Abstract
GEOMATICS, NATURAL HAZARDS AND RISK 2023, VOL. 14, NO. 1, 2208722 https://doi.org/10.1080/19475705.2023.2208722 Statistical analysis of the characteristics of typhoons approaching Japan from 2006 to 2019 Sridhara Nayak and Tetsuya Takemi Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan ABSTRACT ARTICLE HISTORY Received 28 February 2022 This study investigated the characteristics of 60 typhoons Accepted 25 April 2023 approaching Japan over the past 14 years (2006–2019) by con- ducting statistical analysis of their temporal evolution, active KEYWORDS hours, intensity, frequency, size, duration, and translation speed. Typhoon; typhoon intensity; By dividing the time period into the earlier (before 2012) and the typhoon hazard; most recent (after 2013) years, the analysis indicated that the environmental conditions; annual frequency of typhoons is higher in the most recent years climate change than in the earlier years. The typhoons in recent years took rela- tively less time to reach Japan and remained active for shorter time over the land are of Japan than those in the earlier years. The intensity of the typhoons in the recent years showed stronger winds and considerably lower pressures at the landfall time than that in the earlier years. Typhoons in recent years carry more fre- quent and intense rainfall compared to those in the earlier years in this study. The analysis inferred that the higher sea surface temperature, weaker vertical wind shears, and a larger amount of moisture around the centers of the recent typhoons were respon- sible for making them stronger. 1. Introduction Tropical cyclones (TCs), also known as hurricanes, typhoons, or cyclones depending on the region, are among the most devastating natural disasters in the world. These TCs generally form over warm ocean surface near the equator and cause significant socio-economic damages when they make landfall in populated areas (Aon Benfield 2016). TCs have caused significant damages, and losses of lives and properties in many countries across the world. In Bangladesh, frequent TCs caused notable damage and displacement, specifically with Cyclone Sidr in 2007 and Cyclone Amphan in 2020 (Paul 2010; Hassan et al. 2020; Ahsan and Ozbek 2022). The Philippines is also highly vulnerable to TCs, for instance, Super Typhoon Haiyan in 2013 caused signifi- cant damages and losses of lives and properties (Takayabu et al. 2015; Takagi and Esteban 2016). In the United States, storms such as Hurricane Katrina in 2005 and CONTACT Sridhara Nayak nayak.sridhara@n-kishou.co.jp 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 S. NAYAK AND T. TAKEMI Hurricane Sandy in 2012 caused significant damages and alerted the need for improved preparedness and response measures (Padgett et al. 2008; Halverson and Rabenhorst 2013; Xian et al. 2015; Gall and Cutter 2019). The Caribbean islands are also highly vulnerable to TCs, for instance, Hurricane Maria in 2017 caused substan- tial damages, and losses of lives and properties in Puerto Rico and other islands (Cox et al. 2019; Kim and Bui 2019). These cases illustrate the significant impacts that TCs can have on different countries and regions, and highlight the need for further research and preparedness measures to mitigate the risks of future storms. In Japan, typhoons are responsible for causing significant damage each year, which includes the threat to human life, destruction of infrastructure, and damage to agri- culture (Aon Benfield 2016; Takemi et al. 2016a; Guan et al. 2018). In recent decades, more typhoons have made landfall and some have increased in intensity, resulting in prominent typhoon-related losses of lives, crops, and infrastructure (Mei et al. 2015; Hornyak 2020; Yamaguchi and Maeda 2020). As a result, several studies have focused on understanding typhoon characteristics from disaster prevention and mitigation perspectives, including the changes in typhoon frequency, formation, development, structure, and intensity in recent decades or future changes due to climate change (Ishikawa et al. 2013; Mei and Xie 2016; Takemi et al. 2016b, 2016c; Zhan et al. 2017; Gao et al. 2018; Kamahori and Arakawa 2018; Kanada et al. 2019; Nayak and Takemi 2019a, 2019b, 2020a; Hatsuzuka et al. 2020; Nayak and Takemi 2020b). These studies highlight the need for continued research and improved disaster prevention and miti- gation measures to mitigate the risks posed by typhoons in Japan. According to Yamaguchi and Maeda (2020), the number of typhoons approaching the southern coast of Japan has increased from 1980 to 2019 due to favorable envir- onmental conditions for typhoon development. As a result, the number of typhoons forming over the western North Pacific region has also increased, leading to more landfalls in Japan. Mei and Xie (2016) found that typhoons striking east and south- east Asia have intensified by 12%–15% between 1977 and 2014. Several studies have investigated the effects of climate change on individual typhoons, including Typhoon Vera (1959), Mireille (1991), Songda (2004), Talas (2011), Haiyan (2013), Lionrock (2016), Jebi (2018), and Hagibis (2019), to understand their severity if similar typhoons occur in the future with a warming climate (Takayabu et al. 2015; Ito et al. 2016; Takemi et al. 2016b, 2016c; 2019; 2019; Nayak and Takemi 2019a, 2019b; Takemi and Unuma 2020). Hatsuzuka et al. (2020) indicated that typhoon-induced extreme precipitation is likely to increase throughout Japan under a 4 K warmer cli- mate. These studies indicated that the characteristics of typhoons approaching Japan have changed in recent years and are projected to change in their intensity and impacts under future climate changes. However, the detailed characteristics of typhoons such as the temporal evolution, duration, geographical locations over Japan are not well documented in observational or modeling studies. Similarly, the dura- tions and frequencies of typhoon-associated rainfall over Japan have not been thor- oughly explored. Understanding these features of approaching typhoons, especially in recent years, is crucial for disaster prevention and mitigation of typhoon-related haz- ards in Japan. GEOMATICS, NATURAL HAZARDS AND RISK 3 This study aimed to investigate several characteristics of typhoons, i.e. TCs that occur in the western North Pacific Ocean, specifically those that approached or passed over Japan from 2006. The reason for selecting 2006 as the starting year for the analysis period is due to the availability of high-quality precipitation data for the Japanese islands from radar-raingauge products, which have been available since 2006 (explained more about this data in Section 2). The characteristics examined include: what was the duration of typhoons when they were active over Japan land; how did the strength and location of typhoons change as they approached or passed over Japan; what was the frequency of typhoons during the study period; what was the duration and size of typhoons as they approached or passed over Japan; how fast did typhoons move across the ocean and towards Japan; and finally, are there any changes in the typhoon characteristics from an earlier to a later period? This study also examined the environmental conditions that might influence typhoon develop- ment and intensification. These factors include sea surface temperature (SST), which affects the amount of heat energy available for typhoon intensification; moisture, which impacts the formation and structure of typhoons; and vertical wind shear, which disrupts or enhances typhoon formation and growth. 2. Data and methods We examined typhoons that approached and/or landed Japan between 2006 and 2019 from the Regional Specialized Meteorological Center (RSMC) Tokyo best-track data- sets, the China Meteorological Administration (CMA) tropical cyclone best-track datasets (Ying et al. 2014; Lu et al. 2021), and the Joint Typhoon Warning Center (JTWC) Western North Pacific Ocean best-track datasets. We chose to focus on a specific subset of typhoons that could have the greatest impact on Japanese land- masses. We selected a total of 60 typhoons that met specific criteria. These typhoons either made landfall or passed within 100 kilometers of a Japanese landmass and did not weaken before making landfall, with a maximum wind speed of 15 m s or higher. Typhoons that decayed or weakened before making landfall were not included in the study as their impact was assumed to be negligible. Table 1 shows the detailed information of the 60 typhoons. In order to analyze the paths taken by typhoons, we used data on the latitude and longitude positions of the storm at regular intervals between 1 and 6 h. The exact interval used likely depended on the availability of the data, as it may not be possible to collect data on a storm’s position every hour in all cases. We calculated the center of the storm based on the available latitude and longitude data at 6-h intervals. To analyze the intensity of a typhoon, we used the maximum wind speed (the highest speed at which the wind is blowing within the typhoon) and minimum central pres- sure (the lowest atmospheric pressure at the center of the typhoon) at 6-h intervals. The latitudinal and longitudinal locations of each typhoon center were also investi- gated in 6-h intervals to analyze its track. The annual frequencies of typhoons were calculated by counting the number of typhoons per year that met the defined criteria for inclusion in this study. To calculate the time for each typhoon to reach land, we estimated the duration from the initiation point of the typhoon, which is the location 4 S. NAYAK AND T. TAKEMI Table 1. List of typhoons with maximum intensity from RSMC best-track datasets. International Maximum wind Minimum central Sl. No. Year Number ID Name speed (knots) pressure (hPa) 1 2006 0607 Maria 70 975 2 0610 Wukong 50 980 3 0613 Shanshan 110 919 4 2007 0704 Man-Yi 95 930 5 0705 Usagi 90 945 6 0709 Fitow 70 965 7 2008 0813 Sinlaku 100 935 8 2009 0909 Etau 40 992 9 0911 Krovanh 60 975 10 0918 Melor 110 910 11 2010 1004 Dianmu 50 985 12 1007 Kompasu 80 960 13 1009 Malou 50 992 14 1014 Chaba 95 930 15 2011 1102 Songda 105 920 16 1106 Ma-On 95 935 17 1112 Talas 50 970 18 1115 Roke 85 940 19 2012 1204 Guchol 100 930 20 1216 Ganba 110 900 21 1217 Jelawat 110 905 22 2013 1318 Man-Yi 65 960 23 1324 Danas 90 935 24 1326 Wipha 90 930 25 2014 1408 Neoguri 100 930 26 1411 Halong 105 920 27 1418 Phanfone 95 935 28 1419 Vongfong 115 900 29 2015 1511 Nangka 100 925 30 1515 Goni 100 930 31 1518 Etau 50 985 32 2016 1606 Conson 45 985 33 1607 Chanthu 55 980 34 1609 Mindulle 65 975 35 1610 Lionrock 90 940 36 1611 Kompasu 35 994 37 1612 Namtheun 70 955 38 1616 Malakas 95 930 39 1618 Chaba 115 905 40 2017 1703 Nanmadol 55 985 41 1705 Noru 95 935 42 1718 Talim 95 935 43 1721 Lan 100 915 44 1722 Saola 60 975 45 2018 1807 Prapiroon 65 960 46 1812 Jongdari 75 960 47 1813 Shanshan 70 970 48 1815 Leepi 50 994 49 1819 Soulik 85 950 50 1820 Cimaron 85 950 51 1821 Jebi 105 915 52 1824 Trami 105 915 53 1825 Kong-Rey 115 900 54 2019 1903 Sepat 40 994 55 1906 Nari 35 998 56 1908 Francisco 70 970 57 1910 Krosa 75 965 58 1915 Faxai 85 955 59 1917 Tapah 65 970 60 1919 Hagibis 105 915 GEOMATICS, NATURAL HAZARDS AND RISK 5 where the storm begins to form until it reaches a distance of 200 km from Japan. Once the typhoon center is within 200 km of Japan, its active period over Japan is computed from the time taken by each typhoon’s center to travel between 200 km from land and after passing Japan. This is because typhoons can have different inten- sities and effects depending on their distance from land and their trajectory over Japan. In this study, the rainfall amounts associated with each typhoon were com- puted based on the longest radius of 15 m s or higher winds from the typhoon cen- ter. This radius is often referred to as R 15. However, the R 15 information was L L taken from the RSMC best-track datasets only for this particular analysis as it was not available in the other two datasets used in the study. To determine the rainfall amount associated with each typhoon, we utilized observed rainfall product generated by combining radar and raingauge observations, called radar/raingauge analyzed precipitation data (Nagata 2011). This rainfall product provides gridded, accurate precipitation fields throughout the Japanese islands. The horizontal resolution has upgraded in the past; the current data have spatial reso- lution of 1 km, which is available since 2006. In order to take advantage of this high- resolution precipitation data, the analysis period is set to be after 2006. The time period of the data is 1 h. This high-resolution precipitation data is a valuable source of information about the intensity and spatial distribution of rainfall associated with typhoons. With the aid of high-resolution precipitation data, it is possible to obtain more accurate information about the heaviest rainfall and their frequency. This infor- mation can help local authorities and emergency responders to prepare for and respond to the storm more effectively. In order to assess the severity of recent typhoons, we divided our data into two distinct periods of seven years each, covering the periods of 2006 to 2012 (hereafter referred to as "earlier years") and 2013 to 2019 (hereafter referred to as ‘recent years’). We then analyzed the temporal evolution of various typhoon characteristics, includ- ing maximum wind speed, minimum central pressure, translation speed, size, and rainfall amount, for each typhoon in both time periods, as well as the mean features for each period. These two periods were chosen because the years between 2013 and 2018 are among the six warmest on record between 1880 and 2018 (Arguez et al. 2020). Additionally, the period 2014–2016 was characterized by the occurrence of El Nino-Southern Oscillation (ENSO). ENSO can also impact the intensity of storms. For example, during El Nino ~ events, there is a trend of a decrease in the intensity of TCs in the Atlantic basin (Landsea et al. 2010), while the opposite is true for the western Pacific basin (Fudeyasu et al. 2006). Research studies have provided evidence for the impact of ENSO on TCs (Girishkumar et al. 2015; Zhao and Wang 2019: Albert et al. 2022; Song et al. 2022). Hence, it is of interest to examine the behavior of typhoons between 2013 and 2019 and compare it with another 7-year period (2006–2012). To investigate changes that may have occurred in recent years, we ana- lyzed the mean properties of various typhoon variables at 6-h intervals, and compared the results between the two time periods. The rainfall durations and associated rainfall amounts were explored by categoriz- ing the independent rainfall durations caused by each typhoon into different duration bins. Here, an independent rainfall duration refers to a continuous period of rainfall 6 S. NAYAK AND T. TAKEMI over Japanese land while a typhoon passed. The rainfall duration samples collected from each typhoon were independent. Hence, we considered the accumulated rainfall in each independent duration and explored their frequencies. The environmental con- ditions during the time evolution of each typhoon and the mean features in the two periods were examined by analyzing the 3-h surface brightness temperature as SST, 6-h vertical wind shear between 850 and 300 hPa, and 3-h precipitable water from the 55-year Japanese Reanalysis (JRA-55) data (Kobayashi et al. 2015). These features were investigated in 6-h intervals in the R 15 regions from the typhoon center. The spatial differences in these features were investigated by averaging SST, wind, and moisture field for each period. The mean values at 6-h intervals were compared between two time periods in order to investigate any changes that may have occurred in recent years. The mean values of certain variables (e.g. wind speed, precipitation) were calculated at 6-h intervals for each of the two time periods under consideration. The mean value here was the average of all the values collected over a specific time interval. By comparing the mean values at 6-h intervals, we aimed to detect any sig- nificant changes in the variables of interest over time for understanding the charac- teristics and impacts of the recent typhoons. The Student’s t-test is used to assess the significance of differences between the two time periods. The null hypothesis (H ) assumes that there is no change, with a significance level of 95%. This means that if the calculated p-value from the t-test is less than 0.05, we can reject the null hypoth- esis and conclude that there is a significant difference between the two periods. 3. Results First, we analyzed the tracks of the 60 typhoons, their annual frequencies, and time durations. Next, we evaluated the intensities and locations of these 60 typhoons. We also investigated the temporal evolution of the intensity, translation speed, location, and size. Finally, we discussed the intensity and rainfall duration of typhoons in recent years and the associated environmental conditions. 3.1. Typhoon tracks, frequencies, and time durations Typhoons approaching Japan between 2006 and 2019 were mostly formed in the region of 5–15 N and initially moved northwestward before recurving and moving northeastward towards the southern coast of Japan (Figure 1). The term ‘recurving of TCs’ refers to the process where a storm initially moving westward/northwestward turns towards the north or northeast and begins moving in that direction, which is common in the western North Pacific basin. During this period, most typhoons made landfall on the Pacific Ocean side of Japan, with more landfall occurring on that side than the Sea of Japan side. All three best-track datasets, namely RSMC, CMA, and JTWC, showed similar tracks until the typhoons reached the Hokkaido region. The JTWC best-track datasets did not typically show tracks over Hokkaido, while the RSMC and CMA best-track datasets showed tracks over Hokkaido, but the CMA best-track datasets showed tracks mostly up to 155E after landfall. GEOMATICS, NATURAL HAZARDS AND RISK 7 Figure 1. Track of 60 typhoons from (a) RSMS, (b) CMA, and (c) JTWC best-track datasets. The annual frequencies of the typhoons between 2006 and 2019 indicated that the occurrence of the typhoons substantially increased in recent years, especially after 2015 (Figure 2). Prior to 2015, there were approximately four typhoons, but the num- ber has almost doubled in recent years. The 5-year moving averages computed from the previous 5-points and center ±2-points along with the linear trend of the frequen- cies showed a steady increase in typhoons approaching Japan in recent years. Previous studies on the global tropical TCs (Kossin et al. 2020) also highlighted sig- nificant increases in the frequency of TCs making landfall. Takagi and Esteban (2016) reported that the frequency of TCs making landfall over the Philippines increased 0.02 times per year between 1945 and 2013 and most TCs made landfall in the 10– 12 N latitudinal region. Most typhoons during 2006–2019 took 5–8 days, on average, to reach Japan and remained active for 1–3 days over Japan (Figure 2b). A few typhoons took longer to reach Japan (>8 days) and remained active over land for a longer duration (>3 days) (Figure 2c). The reason could be associated with the translation speed, which may be slower in long-lived typhoons. All three best-track datasets yielded similar results. However, JTWC showed a slight variation, which may be due to its insufficient infor- mation over the Hokkaido region. 3.2. Intensities and locations We analyzed the intensity of the 60 typhoons in 6-h intervals from their initiation (T¼ 0) until their decay in terms of the relationship between maximum wind speed and minimum central pressure (Figure 3a). Typhoons approaching Japan between 2006 and 2019 possessed a maximum wind speed of 20–60 m s in the RSMC best- track datasets, while they showed maximum wind speeds of 15–70 m s and 10– 75 m s in the CMA and JTWC best-track datasets, respectively. The typhoons approaching Japan possessed a minimum pressure between 900 and 1005 hPa in all three best-track datasets. The mean intensities of all the typhoons analyzed in 6-h intervals showed a maximum wind speed up to 40 m s and a minimum pressure above 955 hPa. Most typhoons brought hourly rainfall up to 6 mm in the R 15 regions over Japan. A few typhoons carried heavy rainfall up to 18 mm h (Figure 3b). The mean 8 S. NAYAK AND T. TAKEMI Figure 2. (a) Annual frequency of typhoons; (b) Time taken by typhoons to reach the Japanese landmass from their initiation; and (c) Duration of typhoons while active over Japan. The smooth lines (dotted/solid) in (b-c) represent the annual mean durations. rainfall intensities associated with these typhoons were mostly 3 mm h averaged in the R 15 regions over land. Figures 3(c,d) illustrate the latitudinal and longitudinal locations of the typhoons in 6-h intervals. Typhoons approaching Japan between 2006 and 2019 originated between 5 and 25 N latitude and 125 and 170E longitude. Most passed through 20–40 N and 125–145E within 7–8 days. All three best-track datasets indicated similar locations with a 1–2 variation and had the same mean latitudinal locations up to 7 days. This indicated that the typhoons which approached GEOMATICS, NATURAL HAZARDS AND RISK 9 Figure 3. (a) Typhoon intensity (wind speed vs. central pressure) and (b) hourly rainfall amount within R 15 (longest radius of wind 15 m/s from the typhoon center) along the track of each typhoon over Japan land. (c) The latitudinal and (d) longitudinal location of each typhoon at each 6-hours interval. The rainfall intensity in (b) correspond to results calculated with RSMC best-track locations. The bold lines represent the mean values of various typhoon characteristics at each time step. and/or landed the Japanese islands do not simultaneously approach and/or made landfall on coastal areas in the East Asian continent. 3.3. Temporal evolutions The analysis of wind speed and central pressure indicated that typhoons during th 2006–2019 showed peak intensities around the 5 day after their initiation. The max- imum wind speeds were 60, 70, and 75 m s in the RSMC, CMA, and JTWC best- track datasets, respectively (Figure 4a–c). The typhoons showed a minimum central pressure of 900 hPa in all three datasets (Figure 4d–f). The translation speed of each typhoon was calculated in 6-h intervals from the time and distance traveled in ±6 h (Figure 5a–c). Typhoons approaching Japan between 2006 and 2019 typically traveled at a speed of 2–10 m s . However, a few traveled at much faster speeds (>20–25 m s ). The translation speed of typhoons was nearly constant from their initiation until th their decay, but a few typhoons had an increased speed on the 5 day. All the three best-track datasets gave similar translation speeds. In all three best-track datasets, the typhoons between 2006 and 2019 approaching Japan originated in 5–25 N latitude. However, typhoons traveled at higher latitudes up to 60 N in RSMC and CMA datasets. The same trend was noted up to 42 N in the JTWC best-track datasets (Figure 5d–f). In all best-track datasets, the typhoons 10 S. NAYAK AND T. TAKEMI Figure 4. Time evolution of wind speed (upper panel) and minimum central pressure (lower panel) from (a, d) RMSC, (b, e) CMA and (c, f) JTWC best-track datasets during 2006–2019. The open circle represents the magnitude at each time step for the periods 2006–2012 (in blue) and 2013–2019 (in red). The solid blue (red) lines correspond to the mean magnitude at each time step for the period 2006–2012 (2013–2019). Figure 5. Time evolution of translation speed (upper row), latitudinal location (middle row) and longitudinal location (lower row) from (a, d, g) RMSC, (b, e, h) CMA and (c, f, i) JTWC best-track datasets during 2006–2019. The open circle represents the magnitude at each time step for the periods 2006–2012 (in blue) and 2013–2019 (in red). The solid blue (red) lines correspond to the mean magnitude at each time step for the period 2006–2012 (2013–2019). GEOMATICS, NATURAL HAZARDS AND RISK 11 originated in 125–170E. After making landfall, they went beyond 170E in RSMC data- sets, but they mostly went up to 155E in the other two datasets (Figure 5g–i). The size of the typhoons with R 15 was observed frequently 200–600 km during 2006– 2019, although a few were up to 1,000 km (Figure 6a). 3.4. Characteristics of typhoons in recent years To understand the characteristics of typhoons over Japan in the recent years, we compared the intensity, translation speed, location, size, duration, and associated rain- fall of typhoons in the earlier years (2006–2012) with those in the recent years (2013– 2019). In Figure 4, it is seen that the intensity (maximum wind speed and minimum central pressure) of the typhoons in the two periods were mostly the same from the date of their initiation until the 8th day; after the 8th day, recent typhoons showed stronger winds and lower minimum pressures. All the three best-track datasets pro- vided qualitatively similar results, but the JTWC best-track datasets quantitatively showed higher wind speeds. The student’s t-test was used to evaluate the 95% statis- tical significance of the mean difference in the intensities of the typhoons for the two periods. The mean intensity in terms of wind and central pressure of recent typhoons was significantly higher (lower in case of central pressure) than that of earlier Figure 6. Time evolution of (a) typhoon size and (b) rainfall amount with R 15 along the typhoon track at RMSC best-track location during 2006–2019. The open circle represents the magnitude at each time step for the periods 2006–2012 (in blue) and 2013–2019 (in red). The solid blue (red) lines correspond to the mean magnitude at each time step for the period 2006–2012 (2013–2019). 12 S. NAYAK AND T. TAKEMI typhoons (p< 0.05). Mei et al. (2015) also highlighted an increasing trend in the intensity of TCs over the western North Pacific during 1950–2010. Other studies also noted increased TC intensities in recent decades (Mei and Xie 2016; Yoshida et al. 2017; Song et al. 2018; Yamaguchi and Maeda 2020). The translation speeds were not significantly different between the two periods among the three best-track datasets. Here the student’s t-test did not yield a statistic- ally significant result at the 95% level of confidence. There are some variations in the differences of the translation speed on different days in the RSMC, CMA, and JTWC datasets (Figure 5a–c). Recent studies (e.g. Kim et al. 2020) have highlighted that the translation speed of TCs has increased, whereas other studies (e.g. Chan 2019; Kossin et al. 2020) reported that the TC translation speed decreased. Our overall analysis did not find any significant changes in the translation speed of typhoons approaching Japan between 2006 and 2019 until they made landfall. Thus, it is difficult to provide a definite conclusion on this point. The latitudinal locations of the typhoons did not show noticeable changes from their initiation until decay between the two periods in the RSMC and CMA best-track datasets. By contrast, that in the JTWC best-track datasets showed 2–5 lower lati- tudes after the 10th day in recent years (Figure 5d–f). The longitudinal locations of the typhoons were at 5 lower longitudes from their initiation until the 5–7th day in recent years, but the changes during the 8–12th day were negligible (Figure 5g–i). None of the datasets showed clear changes in the longitudinal locations for typhoons active over Japan. Additionally, the typhoon size in the RSMC data did not show sub- stantial changes between the two periods (Figure 6a). The rainfall intensity within the R 15 region over Japan in the two periods indicated almost the same magnitudes (Figure 6b). However, typhoons in earlier years showed rainfall until the 12th day, while rainfall continued even after the 12th day for typhoons in recent years. Figure 7a depicts the rainfall duration and the total rainfall along the RSMC tracks of the 60 typhoons over the Japanese landmass. The rainfall duration refers to continuous hours of rainfall along the track within the R 15 region over Japan. Typhoons approach- ing Japan between 2006 and 2019 brought rainfalls on various time scales with a total amount up to 300 mm. Our analysis showed that, although the frequency of typhoons in recent years was higher (Figure 7a), they broughta slightly lower amountof total rainfall, up to 270 mm. However, typhoons in the recent years caused more frequent rainfall events lasting up to 3 days (Figure 7b), and more frequent total rainfall amounts up to 250 mm than those in the earlier years (Figure 7c). These analyses indicate that typhoons are more intense in the recent years than in the earlier years in terms of maximum wind speed and minimum central pressure. However, in terms of overall rainfall intensity, there is no noticeable change. Notably, typhoons approaching Japan in the recent years have been associated with more frequent rainfall events that last up to 3 days, with a total rainfall amount of up to 250 mm. 4. Discussion Overall results indicated that that the typhoons in recent years are associated with stronger winds and longer lifespan compared to those in earlier years. To GEOMATICS, NATURAL HAZARDS AND RISK 13 Figure 7. (a) Duration versus total rainfall amount (accumulated in each duration), and frequency of (b) duration and (c) total rain during 2006–2012 and 2013–2019. comprehend the mechanism of this severity of typhoons in recent years, we compared the environmental conditions, including SST (Figure 8), vertical wind shear (Figure 9), and moisture (Figure 10) for typhoons approaching Japan between the two peri- ods. The best-track data from RSMC were used here. The time evolution of the mean th SST did not show significant differences between the two periods until the 8 day after initiation. Then SSTs within the typhoon regions were higher in recent years than those in earlier years (Figure 8a). The spatial distribution of the mean SST between 2013 and 2019 showed a higher SST in typhoon active areas over the Pacific Ocean and the Sea of Japan compared to that between 2006 and 2012 (Figure 8b), indicating that warm SST intensified typhoons and prevented decay in recent years 14 S. NAYAK AND T. TAKEMI Figure 8. (a) Time evolution of surface brightness temperature with R 15 along each typhoon dur- ing 2006–2012 and 2013–2019, and (b) spatial distribution of their mean change. Dotted regions indicate 95% significance level. Figure 9. (a) Time evolution of vertical wind shear between 850 hPa and 300 hPa with R 15 along each typhoon during 2006–2012 and 2013–2019, and (b) spatial distribution of their mean change. Dotted regions indicate 95% significance level. Figure 10. (a) Time evolution of precipitable water with R 15 along of each typhoon during 2006– 2012 and 2013-2019, and (b) spatial distribution of their mean change. Dotted regions indicate 95% significance level. GEOMATICS, NATURAL HAZARDS AND RISK 15 (Sun et al. 2017; Mohanty et al. 2019). Takagi and Esteban (2016) also documented that warm SST played an important role in intensified Typhoons Haiyan and Zeb. The time evolution of the vertical wind shear between 850 and 300 hPa indicated that typhoons in recent years were associated with relatively lower vertical wind shears on the 3rd–6th, 8th, and 11th day onwards compared to those in earlier years, indicating more favorable conditions for the intensification and maintenance of typhoons (Figure 9a). Wang et al. (2015) also highlighted that the rapid intensified TCs over the western North Pacific possess relatively weaker vertical wind shear. Fudeyasu et al. (2022) found that the Typhoon Faxai (2019) reached the tropical storm intensity when the vertical shear decreased. We find that the spatial mean dif- ference between the two periods indicated much lower vertical wind shears over the region where most typhoons formed (150–160E and 10–20 N) and over the regions before and after they approached land (121–140E and 22–30 N) (Figure 9b). When the wind shear is low, it not only creates a more stable environment for tropical storms to develop, but also beneficial for various sectors such as aviation as they can reduce turbulence, leading to smoother flights and safer conditions for pilots and pas- sengers. Low wind shear conditions can lead to better oceanic conditions, such as calmer seas and reduced upwelling, which can improve fishing conditions. Low wind shear can create a more stable atmosphere, reducing the chance of severe thunder- storms, hail, and tornadoes. Low wind shear can improve air quality by reducing the mixing of pollutants in the atmosphere. When winds are weak, pollutants can accu- mulate in the same area, leading to poor air quality. The time evolution of mean moisture showed a similar pattern as that of SST, but the spatial mean difference of moisture between the two periods over the regions of typhoon formation and southern Japan showed a pattern similar to that of vertical wind shear. The amount of moisture was almost the same from initiation to the 8th day. After the 8th day, it was higher in recent years (Figure 10a). Higher moisture availability was also noticed over the region where a much lower vertical wind shear was observed in recent typhoons (Figure 10b). Takemi et al. (2019) investigated the impacts of future climate change on typhoon intensities and the resulting hazards by conducting pseudo-global warming experi- ments on Typhoon Talas (2011). They found that a significant increase in precipitable water vapor contributed to the intensification of heavy rainfalls generated by a typhoon. Recent extreme typhoons and rainfall events (Takemi and Unuma 2019, 2020) had a much larger moisture content than the climatological amount from past observations (Unuma and Takemi 2016). Thus, the environmental moisture content seen for typhoons in recent years and the conditions in other recent extreme events appear to signal that a warmed climate state anticipated to occur in the future has already begun. The El Nino/Southern ~ Oscillation (ENSO) may be another cause for strengthening the typhoons during 2013–2019. Because the years 2014–2016 were El Nino ~ years and may contribute to stronger typhoons during this period. Multitudes of studies have examined the relationship between TC genesis and ENSO and have provided the evi- dences supporting the ENSO effect on strengthening the TC (Girishkumar et al. 2015; Zhang et al. 2018; Zhao and Wang 2019: Albert et al. 2022; Song et al. 2022). 16 S. NAYAK AND T. TAKEMI In the El Nino years, the water temperature over Pacific Ocean remains warmer than other years which creates low vertical shear. This provides a favorable environment for typhoon formations and their maintenance for longer lifespan (Patricola et al. 2018; Wang and Li 2022). In a study, Fudeyasu et al. (2006) reported that the typhoons over Japan during El Nino ~ years tend to have stronger intensities and lon- ger lifespan. The impact of ENSO on typhoons during the period 2006–2019 may have played a similar role towards strengthening the typhoons in recent years. However, it’s worth noting that not all studies have found a significant impact of ENSO on TC intensity. For example, a study by Chan (2005) found no significant correlation between El Nino ~ events and the intensity of TCs in the western North Pacific. Overall, the impact of ENSO on TC intensity is complex and varies depend- ing on a range of factors. More research is needed to fully understand the mecha- nisms underlying this relationship. 5. Conclusions and recommendations In this study, 60 typhoons that approached Japan in the past 14 years (2006–2019) were analyzed to explore their temporal evolution, active hours, intensity, latitude, longitude, frequency, size, duration, and translation speed. Typhoons carried winds up to 60 m s around the 5th day after typhoon initiation and had central pressures as low as900hPa. Most typhoonsduring thisperiod traveled at a speed of 2–10 m s with thesizeof 200–600 km within the R 15 region. However, the annual frequency of the recent typhoons increased substantially compared to earlier years. In fact, it almost doubled after 2015. Most typhoons between 2006 and 2019 took an average of 5–8 days to reach Japan and an additional 1–3 days to travel through Japan. Some typhoons took longer to reach Japan (>8 days) and remained over land for longer (>3 days). Typhoons in recent years showed stronger winds and considerably lower pressures at landfall com- pared to those in earlier years. Recent typhoons also brought frequent continuous heavy rainfalls up to 250 mm total rainfall with a duration of up to 3 days. This implies that typhoons in the near future may be a serious concern and a threat to human lives and properties. ENSO effect may be a possible cause for this due to its influential interplay in the Pacific Basin. Many previous studies highlighted about the influence of ENSO towards strengthening the TCs. To understand the mechanism for stronger typhoons with heavy rainfall in recent years, we analyzed the SST, vertical wind shear between 850 and 300 hPa, and the precipitable water between the two periods. Environmental conditions in recent years such as higher SST, rela- tively lesser vertical wind shears, and increased availability of moisture around the typhoon centers have become more favorable to the development of typhoons, mak- ing them stronger. These findings provide valuable information to assess the potential impacts of approaching typhoons in Japan and devise effective adaptation strategies. The study’s results can also be used to evaluate model simulations that assess typhoon activities under warming conditions. However, due to the short length of the analyzed data (only 14 years), drawing a definitive conclusion about climate change would be GEOMATICS, NATURAL HAZARDS AND RISK 17 speculative. Therefore, further investigation using historical and future data is recom- mended, focusing on anomalies such as unusual strength, direction, and track that may be responsible for potential damages. By studying these factors, we can better understand and prepare for the impacts of future typhoons. Acknowledgments The authors would like to thank the comments by anonymous reviewers for improving the original manuscript. This study was supported by the Integrated Research Program for Advancing Climate Models (Grant Number JPMXD0717935498) funded by the Ministry of Education, Culture, Sports, Science and Technology of Japan and the Environment Research and Technology Development Fund (Grant Number JPMEERF20192005) of the Environmental Restoration and Conservation Agency. The Japan Meteorological Agency (JMA) is acknowl- edged for providing the Radar/Rain gauge: Analyzed Precipitation product. The RSMC Tokyo (https://www.jma.go.jp/jma/indexe.html), the CMA Tropical Cyclone Data Center (https:// www.typhoon.org.cn), and the JTWC (https://www.metoc.navy.mil/jtwc/jtwc.html?best-tracks) are recognized for providing the best-track datasets. Authors’ contributions SN proposed the topic, designed the study, analyzed the data and drafted the manuscript. TT helped in the interpretation and the construction of the manuscript. SM helped in analyzing data. All authors read and approved the final manuscript. Disclosure statement No potential conflict of interest was reported by the authors. Funding This study was supported by the TOUGOU program Grant Number JPMXD0717935498 and the advanced studies of climate change projection (SENTAN) Grant Number JPMXD0722678534 funded by the Ministry of Education, Culture, Sports, Science, and Technology, Government of Japan. ORCID Sridhara Nayak http://orcid.org/0000-0003-2421-5199 Tetsuya Takemi http://orcid.org/0000-0002-7596-2373 Data availability statement The dataset supporting the conclusions of this article includes the Japan Meteorological Agency (JMA) based Radar/Rain gauge – Analyzed Precipitation product, and the RSMC Tokyo (https://www.jma.go.jp/jma/indexe.html), the CMA Tropical Cyclone Data Center (https://www.typhoon.org.cn), and the JTWC (https://www.metoc.navy.mil/jtwc/jtwc.html?best- tracks) best-track datasets. 18 S. NAYAK AND T. TAKEMI References Ahsan MM, Ozbek N. 2022. Policy considerations on hurricane induced human displacement: lessons from Cyclone Sidr and Hurricane Katrina. Trop Cyclone Res Rev. 11(2):120–130. Albert J, Krishnan A, Bhaskaran PK, Singh KS. 2022. Role and influence of key atmospheric parameters in large-scale environmental flow associated with tropical cyclogenesis and ENSO in the North Indian Ocean basin. Clim Dyn. 58(1–2):17–34. Aon Benfield. 2016. Global Catastrophe Recap – October 2016. [Available at http://thought- leadership.aon.com/pages/Home.aspx?ReportYear=2016]. Arguez A, Hurley S, Inamdar A, Mahoney L, Sanchez-Lugo A, Yang L. 2020. Should we expect each year in the next decade (2019–28) to be ranked among the top 10 warmest years glo- bally? Bulletin American Meteorological Society. 101(5):E655–E663. Chan JC. 2005. Interannual and interdecadal variations of tropical cyclone activity over the western North Pacific. Meteorol Atmos Phys. 89(1-4):143–152. Chan KT. 2019. Are global tropical cyclones moving slower in a warming climate? Environ Res Lett. 14(10):104015. Cox D, Arikawa T, Barbosa A, Guannel G, Inazu D, Kennedy A, Li Y, Mori N, Perry K, Prevatt D, et al. 2019. Hurricanes Irma and Maria post-event survey in US Virgin Islands. Coastal Eng J. 61(2):121–134. Fudeyasu H, Iizuka S, Matsuura T. 2006. Impact of ENSO on landfall characteristics of tropical cyclones over the western North Pacific during the summer monsoon season. Geophys Res Lett. 33(21):L21815. Fudeyasu H, Shimada U, Oikawa Y, Eito H, Wada A, Yoshida R, Horinouchi T. 2022. Contributions of the Large-Scale Environment to the Typhoon Genesis of Faxai (2019). Journal of the Meteorological Society of Japan. 100(4):617–630. Gall M, Cutter SL. 2019. 2005 events and outcomes: hurricane Katrina and beyond. In: Emergency management. Abingdon: Routledge; p. 191–217. Gao S, Chen Z, Zhang W. 2018. Impacts of tropical North Atlantic SST on western North Pacific landfalling tropical cyclones. J Climate. 31(2):853–862. Girishkumar MS, Thanga Prakash VP, Ravichandran M. 2015. Influence of Pacific Decadal Oscillation on the relationship between ENSO and tropical cyclone activity in the Bay of Bengal during October–December. Clim Dyn. 44(11-12):3469–3479. Guan S, Li S, Hou Y, Hu P, Liu Z, Feng J. 2018. Increasing threat of landfalling typhoons in the Western North Pacific between 1974 and 2013. Int J Appl Earth Obs Geoinf. 68:279– Halverson JB, Rabenhorst T. 2013. Hurricane Sandy: the science and impacts of a superstorm. Weatherwise. 66(2):14–23. Hassan MM, Ash K, Abedin J, Paul BK, Southworth J. 2020. A quantitative framework for analyzing spatial dynamics of flood events: a case study of super cyclone Amphan. Remote Sensing. 12(20):3454. Hatsuzuka D, Sato T, Yoshida K, Ishii M, Mizuta R. 2020. Regional projection of tropical- cyclone-induced extreme precipitation around Japan based on large ensemble simulations. SOLA. 16(0):23–29. Hornyak T. 2020. Typhoons getting stronger, making landfall more often. EOS. 101 Published on 12 August 2020. Ishikawa H, Oku Y, Kim S, Takemi T, Yoshino J. 2013. Estimation of a possible maximum flood event in the Tone River basin, Japan caused by a tropical cyclone. Hydrol Process. 27(23):n/a–n/a. Ito R, Takemi T, Arakawa O. 2016. A possible reduction in the severity of typhoon wind in the northern part of Japan under global warming: a case study. SOLA. 12(0):100–105. Kamahori H, Arakawa O. 2018. Tropical cyclone induced precipitation over Japan using obser- vational data. SOLA. 14(0):165–169. Kanada S, Aiki H, Tsuboki K, Takayabu I. 2019. Future changes in typhoon-related precipita- tion in eastern Hokkaido. SOLA. 15(0):244–249. GEOMATICS, NATURAL HAZARDS AND RISK 19 Kim K, Bui L. 2019. Learning from Hurricane Maria: island ports and supply chain resilience. Int J Disaster Risk Reduct. 39:101244. Kim SH, Moon IJ, Chu PS. 2020. An increase in global trends of tropical cyclone translation speed since 1982 and its physical causes. Environ Res Lett. 15(9):094084. Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahori H, Kobayashi C, Endo H, et al. 2015. The JRA-55 reanalysis: general specifications and basic characteristics. J Meteorological Society Japan. 93(1):5–48. Kossin JP, Knapp KR, Olander TL, Velden CS. 2020. Global increase in major tropical cyclone exceedance probability over the past four decades. Proc Natl Acad Sci USA. 117(22):11975– Landsea CW, Vecchi GA, Bengtsson L, Knutson TR. 2010. Impact of duration thresholds on Atlantic tropical cyclone counts. J Climate. 23(10):2508–2519. Lu XQ, Yu H, Ying M, Zhao BK, Zhang S, Lin LM, Bai LN, Wan RJ. 2021. Western North Pacific tropical cyclone database created by the China Meteorological Administration. Adv Atmos Sci. 38(4):690–699. Mei W, Xie SP, Primeau F, McWilliams JC, Pasquero C. 2015. Northwestern Pacific typhoon intensity controlled by changes in ocean temperatures. Sci Adv. 1(4):e1500014. Mei W, Xie SP. 2016. Intensification of landfalling typhoons over the northwest Pacific since the late 1970s. Nature Geosci. 9(10):753–757. Mohanty S, Nadimpalli R, Osuri KK, Pattanayak S, Mohanty UC, Sil S. 2019. Role of sea sur- face temperature in modulating life cycle of tropical cyclones over Bay of Bengal. Trop Cyclone Res Rev. 8(2):68–83. Nagata K. 2011. Quantitative precipitation estimation and quantitative precipitation forecasting by the Japan Meteorological Agency. RSMC Tokyo–Typhoon Center Technical Review. 13: 37–50. Available online at: http://www.jma.go.jp/jma/ jma-eng/jma-center/rsmc-hp-pub-eg/ techrev/text13-2.pdf. Nayak S, Takemi T. 2019a. Quantitative estimations of hazards resulting from Typhoon Chanthu (2016) for assessing the impact in current and future climate. Hydrological Research Letters. 13(2):20–27. Nayak S, Takemi T. 2019b. Dynamical downscaling of Typhoon Lionrock (2016) for assessing the resulting hazards under global warming. Journal of the Meteorological Society of Japan. 97(1):69–88. Nayak S, Takemi T. 2020a. Typhoon-induced precipitation characterization over northern Japan: a case study for typhoons in 2016. Prog Earth Planet Sci. 7(1):39. Nayak S, Takemi T. 2020b. Robust responses of typhoon hazards in northern Japan to global warming climate: cases of landfalling typhoons in 2016. Meteorol Appl. 27(5):e1954. Padgett J, DesRoches R, Nielson B, Yashinsky M, Kwon OS, Burdette N, Tavera E. 2008. Bridge damage and repair costs from Hurricane Katrina. J Bridge Eng. 13(1):6–14. Patricola CM, Camargo SJ, Klotzbach PJ, Saravanan R, Chang P. 2018. The influence of ENSO flavors on western North Pacific tropical cyclone activity. J Climate. 31(14):5395–5416. Paul BK. 2010. Human injuries caused by Bangladesh’s cyclone Sidr: an empirical study. Nat Hazards. 54(2):483–495. Song J, Klotzbach PJ, Duan Y. 2022. Statistical linkage between coastal El Nino ~ –Southern Oscillation and tropical cyclone formation over the western North Pacific. Atmos Sci Lett. 23(2):e1071. Song J, Klotzbach PJ, Tang J, Wang Y. 2018. The increasing variability of tropical cyclone life- time maximum intensity. Sci Rep. 8(1):1–7. Sun Y, Zhong Z, Li T, Yi L, Camargo SJ, Hu, Y Y, Liu K, Chen H, Liao Q, Shi J. 2017. Impact of ocean warming on tropical cyclone track over the western North Pacific: a numerical investigation based on two case studies. J Geophys Res Atmos. 122(16):8617–8630. Takagi H, Esteban M. 2016. Statistics of tropical cyclone landfalls in the Philippines: unusual characteristics of 2013 Typhoon Haiyan. Nat Hazards. 80(1):211–222. 20 S. NAYAK AND T. TAKEMI Takayabu I, Hibino K, Sasaki H, Shiogama H, Mori N, Shibutani Y, Takemi T. 2015. Climate change effects on the worst-case storm surge: a case study of Typhoon Haiyan. Environ Res Lett. 10(6):064011. Takemi T, Ito R, Arakawa O. 2016a. Effects of global warming on the impacts of Typhoon Mireille (1991) in the Kyushu and Tohoku regions. Hydrological Research Letters. 10(3):81–87. Takemi T, Ito R, Arakawa O. 2016b. Robustness and uncertainty of projected changes in the impacts of Typhoon Vera (1959) under global warming. Hydrological Research Letters. 10(3):88–94. Takemi T, Okada Y, Ito R, Ishikawa H, Nakakita E. 2016c. Assessing the impacts of global warming on meteorological hazards and risks in Japan: philosophy and achievements of the SOUSEI program. Hydrological Research Letters. 10(4):119–125. Takemi T, Unuma T. 2019. Diagnosing environmental properties of the July 2018 Heavy Rainfall event in Japan. SOLA. 15A(0):60–65. Takemi T, Unuma T. 2020. Environmental factors for the development of heavy rainfall in the eastern part of Japan during Typhoon Hagibis (2019). SOLA. 16(0):30–36. Takemi T, Yoshida T, Yamasaki S, Hase K. 2019. Quantitative estimation of strong winds in an urban district during Typhoon Jebi (2018) by merging mesoscale meteorological and large-eddy simulations. SOLA. 15(0):22–27. Takemi T. 2019. Impacts of global warming on extreme rainfall of a slow-moving typhoon: a case study for Typhoon Talas (2011). SOLA. 15(0):125–131. Unuma T, Takemi T. 2016. Characteristics and environmental conditions of quasi-stationary convective clusters during the warm season in Japan. QJR Meteorol Soc. 142(696):1232– Wang Q, Li J. 2022. Feedback of tropical cyclones on El Nino diversity. Part I: phenomenon. Clim Dyn. :1–16. Wang Y, Rao Y, Tan ZM, Schonemann D. 2015. A statistical analysis of the effects of vertical wind shear on tropical cyclone intensity change over the western North Pacific. Monthly Weather Review. 143(9):3434–3453. Xian S, Lin N, Hatzikyriakou A. 2015. Storm surge damage to residential areas: a quantitative analysis for Hurricane Sandy in comparison with FEMA flood map. Nat Hazards. 79(3): 1867–1888. Yamaguchi M, Maeda S. 2020. Slowdown of typhoon translation speeds in mid-latitudes in september influenced by the pacific decadal oscillation and global warming. J Meteorological Society Japan. 98(6):1321–1334. Ying M, Zhang W, Yu H, Lu X, Feng J, Fan Y, Zhu Y, Chen D. 2014. An overview of the China Meteorological Administration tropical cyclone database. J. Atmos. Oceanic Technol. 31(2):287–301. Yoshida K, Sugi M, Mizuta R, Murakami H, Ishii M. 2017. Future changes in tropical cyclone activity in high-resolution large-ensemble simulations. Geophys Res Lett. 44(19):9910–9917. Zhan R, Wang Y, Liu Q. 2017. Salient differences in tropical cyclone activity over the western North Pacific between 1998 and 2016. J Climate. 30(24):9979–9997. Zhang Q, Gu X, Li J, Shi P, Singh VP. 2018. The impact of tropical cyclones on extreme pre- cipitation over coastal and inland areas of China and its association to ENSO. J Climate. 31(5):1865–1880. Zhao H, Wang C. 2019. On the relationship between ENSO and tropical cyclones in the west- ern North Pacific during the boreal summer. Clim Dyn. 52(1-2):275–288.
Journal
Geomatics Natural Hazards and Risk
– Taylor & Francis
Published: Dec 31, 2023
Keywords: Typhoon; typhoon intensity; typhoon hazard; environmental conditions; climate change
