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Improvement of Wind Field Hindcasts for Tropical Cyclones Water Science and Engineering 2016, 9(1): 58e66 HOSTED BY Available online at www.sciencedirect.com Water Science and Engineering journal homepage: http://www.waterjournal.cn Improvement of wind field hindcasts for tropical cyclones Yi Pan a,b, Yong-ping Chen a,b,*, Jiang-xia Li a,b, Xue-lin Ding a,b a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China b College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China Received 16 August 2015; accepted 10 December 2015 Available online 21 February 2016 Abstract This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data. © 2016 Hohai University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Tropical cyclone; Parametric cyclone wind model; CCMP reanalysis data; Wind field hindcasts 1. Introduction The parametric cyclone wind model, proposed in the 1960s (Jelesnianski, 1965, 1966; Russell, 1968), has been A tropical cyclone (usually referred to as a typhoon in the widely used in the hindcasting of wind fields of tropical Western Pacific and a hurricane in the Eastern Pacific and the cyclones due to its simplicity and accuracy (Dube et al., Atlantic) may cause significant storm surges and strong waves 1985; Ginis and Sutyrin, 1995; Lee, 2008). Different para- and poses a great threat to coastal areas. The accurate hindcasting metric cyclone wind models have been proposed and used of tropical cyclone wind fields is important in terms of reducing around the world for the hindcasting of tropical cyclones. and preventing coastal disasters, e.g., through the assessment of Three tropical cyclone models in particular, proposed by sea levee systems, the evaluation of wave conditions, and the Jelesnianski (1966), Holland (1980),andKnaff et al. (2007), optimization of protection strategies against future cyclones. respectively, have been commonly used in published studies. The Holland (1980) model was strongly recommended by the advanced circulation (ADCIRC) model research group (e.g., This work was supported by the National Natural Science Foundation of Mattocks et al., 2006). The Knaff et al. (2007) model, also China (Grants No. 51309092 and 51379072), the Special Fund for Public Welfare Industry of the Ministry of Water Resources of China (Grant No. known as the D09 model (DeMaria et al., 2009), was suc- 201201045), the Natural Science Fund for Colleges and Universities in Jiangsu cessfully applied in the hindcasting of many cyclone events Province (Grant No. BK20130833), and the Fundamental Research Funds for (Pande et al., 2002; Mattocks et al., 2006; Xie et al., 2006; the Central Universities (Grants No. 2015B16014 and 2013B03414). Mattocks and Forbes, 2008; DeMaria et al., 2009; Sampson * Corresponding author. et al., 2013). In these models, the radius of maximum E-mail address: [email protected] (Yong-ping Chen). Peer review under responsibility of Hohai University. wind, which controls the eye diameter of the tropical http://dx.doi.org/10.1016/j.wse.2016.02.002 1674-2370/© 2016 Hohai University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). Yi Pan et al. / Water Science and Engineering 2016, 9(1): 58e66 59 cyclone, is considered a key factor in determining the hind- 2. Existing models for tropical cyclone hindcasting casted wind fields. It can be estimated either through some empirical formulas (Graham and Nunn, 1959; Knaff et al., 2.1. Parametric cyclone wind model 2007) or through the radii of several characteristic wind speeds (Xie et al., 2006; Gao et al., 2013). Although the In classical parametric cyclone wind models, the wind field cyclone wind models can reproduce the wind fields in the is considered to be composed of two different storm compo- center area of the tropical cyclone, the modeled wind fields at nents, the moving component and the rotating component. The a greater distance from the cyclone are not accurate enough, moving component is due to the movement of the tropical since the major factors that control wind fields farther away cyclone center, and the rotating component is due to the bal- from the cyclone might be some other weather systems, ance of the pressure gradient force, the Coriolis force, the rather than the tropical cyclone. centrifugal force, and the friction force. Long-term reanalysis wind data obtained from the data The total wind vector can be written as assimilation model have also been widely used for the v ¼ v þ v ð Þ hindcasting of the wind fields due to their accessibility and mov rot 1 good accuracy. The data provided by the National Centers v v for Environmental Prediction (NCEP), the European Centre where is the total wind vector, mov is the wind vector v for Medium-Range Weather Forecasts (ECMWF), and the induced by the moving component, and rot is the wind vector cross-calibrated multi-platform (CCMP) are the most induced by the rotating component. commonly used reanalysis data. Those data have been Jelesnianski (1965) provided an empirical formula to v widely used to solve ocean and coastal hindcasting calculate mov: problems (e.g., Brenner et al., 2007; Lu¨ et al., 2014; 8 Moeini et al., 2010; Wu and Chiang, 2007). However, pre- r > v < vious studies have shown that the wind speeds near the < mc r Rmax r þ Rmax center of the tropical cyclone obtained from the reanalysis vmov ¼ ð2Þ > Rmax data are generally lower than the actual values (Cavaleri and : v mc þ r Rmax Sclavo, 2006; Signell et al., 2005), and corrections are r Rmax needed before use. v In this paper, some improvements in the hindcasting of wind where mc is the moving velocity vector of the cyclone center, fields for tropical cyclones are presented. Three commonly r is the distance from the cyclone center, and Rmax is the radius used cyclone wind models, proposed by Jelesnianski (1966), of maximum wind. Holland (1980),andKnaff et al. (2007), respectively, were Later, Jelesnianski (1966) provided a modified formula to v first used in this study to hindcast two typical tropical cyclones, calculate mov: i.e., Fanapi and Meranti, which occurred in 2010. The perfor- rR mance of the three models for the hindcasting of cyclone wind v ¼ v max ð3Þ mov mcr2 þ R2 fields is compared and discussed. As both the tropical cyclone max model and the reanalysis data have their own limitations, i.e., Ueno (1981) used an exponential function to calculate vmov: the tropical cyclone model cannot reproduce the characteristics p j À j of the wind field far from the tropical cyclone center, and the r Rmax vmov ¼ vmcexp À ð4Þ reanalysis data tends to underestimate high winds, two modi- 4 Rmax fication methods are proposed to improve the accuracy of Jakobsen and Madsen (2004) used a similar exponential hindcasted wind fields. One is the superposition method, which function to calculate vmov: superposes the wind field calculated from the tropical cyclone model on the reanalysis data, and the other is the direct r vmov ¼ vmcexp À ð5Þ modification method, which directly modifies the reanalysis RG wind speed around the tropical cyclone center, with an amplification factor that varies with the ratio of the measured where RG is the length scale of the moving component and is maximum wind speed to the reanalyzed value as well as the about 500 km. distance from the tropical cyclone center. Eq. (5) was used to calculate the wind vector induced by The details are described in the following sections. Section 2 the moving component in this study. The value of RG was set presents existing models for the hindcasting of cyclone wind to 500 km. fields. Section 3 gives a brief description of the studied area and The rotating component is considered to be more signifi- the selected tropical cyclones. Section 4 presents a comparison cant to the total wind velocity than the moving component. of hindcasted results using different tropical cyclone models or Three different types of models, proposed by Jelesnianski different methods for calculation of the radius of maximum (1965), Holland (1980), and Knaff et al. (2007), respec- wind. Section 5 proposes two modification methods for the tively, are commonly used to calculate the wind velocity hindcasting of tropical cyclone wind fields. Section 6 concludes induced by the rotating storm component. The details are the paper. given below. 60 Yi Pan et al. / Water Science and Engineering 2016, 9(1): 58e66 Jelesnianski (1965) proposed a parametric rotating storm where vrotx and vroty are the x-andy-components of vrot, model, which was later modified by Jelesnianski (1966).
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