study site, and the forecasting horizon was set at 6 h. Finally, the model simulations, observations, and Central Weather Bureau (Taiwan) nowcasts were compared. The simulation results showed that the proposed LTRF model, when ENSO effects were accounted for, can efficiently forecast total typhoon rainfall when typhoons are distant from Taiwan. 1. Introduction frequency and have become more extreme (Salinger et al. 2000). Although ENSO originates in the tropical Taiwan, an island with an area of 36 000 km2,liesin Pacific, it has a global effect on weather and climate. the main track of western North Pacific (WNP) Several scholars have studied the influences of ENSO on typhoons (Fig. 1). The typhoon season is a distinctive tropical cyclone (TC; synonymous with typhoon in this climatic characteristic of Taiwan. Several typhoons paper) activities in the WNP, including formation, track, make landfall in Taiwan every year, usually during late and intensity (Camargo and Sobel 2005; Camargo et al. summer and early autumn, although winter typhoons 2007; Chan 2000; Elsner and Liu 2003; Teng et al. 2014). also sometimes occur (Fan 2011). An average of 3.5 For example, Lander (1994) found that TCs are more typhoons pass near or over Taiwan annually. likely to form east of approximately 1608E during El El Niño–Southern Oscillation (ENSO) is the main Niño events, when sea surface temperatures (SSTs) in cause of climate variability at seasonal and interannual the central and eastern equatorial Pacific are higher than time scales. Climate state changes, usually characterized normal. Elsewhere, Chan (1985) and Teng et al. (2014) by a shift in means, can cause formerly rare events that have determined that typhoons tend to form farther to follow these mean changes to occur more frequently and the east in the WNP during El Niño years, and Wang and with increasing variability (Salinger 1994). ENSO is Chan (2002) indicated that the average maximum in- characterized by an interannual cooling (La Niña) and tensity of TCs is higher and lower in El Niño and La warming (El Niño) of the eastern equatorial Pacific Niña years, respectively, than in normal years. (Collins et al. 2010); however, since 1976, El Niño epi- Other research has demonstrated that the extreme sodes of the Southern Oscillation have increased in precipitation of typhoons, which may be affected by ENSO, leads to numerous casualties and consider- Corresponding author: Chih-Chiang Wei, [email protected] able economic loss. For example, Typhoon Soudelor DOI: 10.1175/JTECH-D-16-0216.1 Ó 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 09/27/21 04:00 AM UTC 2142 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 34 FIG. 1. Geographical location of Taiwan and the study site, with historical typhoon tracks. (7–9 August 2015) generated 1400 mm of rainfall in changes, and mesoscale changes in pressure, wind, and northeastern Taiwan, resulting in 12 fatalities and precipitation—are common and contribute to the challenge more than $100 million (U.S. dollars) in damage. of providing accurate quantitative typhoon precipitation Consequently, developing a model that includes the forecasts in Taiwan. For example, during the approach of effects of ENSO is crucial for predicting total rainfall Typhoon Soudelor in 2015, the CWB issued a rainfall in real time prior to a typhoon’s arrival in Taiwan, as nowcast ranging from 400 to 600 mm over the Hualien well as saving both human lives and resources. County plain (eastern Taiwan); by contrast, the actual total In Taiwan, the Central Weather Bureau (CWB) issues rainfall was 199 mm. Total rainfall nowcasting is also non- ‘‘Typhoon Warning over Ocean’’ (TWO) alerts every existent when a typhoon is several days away from Taiwan. 3 h when a typhoon is expected to affect Taiwan within However, long-distance total rainfall nowcasting is essential 24 h. Subsequently, ‘‘Typhoon Warning over Ocean and for enabling the residents of Taiwan to make appropriate Land’’ (TWOL) alerts are issued every hour when a flood control and disaster prevention preparations. typhoon is expected to land or affect the region within Improvements in both computer capability and algorithm 18 h. Within those final 18 h, the CWB also nowcasts the efficiency have made real-time typhoon rainfall prediction total precipitation. Because of high climatological un- models increasingly useful for water resource management certainty, the rainfall prediction provided by the CWB (Wu et al. 2010; WuandChau2013). Antolik (2000), is a range; however, these ranges are not always accu- Madsen et al. (2014), Maier and Dandy (2000), Michaelides rate. At present, the CWB employs an ensemble fore- et al. (2009),andScofield and Kuligowski (2003) have casting method that is dynamic and flow dependent to conducted in-depth reviews of rainfall prediction models, quantify and communicate forecast uncertainty. How- covering an extensive range of research on this topic. In ever, CWB total rainfall nowcasts often have high pre- Taiwan, numerous studies have also successfully addressed diction errors. These errors are primarily attributable to rainfall prediction and identification problems for typhoons the island’s Central Mountain Range (CMR). The CMR affecting Taiwan in real time (Chang et al. 2013; Hong et al. is 340 km long and 80 km wide, with an average height of 2015; Kuo et al. 2016; Wang et al. 2016; Wei 2013; Wei et al. 2500 m. As a typhoon approaches Taiwan, the CMR 2015). For example, Kuo et al. (2011) built a dynamic time influences its track and intensity: specifically, the to- series model for long-term extreme rainfall to investigate pography increases the rainfall amount significantly by common trends in annual maximum precipitation. Wei and lifting moist air over the windward side of the moun- Roan (2012) addressed the rainfall retrieval problem for tains. Hong et al. (2015) found that significant mesoscale quantitative precipitation forecasting over land during ty- variations caused by orographic effects—including phoons. More recently, Lin and Jhong (2015) developed track deflection, secondary low development, intensity typhoon rainfall forecasting models that yield 1–6-h Unauthenticated | Downloaded 09/27/21 04:00 AM UTC OCTOBER 2017 W E I 2143 advanced hourly rainfall predictions for southern Taiwan. tasks because of their ease of use, interpretability, and In addition, Lo et al. (2015) developed an artificial neural ability to deal with covariates measured at different levels network–based model for forecasting precipitation in (Lariviere and den Poel 2005).TheC4.5algorithmwas eastern Taiwan, using an automatic calibration approach introduced by Quinlan (1993) and uses a divide-and- to adjust the training parameters. conquer approach to grow decision trees. Conversely, the The purpose of this study was to develop a model that RF algorithm developed by Breiman (2001) is an ensemble can predict the total rainfall during a typhoon when the of classification trees; the theorems of this algorithm are storm is still several days away from Taiwan. The con- presented in section 3b. Both the C4.5 and RF decision cept used in this paper is inspired by the previous work trees have been utilized to address numerous civil and of Wei (2014), who predicted the hourly rainfall during a oceanic engineering and atmospheric science problems. For typhoon invasion in Taiwan. Wei (2014) used meteoro- example, the C4.5 has been adopted to study water reservoir logical and radar reflectivity data to simulate the oper- control (Bessler et al. 2003; Wei and Hsu 2008, 2009), wave ational forecasting of real-time hourly rainfall for height prediction (Mahjoobi and Etemad-Shahidi 2008), developing a rainfall forecasting model for
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