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Quaternary International 244 (2011) 169e177

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Tropical cyclones in China: County-based analysis of landfalls and economic lossesin Fujian Province

Marco Gemmer a, Yizhou Yin a,b, Yong Luo a,*, Thomas Fischer a

aChina Meteorological Administration (CMA), National Climate Center (NCC), 46 Zhongguancun Nandajie, Haidian, Beijing 100081, PR Chinab Institute of Atmospheric Physics, Chinese Academy of Sciences, Waiqijiahuozi Deshengmen, Chaoyang, Beijing 100029, PR China

a r t i c l e i n f o

Article history:Available online 30 March 2011

* Corresponding author. Fax: þ86 10 62176804.E-mail address: yluo@cma.gov.cn (Y. Luo).

1040-6182/$ e see front matter � 2011 Elsevier Ltd adoi:10.1016/j.quaint.2011.03.021

a b s t r a c t

Most of China’s coastline is economically developing, densely populated, and frequently hit by landfallingTropical Cyclones (TCs). Economic losses below province level have not been systematically analyzed dueto lack of data. The objective of this paper is to conduct a TC loss assessment on county level in FujianProvince, coastal SE China, and to break down economic losses from province-scale to smaller admin-istrative units. A unique loss database established by the China Meteorological Administration (CMA) andNational Climate Center is used, and four entries at county-level are derived: location of losses due to TC,total economic losses per TC, start time of TC, and end time of TC. Tracks and intensities of TCs from 1949e2008 are derived from the CMA and Shanghai Typhoon Center annual typhoon yearbooks. Physical andeconomic data are overlaid in a Geographical information System. The landfall spots of TCs on China’smainland coastline from 1949e2008 are determined by generating segments of 1� length. The resultshows that Guangdong Province (South China) and Fujian Province (South-East China) host distinct hotspots where TCs make frequent landfall. All TCs making landfall in Central-North Fujian originated fromthe West North Pacific and none from the South China Sea.

Direct economic losses in 25 counties along Fujian’s coastline due to TCs from 1984e2007 are analyzedand corrected with the Consumer Price Index. Some counties report losses frequently at low magnitudebut seldom at high magnitude. Others like urban Fuzhou experience losses above 10 million CNY per TC,the most costly one 70 times higher. Other rural counties might experience economic losses far below 10million CNY when being hit. Landfalling TCs in average cause economic losses of minimum 10 millionCNY in 21 of 25 counties. In roughly one third of the counties, economic losses account for more than 30million CNY when a TC has impact. The average economic losses per TC are 0.2e0.5% of the counties’ GDP(South and North of Fujian’s coastline) and even more than 0.5% of the GDP in North-East Fujian. Theeconomic impacts of TCs are higher along the southern and northern coastline of Fujian Province whereTC landfall activity is higher, but higher economic losses are triggered by higher GDP in these counties.The most costly TCs in Fujian had intensities of Severe Tropical Storm or Typhoon and occurred mostly inthe 2000’s after making landfall in July.

� 2011 Elsevier Ltd and INQUA. All rights reserved.

1. Introduction

China’s coastal areas are economically developed, denselypopulated, and are regularly affected by tropical cyclones (TCs). Anaverage of 9 TCs make landfall in China every year (Yin et al., 2010).Serious losses of life and property damages can occur when TCsmake landfall in these areas, causing strong winds, torrentialrainfall, and tidal surges (Zhou et al., 2004). Based on Liu et al.

nd INQUA. All rights reserved.

(2009), some 250 million people in China are potentially exposedto typhoon-disasters. In China, almost half of the economic lossescaused by natural disasters resulted from TCs. For example, in 2006,meteorological disasters in China caused 3485 casualties and 25.2billion CNY in direct economic losses, of which TCs accounted for30% of the total economic losses and 43% of the casualties (Xiao andXiao, 2010).

Louie and Liu (2003), Chan and Shi (2000) and Liu et al. (2003)describe records on the historical frequency of TC landfalls overparts in Guangdong and Fujian, the mainland provinces withhighest landfall frequency of TCs. These sources mostly focus on thereconstruction of TC tracks and deliver the historical evidence of TC

Table 1Number of TCs (tropical storm level and above) makinglandfall in the respective province 1949e2008, listed fromnorth to south.

Province Number of TCs

Liaoning 2Hebei 0Tianjin 0Shandong 9Jiangsu 4Shanghai 4Zhejiang 37Fujian 95Guangdong 204Guangxi 8Sum 363

M. Gemmer et al. / Quaternary International 244 (2011) 169e177170

frequencies in this area. However, little work has been done on theeconomic impacts of TCs in China on a resolution below provincelevel.

Research on TCs affecting China focuses on their physical extentand falls into the domains of atmospheric and meteorologicalsciences. One focus is the assessment of the variability in numberand landfall of TCs (Xu et al., 2004; Li and Duan, 2010; Liu and Chan,2010). Another major topic is the review and forecasting of TCintensity (Wang and Zhou, 2008; Wong et al., 2008) and the reviewand forecasting of TC tracks and TC genesis (Ma et al., 2007; Wangand Ren, 2008). Much effort has been spent on TC reanalysis inChina (Yu et al., 2007; Zhang et al., 2007; Wang et al., 2008) or theassociation of TCs with heavy precipitation (Ren et al., 2006; Chenet al., 2010; Yin et al., 2010). All of these approaches attempt toimprove the forecast and description of the physical features ofa TC. However, it is very difficult to assess and forecast theeconomic damages. Even though the basic risk can be physicallyand statistically assessed, e.g. based on TC frequency, the TCintensity and landfall spot is not necessarily related to the realdamage (Sousounis et al., 2008). There is no ‘rule of thumb’describing when a TC becomes costly. Post-disaster assessment ofeconomic losses is mainly limited to countries with high insurancedensity.

Most of the losses caused by TCs in China are uninsured,although foreign direct insurance and reinsurance providers haveentered the Chinese market recently (Shi et al., 2010). Catastrophebonds for natural hazards have been discussed scientifically (Li andLiu, 2010) and pilot programs for agricultural insurance have beenlaunched (Wang et al., 2009). This situation is similar to most otheremerging or developing countries facing weather-risks (Andersen,2002). Currently, households and businesses in low- and middle-income countries have only 1% and 3% of insurance coverageagainst catastrophe risks, respectively, compared to 30% in highincome countries (MunichRe, 2005). With high insurance coveragein the developedworld, an immense database on asset losses due tonatural disasters and societal impacts has emerged (Lindell andPrater, 2003; Thieken et al., 2006). Data availability in emergingcountries is less favourable. In scientific literature for these coun-tries, and China in particular, TC loss assessment and review istypically made annually on a national level (Xiao and Xiao, 2010),event-based on a local level (Liu et al., 2009), or trigger-based onthe global level (Varangis et al., 2002).

TC losses affect a broad range of sectors and cause direct as wellas indirect losses. Often, it is difficult to assess relevant data inChina. Mostly, data time series cover the past few years only (Xuand Gao, 2005). The China Meteorological Administration (CMA),however, has started to publish annual losses due to meteorologicaldisasters in China on the province level since 2004 (CMA,

2005e2008). Data on economic losses related to natural hazardsare published annually by the relevant Ministries such as theMinistry of Water Resources (flood losses), Ministry of Agriculture(losses related to agricultural drought), or the Ministry of CivilAffairs who also hosts a State Center for HazardManagement whichcollects natural hazard related data for post-disaster assessments.While the Ministries and their Agencies publish annual data in thefield of their responsibility and data below province level are notpublished, CMA publishes all weather and climate related loss data.

A variety of concepts have been published for different risks andeconomic losses related to natural disasters. Zhang et al. (2005)assessed the risk of agro-meteorological hazards in Jilin (North-east China) and used general loss data and specific agriculturalindicators and data, as did Chen et al. (2009a) for Fujian Provinceand Wu et al. (2007) for Zhejiang Province. Hu et al. (2010) dis-cussed emergency response mechanisms for meteorologicaldisasters. This kind of assessment can be found for other naturalhazards such as floods, droughts, or landslides.

Zhang et al. (2009) started an approach for TC loss assessment inChina on the province level and assigned TC losses to provinces byyears. This was the first publicly available approach to break downlosses into more detailed information and was followed by Xiaoand Xiao (2010) who focused on casualties. Meanwhile, directeconomic losses caused by TCs can be assigned to the provinces ofChina. The basic risk in terms of loss frequency and extent can beindicated for each province and compared. Recent example areprovided by Zhang et al. (2010) and Ye et al. (2004) who provideinformation on changing properties on typhoon losses and othernatural hazards or Typhoon Storm Surge Disaster Degree inGuangdong Province, Lou et al. (2009) who simulated economiclosses due to TCs in Zhejiang province, Li and Liu (2010) who dis-cussed typhoon losses in view of the insurance industry, and Chenet al. (2009b) who statistically investigated the features of directeconomic losses caused by the TCs affecting China from 1980 to2004.

However, China’s coastal provinces are large in extent and onlya small proportion of the province might have been affected duringa TC. It has not been statistically assessedwhich part of the provincehad losses triggered by a TC. The challenges are to answer thefollowing questions:

- inwhich part of the province arise economic losses during a TC,- how to assess economic losses (are they related toTC or not?),

Answering these questions will help to break down economiclosses from province-scale to smaller administrative units. Untilnow, the counties susceptible to high or low economic losses havenot yet been identified. The objective of this paper is to conducta first-ever TC loss assessment on a county level in Fujian Province,coastal SE China. This will be made using a unique loss databaseestablished locally by the China Meteorological Administration andNational Climate Center. Unlike the physically based approachesthat assess all TCs in China (whether they cause economic losses ornot), this methodology will investigate only TCs that causedeconomic losses.

2. Data, methods and regional settings

The term TC refers to events with minimum intensity at tropicalstorm level. TC data are derived from the CMA annual typhoonyearbooks. Records consist of 6-hourly positions (0.1� latitude andlongitude) and intensities (intervals of 2-min mean maximumsustained wind speed [m/s] near the storm center). These areavailable from 1949e2008. In addition, track data from theShanghai Typhoon Center of CMA were used. They represent the

Fig. 1. Location of the coastal provinces of China, 1� segments, ranking of the segments with highest TC landfall activity (bold) and total number of TCs making landfall in thesegments (in brackets).

M. Gemmer et al. / Quaternary International 244 (2011) 169e177 171

best TC tracks of the 363 TCs making landfall in China 1949e2008.Different TC intensities are used for the analyses in Section 3.

For the landfall analysis, the digital vector map for the coastlineof mainland China from Liaoning Province in the NE to Guangxi inthe SW was converted to nearly 40,000 points, making use of theGeographical Information System ArcGIS and the feature ‘verticesto points’. All TC tracks were then attributed to longitude/latitudepositions of the coastline when making landfall. The coastline wasthen divided into 11 segments from 111�E to 122�E, each being 1� in

East-West extent (w10 km). The number of TCs making landfallwas attributed to each segment thereafter, also distinguishingwhether the TC originated from the South China Sea (SCS) or theNorth West-Pacific (NWP).

Damage and economic loss data related to weather and climaterelated risks are recorded by the CMA. The CMA headquarters basedin Beijing released guidelines in order to harmonize the way ofrecording natural disasters in China. In the case of meteorologicaldisasters, local bureaus of CMA on county-level have to record the

Table 2Number of TCs making landfall in the respective segments of the coastline1949e2008, listed from south to north.

Segment(longitude �E)

Total number ofTCs making landfall

Origin from theSouth China Sea (%)

(108e111) 60 n/a(111e112) 34 35(112e113) 19 42(113e114) 22 23(114e115) 26 27(115e116) 18 33(116e117) 29 28(117e118) 14 14(118e119) 31 13(119e120) 46 0(120e121) 19 0(121e122) 25 4sum 343

Fig. 3. Record of 34 TCs making landfall in segment 110e111�E (cp. Fig. 1) 1949e2008.

M. Gemmer et al. / Quaternary International 244 (2011) 169e177172

weather event and indicators concerning the disaster relateddamages and losses (e.g. number of affected population, losses inagriculture). Based on these guidelines, the losses due to TCs havebeen compiled by the Fujian Climate Center. For this study, theperiod covering the years from 1984 to 2007 was provided as it isavailable in digital format. In order to validate the data on TC losses,the authors organised a two-week field investigation in Fujianprovince in June 2009. For this paper, four entries (at county-level)were used from the local economic loss database: location of lossoccurrences due toTC, total economic losses per TC, start time of TC,and end time of TC.

Thirty coastal and near-coast stations in Fujian Province wereselected for the county-based analysis. After checking consistencyof weather and loss data on TC-events, 25 counties remained for thecomplete analysis on the county level. For 5 of the 30 stations,either data were not available at the county level as the stationwasat the city level and lacked loss data, or the loss data could not beharmonised with wind and precipitation data to prove that a TCoccurred.

High TC susceptibility does not necessarily result in highsusceptibility of economic losses. With the approach in this study,economic loss susceptibility can be derived for the counties. This is

Fig. 2. Record of 46 TCs that made landfall in segment 119e120�E (cp. Fig. 1)1949e2008.

opposed to TC susceptibility, which does not provide informationon economic losses.

The consumer price index (CPI) for China with its baseline in1978 (opening of China during Deng Xiaoping’s reform policy) wasapplied to the event-based economic loss data in order to make thelosses per TC comparable. GDP data from the Fujian statisticalyearbook was used to analyse the economic impact of TCs atcounty-level with regard to the annual economic output.

3. Results

3.1. Tropical cyclone landfall activity 1949e2008 in Southern China

The total number of TCs making landfall in the respectivecoastal province of China 1949e2008 is displayed in Table 1. Theprovinces are listed from north to south, and Fig. 1 shows thelocation of the more relevant southern and eastern provinces. Thehighest number of TCs making landfall were recorded in Guang-dong Province (204) and Fujian Province (95). In all other coastalprovinces, fewer TCs made landfall. However, the length of coast-lines varies significantly, and the TCs mostly enter the coastlinefrom the south and southeast, i.e. provinces with a coastlineoriented east-west are likely to be more frequently hit by TCs thanthose with a coastline aligned south-north. TCs originating fromthe South China Sea (SCS) are therefore more likely to hit Guangxiand Guangdong, while TCs from thewest North Pacific (WNP)makelandfall in higher latitudinal provinces. The focus of TC impactsinitially will mainly focus on Guangdong, Fujian, and Zhejiang.

The analysis of TC landfall activity will focus on the coastlineeast of the Leizhou Peninsula (SW Guangdong Province at 110�E)and south of Hangzhou Bay (NE Zhejiang Province at 122�E). Thecoastline east of 111�E was therefore divided in 11 segments of 1�

longitude in order to identify the area with highest TC landfallactivity. The 11 segments can be seen in Fig.1 along the South Chinacoastline of Guangdong, Fujian and Zhejiang Provinces.

The results of the TC landfall analysis can be seen in Fig. 1, andadditionally with the 108e111�E segments in Table 2. The totalnumber of TCs between 108 and 122�E is 343. The total number of363 TCs that made landfall in Mainland China 1949e2008 includesTCs that made landfall north of this stretch of coastline (1 in Zhe-jiang and 19 in the other provinces mentioned in Table 1).

Table 3Coastal counties in Fujianwith weather stations, number of TCs causing losses 1984e2007, most costly TC (loss/CPI 106CNY), number of TCs with impact higher than 10millionCNY, and average loss/CPI per TC (bold numbers representing the six counties with the highest losses per TC, underlined numbers representing counties with generally lowlosses).

No Station ID name lon lat TC impact(number)

Max. loss/CPI(106CNY)

TCs causinglosses > 10 � 107 CNY

Average loss/CPIper TC

1 58748 Fu an 119.65 27.1 30 138 16 27.182 58749 Zhe rong 119.9 27.25 29 60 6 8.783 58754 Fu ding 120.2 27.33 26 675 21 68.474 58839 Min qing 118.85 26.23 7 15 1 5.765 58843 Xia pu 120 26.88 26 517 18 43.416 58844 Min hou 119.15 26.15 10 116 3 21.177 58845 Luo yuan 119.53 26.5 23 133 10 24.458 58846 Ning de 119.52 26.67 23 163 11 33.239 58847 Fu zhou 119.28 26.08 16 741 15 173.7610 58848 Lian jiang 119.53 26.2 30 128 16 26.1011a 58929 An xi 118.15 25.0712a 58934 Yong chun 118.27 25.3313 58935 De hua 118.23 25.48 17 35 7 8.9714 58936 Xian you 118.7 25.37 21 185 9 18.8215 58941 Chang le 119.5 25.97 25 106 10 15.2316 58944 Ping tan 119.82 25.52 21 119 8 16.7717a 58946 Pu tian 119 25.4318 59122 Chang tai 117.75 24.62 24 109 6 14.2919 59124 Nanjing 117.37 24.52 20 70 9 14.3320 59125 Ping he 117.32 24.37 21 104 14 24.2921 59126 Zhang zhou 117.65 24.5 27 28 4 5.2322 59127 Long hai 117.82 24.45 20 219 13 33.4523 59130 Tong an 118.13 24.72 20 69 3 6.424 59131 Nan an 118.37 24.97 11 98 9 28.9825a 59133 Chong wu 118.92 24.926a 59134 Xia men 118.07 24.4827 59137 Jin jiang 118.57 24.82 19 108 8 19.9828 59320 Zhao an 117.13 23.77 23 178 16 28.0729 59321 Dong shan 117.5 23.78 19 109 6 14.530 59322 Yun xiao 117.37 23.98 24 79 10 13.9

a No loss data on county-level.

M. Gemmer et al. / Quaternary International 244 (2011) 169e177 173

Thenumberof TCsmaking landfall is scatteredover the segmentsalong the coastline. The highest number of TCs in the selected areamade landfall in the segment NE Fujian Province (46) between 119and 120�E, followed by the segments SWGuangdong Province (34)between 111 and 112�E and Central Fujian coastline (31) between118and119�E. Fromthis analysis, as opposed tocountingTC landfallson province level, there is no gradual decrease of TC landfall eventsfrom south to north. Some ‘hot-spots’ along the coastline existwhere TCs make frequent landfall. One hot-spot segment is inCentral and North Fujian Province, and the second one is in

Fig. 4. Highest economic losses (losses/CPI), average economic losses pe

Guangdong Province where the segments with higher TC landfallfrequency are not concentrated but scattered over the coastline.

The segment with the lowest number of TCs making landfall islocated in the south of Fujian Province, although the center andnorth are a distinct TC landfall hot spot. Fig. 2 shows the tracks ofthe 46 TCs that made landfall in segment 119e120�E, ranking firstin terms of TC landfall. As can be seen, no TC originated in the SCS,but all in the WNP. Most of the TCs that made landfall in northernFujian Province crossed Taiwan or passed to the north. With oneexception, all tracks passed the Philippines to the west or north.

r TC, and number of TCs causing losses on county-level 1984e2007.

Fig. 5. Location of the 25 counties with analysed TC losses in Fujian Province.

M. Gemmer et al. / Quaternary International 244 (2011) 169e177174

Fig. 3 displays the tracks of the 34 TCs that landed in segment111e112�E in Guangdong Province, ranking second in the numberof TC landfall. Roughly one third originated in the SCS. All TCsmaking landfall in Guangdong Province passed Taiwan in the South.

Comparing the landfalling TCs in the hot spots (Guangdong andFujian), TCs landing in Fujian are longer in duration and distanceafter making landfall. They continue in a northern direction inFujian as compared to TCs landing in Guangdong which continue tothe west. Sousounis et al. (2008) concluded that the duration ofa TC increases the risk of economic losses. As Fujian includes thesegments with highest number of landfalling TCs, which also aresustained longer than in Guangdong province, the economic lossescaused by TCs are analyzed for Fujian Province in the followingsection.

3.2. Tropical cyclones in Fujian Province: economic losses

For the analysis of economic losses, the local weather-riskrelated losses database of Fujian Climate Center was used. Theeconomic losses presented are caused by TCs. Any TC that did notcause economic losses was not taken into consideration. The CPIwas applied to align economic loss data to the 1978 base. TCscausing losses in Fujian 1984e2007 were taken into consideration.Earlier records are not available digitally.

Table 3 shows some key features of the TC losses analysis. Somecounties reported losses more frequently than others (Fig. 6 lowerright). Hence, they are more often hit by TCs (e.g. stations 1 and 10with 30 reported TCs causing losses). The other counties such asFuzhou (no. 9) have been hit by TCs half as often; it reported 15eventswith economic losses over 10million CNYwhilst being hit 16times. Station 1 (Fu’an) also reported 16 TCs with more than 10million CNYeconomic losses, which represents 50% of the reportedTCs.

Some areas are more frequently hit with lower frequency ofhigh losses, whilst other areas repeatedly report high losses. The

column on the average loss/CPI per TC underlines this finding.While Fuzhou (no. 9) reports average losses of 173 million CNY perTC (CPI corrected) and the most costly TC caused 741 million CNYlosses, Zhangzhou (no. 21) was hit 27 times (60% more than Fuz-hou) with the highest loss of 28 million CNY and average losses of5.23 million CNY per TC. This is underlined by Fig. 4 which showsthe highest economic losses (losses/CPI) per county, averageeconomic losses per TC and county, and number of TCs causinglosses on county-level 1984e2007. Minqing County was rarelyaffected by TCs, and both the historical highest and average TClosses are low. Lianjiang County was frequently hit (30 times), butthe highest losses and average losses are comparatively low. Fuz-hou has been hit 16 times, but the highest and average losses arethe highest in the research area. The location of the counties can beobtained from Fig. 5.

As can be seen from Fig. 6, the 25 investigated counties arediverse in population with population being higher directly at thecoast, and most of the counties having between 0.5 and 1 millioninhabitants. The GDP of three counties is more than 50 billionCNY (2007 level), while in fifteen counties less than 10 billionCNY are achieved. These are mostly in the hinterland and south ofFujian and can be considered as counties with comparatively lowGDP.

Most of the counties in the north, however, rank highest in themaximum economic losses that have been recorded 1984e2007(CPI corrected), which is between 100 and 200 million CNY andover 200 million CNY, respectively. These are mostly the countiesfor which economic losses due to TCs have been recorded mostfrequently in the upper north and lower south of Fujian’s coastline.Exceptions are Longhai County in the hinterland of Xiamen, andFujian Province’s capital city of Fuzhou, where TCs impact lessfrequently but cause higher absolute economic losses. This is alsovisible from the left panel of Fig. 7 where the average economiclosses per TC 1984e2007 are shown. Except for 5 counties in thehinterland of the coast, on average landing TCs cause economiclosses at the county-level of at least 10 million CNY. Most of thecounties experienced economic losses between 20 and 30 millionCNY per TC and roughly one third of more than 30 million CNY. InFuzhou, the value exceeds 173 million CNY (Table 3).

The impacts on the economy are displayed in the right panel ofFig. 7 where the average economic losses per TC in percentage ofthe GDP (2007 values) are shown. Most of the counties in the southand north of Fujian’s coastline lose in average 0.2e0.5% of their GDPdue to every TC, while in the counties of northeast Fujian they loseeven more than 0.5% of their GDP.

The intensity of the three most costly TCs (after CPI) in each ofthe 25 counties shows the following characteristics:

(1) in 73 of 75 cases the TC made landfall; (2) the TC intensity atthe time of landfall was: Tropical Storm in 3 cases, Severe TropicalStorm in 30 cases, Typhoon in 37 cases, and Severe Typhoon in 5cases; (3) the most costly TCs were recorded in May (6), June (11),July (16), August (14), September (15), October (13), making July themonth the most susceptible month for high TC losses; (4) the 75most costly TCs (25 counties times three events) have been causedby 26 different TC-events, i.e. a costly TC has hit three counties onaverage; (5) four of these 26 TCs occurred in the 1980s, eight in the1990s, and 14 in the 2000s (until end of 2007); (6) the single mostcostly TC event in each county occurred eight times in the 1990sand 17 times in the 2000s.

The economic impacts of TCs are higher along the southern andnorthern coastline of Fujian Province. These are also the areaswhere TC activity is higher, thus resulting in higher frequency ofeconomic losses. The most costly TCs in Fujian had intensities ofSevere Tropical Storm or Typhoon, occurred mostly in the 2000s,and made landfall in July.

Fig. 6. Variables for the 25 selected counties in Fujian Province: GDP in billion CNY, 2007 (upper left), population in million, 2007 (upper right), maximum economic losses duringone TC 1984e2007 (lower left), number of TCs for each county with recorded economic losses 1984e2007 (lower right).

M. Gemmer et al. / Quaternary International 244 (2011) 169e177 175

4. Discussion and conclusions

The study was able to answer the questions where and wheneconomic losses due to TCs occurred, and the objective to apply aneconomic loss assessment on county level in Fujian Province wasachieved. Comparing the results of the two approaches, theeconomic losses due to TCs in Fujian Province are higher in thenorth than in the south. This is not because of the higher frequency

of TCs making landfall in the north (Fig. 1) but apparently becauseof higher GDP in the north of Fujian, or other external factors suchas wind and precipitation caused by TCs.

The landfall activity of TCs delivers some new insights. TCstatistics on a provincial level might be an ideal instrument fora national assessment of weather-related risks. However, makinguse of segments as done in this study can point out landfall hotspots in greater detail. Aligning TC landfall areas to 1� segments has

Fig. 7. Variables for the 25 selected counties in Fujian Province: average economic losses per TC in million CNY (left), average economic loss per TC in percentage (%) of 2007 GDP(right).

M. Gemmer et al. / Quaternary International 244 (2011) 169e177176

proven to be an advanced step in order to describe the basic risk ofTC landfall activity through 1949e2008. Residents in South Fujianare relatively more safe in view of landfalling TCs than those incentral-north Fujian. In order to provide even more detail on thelandfall zoning and as the segments cover different coast-lengths, itis recommended to make use of coastline stretches of equal lengthfor this assessment in future.

Making use of CMA’s local economic loss database for weather-related disasters enables a unique mapping of TC related economiclosses in coastal Fujian. Much has been written on the evolution ofTCs in the world and the associated economic losses caused bythem. Zhang et al. (2009) noted that monetary losses in China from1983 to 2006 have been increasing due to the nation’s productivityboom and not due to higher TC frequency. This is supported by Yinet al. (2010) who noted that the number of TCs making landfall inChina and the overall number of TCs in the WNP show no trend.Detecting and forecasting the tracks and potential landing zones ofTCs remains important, as this appears decisive for the economiclosses.

The database shows that about three quarters of the countiesexperienced the historically highest losses due toTCs in 2002, 2005,and 2006. In most of the other counties the historically most costlyTCs occurred in the 1990s. All the historical losses are transformedwith the CPI and therefore comparable. This shows that TC impactshave not necessarily increased due to economic growth. A reasonthat TC losses are reported on given levels and did not increasetremendously might be due to improvements of the early warningsystems established in the Pacific and in China and improveddisaster preparedness. Expanding the digital database for theperiod before 1984 might be most appropriate for adding moredetail to the TC loss statistics and analyses. This task, however, willbe very time-consuming.

The economic loss analysis has underlined that different TCzones exist in Fujian. On average, a landfalling TC will cause at least10 million TC losses per county at the coastline. This will impact thelocal GDP by at least 0.2% in the counties of north and south Fujian,although the GDP in North Fujian is comparatively high. Unfortu-nately for Fujian, the counties with higher population, GDP, and

consequently higher maximum and average economic losses aresituated in the center and north of Fujian which has higher TClandfall frequency than the south.

More research will be conducted by the authors on the causes ofthe losses by TCs as little has been written on the triggers thatphysically cause the losses (e.g. precipitation andwind). This will bepossible as the database contains the start and end dates wheneconomic losses were inventoried, and might lead to a betterunderstanding of the complex correlation between the landfallingprocess and the associated economic losses.

It can be concluded that it is possible to break down economiclosses due to TCs on county-level in China, but the investigation iscostly and time-consuming. It becomes clear that local support isnecessary in order to access the weather-risk information. Never-theless, the exercise is important in order to classify TC losses andtypical impacts of TCs in the counties of China’s coastal provinces.This will enable improvements in non-traditional benefits such asaweather-index based insurance system for the economic TC lossesthat cannot be prevented by preparedness. The approach can beexpanded to any coastal province of China where NCC’s databaseprovides sufficient information.

Acknowledgements

Thanksmust be given to Jiang Tong, Su Buda, and Lucie Vaucel ofthe National Climate Center for preparing data, and to RunWang ofthe Institute of Urban Environment, Chinese Academy of Science inXiamen, for providing topographical maps and GIS layers. Workleading to this manuscript was supported by the National BasicResearch Program of China (973 Program) No. 2010CB428401, theSpecial Fund of Climate Change of the China MeteorologicalAdministration (CCSF-09-16), and the National Natural ScienceFoundation of China (40910177). Acquiring the loss databases andGIS layers was supported by the project on weather-index basedinsurance of the Deutsche Gesellschaft für Technische Zusamme-narbeit (GTZ) on behalf of Germany’s Federal Ministry for theEnvironment, Nature Conservation and Nuclear Safety. The posi-tions of Marco Gemmer and Thomas Fischer at the National Climate

M. Gemmer et al. / Quaternary International 244 (2011) 169e177 177

Center are supported by the German Development Cooperationthrough the Center for International Migration and Development(www.cimonline.de).

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