The Use of a Spectral Nudging Technique to Determine the Impact of Environmental Factors on the Track of Typhoon Megi (2010)

atmosphere

Article The Use of a Spectral Nudging Technique to Determine the Impact of Environmental Factors on the Track of Typhoon Megi (2010)

Xingliang Guo ID and Wei Zhong * Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101, China; [email protected] * Correspondence: [email protected]

Received: 3 October 2017; Accepted: 7 December 2017; Published: 20 December 2017

Abstract: Sensitivity tests based on a spectral nudging (SN) technique are conducted to analyze the effect of large-scale environmental factors on the movement of typhoon Megi (2010). The error of simulated typhoon track is effectively reduced using SN and the impact of dynamical factors is more significant than that of thermal factors. During the initial integration and deflection period of Megi (2010), the local steering flow of the whole and lower troposphere is corrected by a direct large-scale wind adjustment, which improves track simulation. However, environmental field nudging may weaken the impacts of terrain and typhoon system development in the landfall period, resulting in large simulated track errors. Comparison of the steering flow and inner structure of the typhoon reveals that the large-scale circulation influences the speed and direction of typhoon motion by: (1) adjusting the local steering flow and (2) modifying the environmental vertical wind shear to change the location and symmetry of the inner severe convection.

Keywords: spectral nudging; typhoon track; environmental factors

1. Introduction Although the forecasting accuracy of typhoon tracks has been effectively improved in recent years through observations, numerical simulations, data assimilation and studies of the physical mechanisms affecting typhoon movement [1], the accurate prediction of abnormal typhoon tracks, including their continuous changes and abrupt deflection, is still not possible [2]. Therefore, an extensive study of the physical mechanism underlying the abnormal motion of typhoons is fundamental to improving their simulation and prediction. Typhoon Megi (2010) was the most powerful typhoon over the western North Pacific Ocean in 2010. It was generated in an ocean area southwest of Guam on 11 October and made landfall at Luzon Island on 18 October. On 23 October, Megi made a second landfall over Fujian province in China and dissipated the next day. From 0600 UTC 19 October to 1200 UTC 20 October, Megi entered the South China Sea (SCS) and suddenly made a sharp northward turn, which was the most noteworthy feature during its life and led to difficulties in predicting its track. This unusual track change was not predicted accurately by any of the leading operational centers, making it difficult for the prevention and reduction of typhoon damage. Several studies have investigated the sudden track deflection of Megi by considering the effects of major weather systems on the typhoon system and its inner structure [3–5]. Based on the studies of Kieu et al. [6] and Peng et al. [7], large-scale environmental flow plays the most important role in Megi’s movement. Besides, it has been shown that the western Pacific subtropical high (WPSH) and an approaching eastward-moving mid-latitude trough played an important role in Megi’s sudden northward deflection [8]. And Megi’s northward track deflection was mainly determined by the influence of mid-latitude circulation [9].

Atmosphere 2017, 8, 257; doi:10.3390/atmos8120257 www.mdpi.com/journal/atmosphere Atmosphere 2017, 8, 257 2 of 17

Because the movement of a typhoon is mainly determined by the large-scale environmental flow [10,11], it is critical for a limited-area model to appropriately describe the large-scale background circulation. To ensure that the large-scale environmental flow simulated by a limited-area model remains similar to observations or analysis, Waldron et al. [12] proposed a spectral nudging (SN) technique, which was then implemented by Storch et al. [13]. The main purpose of SN technique is to correct the simulated large-scale circulation without deteriorating regional scales. Up to now, the SN technique has been widely used in regional climate models. Many studies have shown that it can improve the simulation of typhoon climatological activity [14,15]. Recently, some studies have used the SN technique in typhoon case studies. Feser and Storch [16] used the SN technique in the simulation of typhoon Winnie (1997). It was found that the SN technique could improve the simulation of Winnie’s motion and the evolution of the typhoon. Li et al. [17] conducted a high-resolution simulation of typhoon Longwang (2005) with the Weather Research and Forecasting (WRF) model and found that the SN technique could effectively simulate the formation and evolution of the typhoon. Wang et al. [18] adopted an approach that combined dynamical initialization and SN to produce a simulated track and intensity of Megi (2010) that was very similar to the observation. Thus, it has been demonstrated that the SN technique can effectively improve typhoon simulation and especially the simulation of a typhoon track. However, the effects of environmental factors on the typhoon track are extremely complicated. Different physical factors in the environmental field will have different impacts on the deflection of a typhoon track. On the other hand, environmental factors will interact with other outside forcings (e.g., topographic forcing) or the inner structure of the typhoon itself, leading to the deflection of a typhoon track. Megi was under the influence of several systems and several factors during the change in its track, in which it experienced different large-scale circulation systems and passed over the high terrain of Luzon Island. Thus, its path included not only a deflection period after leaving Luzon Island but also a notable period of southward movement when approaching and landing on the island. Therefore, investigating the effect of different factors (dynamical or thermal) of the environmental field on Megi’s track during its evolution will not only help to select a proper configuration for the application of the SN technique but also enable a better understanding of the physical mechanisms by which environmental factors affect the typhoon track. In this study, the SN technique is used in the simulation of typhoon Megi and sensitivity tests are conducted to investigate the effect of different environmental factors of the environmental field on Megi’s track before and after it passes over Luzon Island. The experimental design in this study is different from that of many previous studies [19–23] in which SN is often used to correct large-scale circulation in the upper atmosphere levels. Therefore, the experimental design in this study has certain limitations and is unlikely to get optimal simulation results. Since the purpose is to investigate the impact of different environmental field, which affects specificity of the experimental design in this study, SN will be adopted at all model levels regardless of environmental field at upper or lower levels. The experimental design and SN technique are introduced in Section2. Section3 describes the sensitivity tests and results. Section4 explores the physical mechanism of large-scale environmental effects on the typhoon track in the different periods. A discussion of the results and the conclusions of the study are given in Section5.

2. Experimental Design and SN

2.1. Experimental Design of Numerical Simulation The numerical simulations presented in this study are conducted using the WRF model (WRFV3.4), which is developed by a collaboration of research institutions, including the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The model’s initial and lateral boundary conditions are interpolated from NCEP Final Operational Global Analysis (FNL) and the input sea surface temperature (SST) data are obtained from the National Atmosphere 2017, 8, 257 3 of 17

Oceanic and Atmospheric Administration (NOAA) SST analysis. The model integrates from 0600 UTC 17 October to 0600 UTC 21 October. The simulation period contains the southward moving period when the typhoon approaches and moves over Luzon Island, as well as the deflection period after it leaves the island. There are 246 × 176 grid points in each of the zonal and meridional directions, with a horizontal grid spacing of 18 km and 36 vertical layers between the model top at 50 hPa and the surface. The selected simulation range covers the full range of the movement of Megi during the simulation period and contains the major weather systems that affect its track, i.e., the WPSH, a continental high-pressure system in the northeast of China and the South Asian High (SAH). After conducting several tests with different configuration of physical parameterization schemes, we select the one (Table1) with the best simulation result as the configuration of physical parameterization schemes for the control experiment (CTRL). WRF Single-Moment 6-class (WSM6) scheme is an option of microphysics schemes in WRF.

Table 1. Physical parameterization schemes for CTRL.

Microphysics WSM6 Longwave Radiation RRTM Shortwave Radiation Dudhia Surface Layer Monin-Obukhov Land Surface Noah Planetary Boundary layer MYNN2.5 Cumulus Parameterization Kain-Fritsch

Figure1 shows the simulated typhoon track of CTRL compared with the observation. To quantitatively analyze the accuracy of the track simulated by CTRL and the following sensitivity tests, the error of the typhoon track is calculated: q 2 2 Error = (xobs − xmodel) + (yobs − ymodel) (1) where xobs − xmodel and yobs − ymodel are the zonal and meridional distances between the observation and model results, respectively. The mean errors for the first 24, 48, 72 and 96 h of the typhoon track simulated by CTRL are calculated and are 23, 20, 37 and 86 km, respectively. It can be seen that the error of the first 48 h integration is small but increases rapidly during the latter 48 h. From the observed typhoon track (Figure1, 0600 UTC 19 October (i.e., 48 h after the initial integration time) is determined to be the deflection moment when the southwestward moving typhoon begins to turn northward. By setting this moment as the demarcation point, the errors before and after the deflection moment are 20 and 160 km, respectively. In conclusion, CTRL precisely simulates the deflection moment as well as the speed and direction of typhoon movement before the deflection. However, the simulated track after the deflection needs to be improved. The background circulation patterns of NCEP and CTRL are analyzed in this section (Figure2). Before the deflection moment (Figure2a), the strong WPSH around 20 ◦–25◦ N and the continental high in the northeast of China prevents the typhoon from moving northward. The anticyclonic circulation south of the high joins with the cyclonic circulation north and northwest of the typhoon, forming a strong jet that forces the typhoon to move westward. Compared to the background circulation simulated by CTRL (Figure2c), there is a minor deviation in the 500 hPa geopotential height field between the CTRL and the NCEP. The positions of the WPSH and the continental high are precisely simulated by the CTRL. The deviation in the 850 hPa wind field is also minor. Thus, the simulated typhoon track is similar to the observed track before the deflection, both moving southwestward. However, after the deflection moment (Figure2b), the subtropical high moves eastward at the 500 hPa level and its influence on the evolution and movement of the typhoon reduces. Due to the abrupt enhancement of the cross-equatorial flow, the southwester south of the typhoon is rapidly enhanced, Atmosphere 2017, 8, 257 4 of 17

Atmosphere 2017, 8, 257 4 of 17 geopotentialAtmosphere 2017 ,height 8, 257 field simulated by CTRL (Figure 2d) has a large deviation from the NCEP.4 Theof 17 simulated subtropical high does not move eastward. The simulated cross-equatorial flow is so strong whichandgeopotential the leads simulated theheight typhoon west field wind tosimulated turn at the to north. 850by CTRLhPa At level this (Figure moment,is much 2d) hasstronger the a geopotential large than deviation that height in thefrom fieldNCEP, the simulated NCEP. leading The byto theCTRLsimulated track (Figure simulated subtropical2d) has by a high largeCTRL does deviation deviating not move from to theeastward. the east NCEP. after The The the simulated simulated track deflection. cross-equatori subtropical highal flow does is not so strong move eastward.and theIn all,simulated The the simulated simulation west wind cross-equatorial result at the of 850 CTRL hPa flow level precisely is so is strong much reflects andstronger the the simulated than southward that west in thelandfall wind NCEP, at process, the leading 850 hPa the to deflectionlevelthe track is much simulated mome strongernt asby thanwellCTRL thatas deviating the in speed the NCEP, to and the leading directioneast after to ofthe typhoon track simulateddeflection. movement by CTRLbefore deviating the deflection. to the However,east afterIn all, the due the track to simulation the deflection. simulated result error of ofCTRL large -preciselscale environmentaly reflects the field, southward the simulated landfall error process, of Megi’s the deflectionIn all, process themoment simulation is as significant. well result as the of CTRL speed precisely and dire reflectsction of the typhoon southward movement landfall process,before the the deflection. deflection momentHowever, as due well to asthe the simulated speed and error direction of large-scale of typhoon environmental movement field, before the si themulated deflection. error However,of Megi’s duedeflection to the process simulated is significant. error of large-scale environmental field, the simulated error of Megi’s deflection process is significant.

Figure 1. Simulated typhoon track by CTRL (in purple) compared with the observed track (in black). Figure 1. Simulated typhoon track by CTRL (in purple) compared with the observed track (in black). Figure 1. Simulated typhoon track by CTRL (in purple) compared with the observed track (in black).

(a) (b)

Figure 2. NCEP geopotential height at 500 hPa (unit: hPa), wind field at 850 hPa, areas where wind Figure 2. NCEP geopotential(c) height at 500 hPa (unit: hPa), wind ﬁeld at 850(d hPa,) areas where wind −1 speed is more than 1515 msms−1 (dashes)(dashes) at at ( (aa)) 0600 0600 UTC UTC 18 18 and and ( (bb)) 060 06000 UTC UTC 20; simulated geopotential heightFigure at2. 500NCEP hPa geopotential (unit: hPa), wind height field ﬁeld at 500deviation hPa (unit: between hPa), the wind simulation field at result 850 hPa, and areas NCEP where at 85 850 0wind h hPaPa −1 atspeed ( c) 0600 is more UTC than 18 and 15 ms (d) 0600 (dashes) UTC at 20. (a ) 0600 UTC 18 and (b) 0600 UTC 20; simulated geopotential height at 500 hPa (unit: hPa), wind field deviation between the simulation result and NCEP at 850 hPa at (c) 0600 UTC 18 and (d) 0600 UTC 20.

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2.2. The SN Technique The aim of the SN technique is to add a new term to the tendencies of the variables that relax the selected part of a spectrum to the corresponding waves from a reanalysis, ensuring that the model simulates large-scale components that are close to the reanalysis data [12,13,24]. First, a nudged model variable Ψ is selected and then decomposed together with the corresponding reanalysis variable Ψa:

Jm,Km m Ψ(λ, φ, t) = ∑ αj,k(t) exp(ijλ/Lλ) exp(ikφ/Lφ) (2) j=−Jm,k=−Km

Ja,Ka a Ψa(λ, φ, t) = ∑ αj,k(t) exp(ijλ/Lλ) exp(ikφ/Lφ) (3) j=−Ja,k=−Ka where λ and ϕ are, respectively, the zonal and meridional coordinates, t represents time, Lλ and Lφ are the zonal and meridional extensions of area, respectively, Jm and Km are the highest wave numbers decomposed from the model variables and Ja and Ka are the highest wave numbers decomposed from the reanalysis variables. The nudging terms are obtained by Ψ minus Ψa multiplied by a coefﬁcient:

Ja,Ka h a m i ∑ ηj,k αj,k(t) − αj,k(t) exp(ijλ/Lλ) exp(ikφ/Lφ) (4) j=−Ja,k=−Ka with the coefﬁcient ηj,k, which can vary with height. The overall SN technique can be mathematically expressed as follows:

∂Ψ Ja,Ka h i = L(Ψ) − η αa (t) − αm (t) exp(ijλ/L ) exp(ikφ/L ) (5) ∂t ∑ j,k j,k j,k λ φ j=−Ja,k=−Ka where L is the model operator. As a result of SN, a specific model variable can be selected and constrained close to the reanalysis variable at a specific scale or height. Thus, the SN technique can reduce the simulated large-scale environmental flow deviation. It can also reflect the influence of different environmental factors on the simulation results by selecting the nudging variables. In this study, SN in the WRF model is applied to reduce the deviation of the simulated large-scale environmental flow. The SN scheme in the WRF model can be used to select and nudge zonal and meridional wind components (u, v), potential temperatures (θ) and geopotential (Φ). It can also nudge at all levels or only above a specified model level. In SN, the zonal and meridional wave numbers (Ja and Ka) are chosen to correspond to the chosen spatial scales in the zonal and meridional directions. In this study, sensitivity tests are conducted by selecting nudging variables to obtain the optimal parameter configuration for the simulation of typhoon Megi and to analyze the physical mechanisms by which environmental factors affect the typhoon track. It’s important to note that for operational practice, we don’t have the reanalysis field during the entire integration period, except for the initial time. Therefore, sensitivity tests which nudge over all simulation intervals in this study render this work unrealistic for most practical applications. Besides, the initial and boundary conditions for this study are taken from the NCEP FNL reanalysis. This reanalysis data is good for research purposes but it’s in general not a good proxy for actual forecasts. In spite of this limitation, investigating the physical mechanism of typhoon track based on spectral nudging technique still has important theoretical significance. Atmosphere 2017, 8, 257 6 of 17

3. Effect of Different Large-Scale Environmental Factors

3.1. Sensitivity Tests According to the available nudging variables in the WRF model, sensitivity tests are undertaken by selecting different nudging variables (Table2). SN1 nudges zonal and meridional wind components; SN2 nudges wind components and geopotential; SN3 nudges potential temperature; and SN4 nudges all of the available variables in the WRF model. Because the wind and geopotential fields reflect the dynamical features of the environmental field, while the potential temperature field reflects the thermal features, SN1 and SN2 reflect the influence of dynamical factors of the large-scale environmental field, while SN3 reflects the influence of thermal factors of the large-scale environmental field. SN4 reflects the joint influence of dynamical and thermal factors. Considering the basic spatial scale of a typhoon, the wave numbers chosen in the sensitivity tests are Ja = 4 and Ka = 3, which corresponds to spatial scales of 1000 km in both the zonal and meridional directions.

Table 2. Experimental design of sensitivity tests.

Tests Variables Height Range Wavenumbers CTRL No No No SN1 (u, v) all levels Ja = 4, Ka = 3 SN2 (u, v) Φ all levels Ja = 4, Ka = 3 SN3 Θ all levels Ja = 4, Ka = 3 SN4 (u, v) Φ θ all levels Ja = 4, Ka = 3

3.2. Simulation Results Figure3 displays the simulated tracks and temporal evolution of the track errors in the sensitivity tests compared with CTRL. It can be seen that the tracks simulated by SN1, SN2 and SN4 are generally very similar. Although deflection moment simulated by these three tests is nearly 6 h later than the observed deflection moment, the simulated typhoon tracks are very similar to the observed track. This is particularly true in the period after the deflection, during which the tracks simulated by these three tests are greatly improved compared with CTRL, which deviates far from the observed track. It is important to note that in these three tests, the simulated typhoon is moving westward stably when it approaches and lands on Luzon Island (0000 UTC 18 October to 0600 UTC 19 October); thus, the simulated typhoon tracks clearly deviate to the north compared with CTRL and the observed track. The deflection moment simulated by SN3 is about 18 h later than the observed deflection moment and the simulated track after the deflection is improved compared with the CTRL but still deviates to the east. The mean track errors during the different simulation periods are calculated (Table3). The mean track errors of the sensitivity tests are smaller than that of CTRL in the original integration period (0–24 h) and the whole integration period (0–96 h) but increased substantially in the integration period (0–48 h) when the typhoon passes over Luzon Island. Overall, the use of SN improves the track simulation when the typhoon is over the ocean and especially improves the simulation of Megi’s northward deflection, its move speed and direction after the deflection. However, the simulated tracks in tests using SN deviates from the observed track when the typhoon passes over high terrain.

Table 3. Mean track errors in the ﬁrst 24, 48, 72, 96 h and during different periods (units: km).

Tests 0–24 h 0–48 h 0–72 h 0–96 h Landfall Period Deﬂection Period CTRL 23 20 37 86 17 82 SN1 15 34 36 32 53 39 SN2 15 33 35 31 53 37 SN3 25 47 44 52 69 47 SN4 17 35 34 31 60 32 Atmosphere 2017, 8, 257 7 of 17

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Figure 3. Simulated typhoon tracks and temporal evolution of track errors (unit: km) in the ﬁrst group Figure 3. Simulated typhoon tracks and temporal evolution of track errors (unit: km) in the first group of sensitivity tests; where black, purple, blue, sky blue, brown, red correspond with observation, CTRL, of sensitivity tests; where black, purple, blue, sky blue, brown, red correspond with observation, SN1, SN2, SN3, SN4, respectively. CTRL, SN1, SN2, SN3, SN4, respectively.

TheThe effect effect of of different different variables variables on on the the typhoon typhoon tr trackack during during different different periods periods is is assessed. assessed. In In the the wholewhole simulation simulation period, period, SN4, SN4, which which nudges nudges all all av availableailable variables variables and and SN2, SN2, which which nudges nudges the the wind wind andand geopotential geopotential (dynamical (dynamical factor) factor) fields, fields, has has the the smallest smallest mean mean track track errors, errors, each each with with a a value value of of 3131 km. km. SN1, SN1, which which only only nudges nudges the the wind wind field, field, has has a a mean mean track track error error of of 32 32 km, km, slightly slightly larger larger than than thatthat of of SN2 SN2 and and SN4. SN4. SN3, SN3, which which only only nudges nudges the the potential potential temperature temperature (thermal (thermal factor), factor), has has a a mean mean tracktrack error error of 52 km.km. BasedBased onon the the observed observed typhoon typhoo track,n track, we we define define a landfall a landfall period period from from 0600 0600 UTC UTC18 October 18 October to 1800 to 1800 UTC UTC 18 October 18 October and aand deflection a deflection period period from from 0600 0600 UTC UTC 19 October 19 October to 1200 to 1200 UTC UTC20 October. 20 October. Mean Mean track track errors errors in in these these two two periods periods are are calculated. calculated. During the the deflection deflection period, period, CTRLCTRL has has the the largest largest mean mean track track error, error, with with a a valu valuee of of 82 82 km. km. The The mean mean track track errors errors of of tests tests where where SNSN is is applied applied are are all all greatly greatly redu reduced,ced, especially especially SN4, SN4, whose whose mean mean track track error error decreases decreases to to 32 32 km, km, withwith an an apparent apparent improvement ofof tracktrack simulation.simulation. However, However, during during the the landfall landfall period, period, CTRL CTRL has has the thesmallest smallest mean mean track track error, error, with awith value a value of 17 km.of 17 The km. mean The track mean errors track of errors tests where of tests SN where is applied SN allis appliedincreases, all especiallyincreases, SN3,especially whose SN3, mean whose track mean error track increases error to increases 69 km. The to 69 mean km. trackThe mean error track of SN1 error and ofSN2 SN1 is and smaller SN2 than is smaller that of than SN3 that but of at SN3 53 km but is at still 53 three km is times still three larger times than larger that of than CTRL. that of CTRL. FromFrom the the analysis analysis above, above, it itcan can be beconcluded concluded that that during during the thewhole whole simulation simulation period, period, the typhoonthe typhoon track track is more is more sensitive sensitive to the to effects the effects of environmental of environmental dynamical dynamical factors factors than than the theeffects effects of environmentalof environmental thermal thermal factors. factors. Beca Becauseuse the large-scale the large-scale wind wind field fieldand andgeopotential geopotential height height field fieldare relatedare related to geostrophic to geostrophic balance, balance, nudging nudging just just wind wind (geopotential) (geopotential) oror both both wind wind and and geopotential geopotential producesproduces no no obvious obvious distinction distinction in in the the simulation simulation results. results. During During the the diff differenterent simulation simulation period, period, nudgingnudging the environmentalenvironmental field field could could improve improve the simulationthe simulation of the typhoon’sof the typhoon’s northward northward deflection. deflection.But when But the typhoonwhen the crosses typhoon over crosses high over terrain, high the terrain, simulated the simulated tracks deviate tracks substantially. deviate substantially. It’sIt’s important important to to note note that that sensitivity sensitivity tests tests integrated integrated from from 1200 1200 UTC UTC 17 17 to to 0600 0600 UTC UTC 21 21 are are conducted.conducted. Simulation Simulation results results (figure (figure not not shown) shown) are are similar similar to that to that of previous of previous study. study. Therefore, Therefore, the simulationthe simulation results results above above can be can representative be representative to investigate to investigate the mechanism the mechanism of typhoon of typhoon motion. motion.

Atmosphere 2017, 8, 257 8 of 17 Atmosphere 2017, 8, 257 8 of 17

4. Analysis of the Influence Influence of Environmental Variables From the results of the sensitivity tests, it is found that tests using SN improves the track simulation. Because Because different different envi environmentalronmental variables variables have have different different influences influences on the on thetyphoon, typhoon, the typhoonthe typhoon track track responds responds differently differently to environmenta to environmentall dynamical dynamical factors and factors thermal and factors. thermal Nudging factors. justNudging the wind just the orwind both orwind both and wind geopotential and geopotential produces produces no obvious no obvious distin distinctionction in in the the simulation simulation results. TheThe remainderremainder of of this this section section considers considers the influencethe influence of environmental of environmental dynamical dynamical and thermal and thermalfactors on factors the typhoon on the typhoon track based track on based SN1 andon SN1 SN3. and SN3.

4.1. Effect on the Overall Typhoon System A large number of studies have suggested that the track and intensity of a typhoon system is closely relatedrelated toto the the large-scale large-scale background background ﬂow flow and and thermal thermal structure structure [25,26 ].[25,26]. Based onBased their on studies, their ◦ ◦ studies,the environmental the environmental mean wind mean at wind each at vertical each vertical level of level a 10 of ×a 10°10 ×rectangular 10° rectangular area area around around on theon thetyphoon typhoon center center is calculated,is calculated, as as well well as as the the temporal temporal evolution evolution of of the the steering steering ﬂowflow ofof thethe whole (850–300 hPa) and lower (800–600 hPa)hPa) tropospheretroposphere (Figure(Figure4 4a).a).

(a) (b)

−1 Figure 4. Temporal-spatial evolution of environmentalenvironmental mean wind (black wind vector, units: ms−1),), -1 temperature anomalyanomaly inin thethe corecore area area (dashes, (dashes, units: units: K) K) and and steering steering ﬂow flow (wind (wind vectors, vectors, units: units: ms ms-1) in) in(a) ( NCEP,a) NCEP, (b )(b CTRL,) CTRL, (c) ( SN1c) SN1 and and (d )(d SN3.) SN3. The The environmental environmental mean mean wind wind is is calculated calculated by by 10 10°◦ × × 1010°◦ rectangle area centering at the typhoon center. The temperature anomaly is the difference of the mean temperature in the core areaarea (2(2°◦ ×× 2°)2◦) between between the the present present time and initial time. Black wind vectors below represent the average direction vectors by six hours by observation.observation. Red and green vectors respectively represent steering flow ﬂow of the wholewhole troposphere (850–300 hPa) and lower troposphere (800–600 hPa).

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Compared to the average direction vectors of the typhoon during the 6 h observation (Figure4a), it can be seen that from the beginning integration moment to 0000 UTC 18 October, the environmental mean winds at all tropospheric levels are northeaster or east wind and the steering flow of the whole or lower troposphere is also northeaster. This corresponds with the typhoon’s fast westward movement while deviating to the south. At 0600 UTC 18 October, the typhoon lands on Luzon Island. The steering flow of the whole or lower troposphere is predominantly the east wind component but a south wind component is also present. This south wind component is more obvious in the lower troposphere, which is not in accordance with the typhoon’s southward track when crossing over the island. Xu et al. [27] analyzed the relationship between the steering flow of both the whole (850–300 hPa) and lower troposphere (800–600 hPa) and the Megi (2010) track. The results also showed that when the typhoon crossed over the island, there was a deviation between the environmental wind direction and the typhoon’s direction of movement. In this period, the typhoon’s movement is probably mainly affected by other elements (e.g., terrain). By 1200 UTC 18 October, the typhoon has crossed over Luzon Island and entered the SCS, continuing to move westward. From 0000 UTC 19 October onward, the steering flow of the whole and lower troposphere weakens, slowing down the typhoon’s westward movement. At 0600 UTC 19 October, the environmental mean wind in the lower troposphere begin to turn to a southwester, while the wind in the upper troposphere is still an east wind. At this moment, the typhoon’s direction of movement begins to turn northward. At 1800 UTC 19 October, the steering flow of the whole and lower troposphere is enhanced and a strong northeastward steering flow is maintained from this moment. Thus, the typhoon’s direction of movement gradually turns from westward to the northward. By 1200 UTC 20 October, the typhoon has completed the northward deflection process and continues moving northward. After the deflection, the steering flow of the lower troposphere is in correlation with the typhoon’s movement. In all, the steering flow plays an important role during the original integration period and after the deflection, especially the steering flow of lower troposphere (800–600 hPa). But the large-scale environmental flow has no obvious impact on the typhoon track when it crosses over the island. Comparing the environmental mean wind and steering flow among CTRL, SN1 and SN3, it can be seen that from the beginning integration moment to 0000 UTC 18 October, the steering flow of lower troposphere in CTRL points to the west (Figure4b). This explains the fact that the simulated track by CTRL moves eastward and deviates to the north slightly. Meanwhile, the environmental mean wind and steering flow in SN1 (Figure4c) are mainly northeaster, corresponding with the typhoon’s westward movement while deviating to the south. During the period when the typhoon passes over Luzon Island, the deviation of the environmental mean wind and steering flow between SN1 and NCEP is small, corresponding with the simulated track deviating to the north. However, the steering flow of the lower troposphere in CTRL is a northeaster, which modifies the south wind component of the environmental steering flow and successfully simulates the southward track when the typhoon passes over the island. After 1200 UTC 19 October, there is a large eastward component in the steering flow in CTRL, corresponding with the fact that the simulated track deviates substantially to the east. The deviation of the environmental mean wind and steering flow between SN1 and NCEP is very small. Steered by the modified steering flow, the simulated track is very similar to the observed track. From the temporal evolution of the steering flow of the whole and lower tropospheres in SN3 (Figure4d), it can be seen that the steering flow in SN3 is modified less than in SN1 and thus there is no significant impact on the typhoon track. To determine the relationship between environmental thermal factors and the typhoon intensity and track, we define the present temperature anomaly as the difference in the mean temperature in the core area (2◦ × 2◦) between the present time and the initial time. Comparing the temporal evolution of the temperature anomaly (Figure4a), the mean temperature anomaly of the whole troposphere (Figure5b) and the intensity of the typhoon (Figure5a), it can be seen that from 0600 UTC 17 October to 0000 UTC 18 October the mean temperature anomaly of the whole troposphere is almost positive, with a positive area located at 600–400 hPa or below 800 hPa. In this period, the intensity of the AtmosphereAtmosphere2017 2017, 8,, 2578, 257 1010 of 17of 17

the typhoon passes over Luzon Island. In this period, the mean temperature anomaly of the whole typhoon is slightly enhanced. From 0000 UTC 18 October to 0000 UTC 19 October, the typhoon troposphere is negative and the maximum value of the negative area is located at 600–400 hPa, in passes over Luzon Island. In this period, the mean temperature anomaly of the whole troposphere is correlation with the weakened typhoon intensity. From 1200 UTC 19 October to 1800 UTC 19 October, negative and the maximum value of the negative area is located at 600–400 hPa, in correlation with the the temperature anomaly of the upper troposphere is positive, while for the lower troposphere it is weakened typhoon intensity. From 1200 UTC 19 October to 1800 UTC 19 October, the temperature negative but small and the mean temperature anomaly of the whole troposphere is also positive. In anomaly of the upper troposphere is positive, while for the lower troposphere it is negative but this period, the intensity of the typhoon is enhanced for a short time. After 1800 UTC 19 October, the small and the mean temperature anomaly of the whole troposphere is also positive. In this period, intensity of the typhoon is maintained. The temperature anomaly of the upper troposphere is the intensity of the typhoon is enhanced for a short time. After 1800 UTC 19 October, the intensity of positive, while that of the lower troposphere is negative and the mean temperature anomaly of the the typhoon is maintained. The temperature anomaly of the upper troposphere is positive, while that whole troposphere is negative and almost consistent over time. In all, when the typhoon passes over of the lower troposphere is negative and the mean temperature anomaly of the whole troposphere is the island, the mean temperature anomaly of the whole troposphere is negative, in correlation with negative and almost consistent over time. In all, when the typhoon passes over the island, the mean the weakened intensity of the typhoon. When the typhoon passes over the ocean surface, the mean temperature anomaly of the whole troposphere is negative, in correlation with the weakened intensity temperature anomaly of the whole troposphere is positive and the intensity of the typhoon is of the typhoon. When the typhoon passes over the ocean surface, the mean temperature anomaly enhanced. The analysis described above confirms that the temperature anomaly in the core area of the whole troposphere is positive and the intensity of the typhoon is enhanced. The analysis reflects the evolution of a warm-core structure in the typhoon center and has an important influence described above confirms that the temperature anomaly in the core area reflects the evolution of a on the evolution of typhoon intensity [28]. The temperature anomaly of the middle and upper warm-core structure in the typhoon center and has an important influence on the evolution of typhoon tropospheres has the most significant impact on typhoon intensity. intensity [28]. The temperature anomaly of the middle and upper tropospheres has the most significant Comparing the modification to the temperature anomaly in CTRL and the sensitivity tests in the impact on typhoon intensity. core area, it can be seen that the results simulated by SN1 (Figure 4c) and SN3 (Figure 4d) are similar Comparing the modification to the temperature anomaly in CTRL and the sensitivity tests in the to the environmental field in terms of their variation and magnitude. However, the intensity core area, it can be seen that the results simulated by SN1 (Figure4c) and SN3 (Figure4d) are similar to simulated by SN1 and SN3 is weaker than that in CTRL (Figure 4a), especially SN3, in which the the environmental field in terms of their variation and magnitude. However, the intensity simulated by simulated intensity is the weakest. The analysis described above shows that nudging the large-scale SN1 and SN3 is weaker than that in CTRL (Figure4a), especially SN3, in which the simulated intensity environmental field, especially the thermal environmental field, weakens the thermal feedback of the is the weakest. The analysis described above shows that nudging the large-scale environmental field, convection process, leading to a decrease in the mean temperature in the core area during the whole especially the thermal environmental field, weakens the thermal feedback of the convection process, simulation period, with an associated decrease in the simulated intensity. However, it also modifies leading to a decrease in the mean temperature in the core area during the whole simulation period, the phenomenon whereby the simulated intensity is stronger than the observation for a short period with an associated decrease in the simulated intensity. However, it also modifies the phenomenon after 0000 UTC 19 October in CTRL; thus, it improves the simulation of the typhoon track to a certain whereby the simulated intensity is stronger than the observation for a short period after 0000 UTC extent. 19 October in CTRL; thus, it improves the simulation of the typhoon track to a certain extent.

(a)

Figure 5. Cont.

Atmosphere 2017, 8, 257 11 of 17 Atmosphere 2017, 8, 257 11 of 17

(b)

Figure 5. Temporal evolution of observed and simulated (a) minimum sea level pressure(units: hPa) Figure 5. Temporal evolution of observed and simulated (a) minimum sea level pressure(units: hPa) and (b) mean temperature anomaly of the whole troposphere (units: K); where black, purple, blue, and (b) mean temperature anomaly of the whole troposphere (units: K); where black, purple, blue, brown respectively correspond with observation (NCEP), CTRL, SN1, SN3. brown respectively correspond with observation (NCEP), CTRL, SN1, SN3.

4.2. Interaction with the Inner Structure of the Typhoon 4.2. Interaction with the Inner Structure of the Typhoon Many studies have shown that the inner structure of a typhoon is an important factor in the Many studies have shown that the inner structure of a typhoon is an important factor in the evolution of a typhoon track [29,30]. He [31] defined the movement speed of a typhoon center as→ V 0 evolutionand expressed of a typhoon the accelerated track [29 speed,30]. Heof typhoon [31] defined movement the movement generated speed by adiabatic of a typhoon heating center as follows: as V0 and expressed the accelerated speed of typhoon movement generated by adiabatic heating as follows: dV 0 1  → = QV (6) dV 1 (→ ) dt0 = Cp T QV (6) dt CphTi where represents the average volume, ( ) represents the average horizontal area, Cp is the where h i represents the average volume, () represents the average horizontal area, Cp is the specific specific heat at constant pressure, Q is the adiabatic heating rate in a unit mass of air per unit time→ heat at constant pressure, Q is the adiabatic heating rate in a unit mass of air per unit time and V and V is the steering speed of area-averaged flow field at a certain height, which can be considered is the steering speed of area-averaged flow field at a certain height, which can be considered to be to be the environmental mean speed of the area influenced at this→ height. QV is the adiabatic the environmental mean speed of the area influenced at this height. QV is the adiabatic heating rate heating rate multiplied by the local steering speed, with a value in direct proportion to the value of multiplied by the local steering speed, with a value in direct proportion to the value of the adiabatic the adiabatic heating rate and local steering speed. The→ direction of QV depends on the heating heating rate and local steering speed. The direction of QV depends on the heating property. When Q > 0 property. When Q > 0 (heating), its direction accords with the direction of the steering speed. Using (heating), its direction accords with the direction of the steering speed. Using the formula above, it is the formula above, it is possible to qualitatively analyze the influence of heating due to cumulus possible to qualitatively analyze the influence of heating due to cumulus convective condensation on convective condensation on typhoon movement. If the area of precipitation is centered on the left typhoon movement. If the area of precipitation is centered on the left side of the typhoon’s direction of side of the typhoon’s direction of movement, the direction of the accelerated speed generated by movement, the direction of the accelerated speed generated by adiabatic heating is the opposite of adiabatic heating is the opposite of the typhoon’s direction of movement; thus, the heating due to the typhoon’s direction of movement; thus, the heating due to cumulus convective condensation will cumulus convective condensation will make the typhoon slow down. In a similar way, if the area of make the typhoon slow down. In a similar way, if the area of precipitation is centered on the right precipitation is centered on the right side of the typhoon’s direction of movement, the typhoon will side of the typhoon’s direction of movement, the typhoon will speed up. If the area of precipitation is speed up. If the area of precipitation is located at the front of the typhoon, it will deviate to the left. If located at the front of the typhoon, it will deviate to the left. If the area of precipitation is located at the the area of precipitation is located at the back of the typhoon, it will deviate to the right. back of the typhoon, it will deviate to the right. Based on the theoretical analysis above, Figures 6 and 7 show the distribution of the typhoon’s Based on the theoretical analysis above, Figures6 and7 show the distribution of the typhoon’s inner severe convection and wind field at low (850 hPa) and middle (500 hPa) levels as simulated by inner severe convection and wind field at low (850 hPa) and middle (500 hPa) levels as simulated CTRL and sensitivity tests, at both the moment of making landfall (0600 UTC 18 October) and by CTRL and sensitivity tests, at both the moment of making landfall (0600 UTC 18 October) and deflection (0600 UTC 20 October), respectively. Based on the previous analysis of the environmental deflection (0600 UTC 20 October), respectively. Based on the previous analysis of the environmental mean wind, at the making-landfall moment (0600 UTC 18 October) the local steering flow at 850 and mean wind, at the making-landfall moment (0600 UTC 18 October) the local steering flow at 850 and 500 hPa is mainly an east wind (Figure 4a). The areas with large radar reflectivity at 850 hPa (Figure 500 hPa is mainly an east wind (Figure4a). The areas with large radar reflectivity at 850 hPa (Figure6d) 6d) in CTRL are mainly concentrated in the southern and northern parts of the typhoon inner core, in CTRL are mainly concentrated in the southern and northern parts of the typhoon inner core, which which are blocked by the high terrain of Luzon Island west of the typhoon. At 500 hPa (Figure 6a), areas of large radar reflectivity are apparent in the northern, western and southern parts of the

Atmosphere 2017, 8, 257 12 of 17 are blocked by the high terrain of Luzon Island west of the typhoon. At 500 hPa (Figure6a), areas of Atmosphere 2017, 8, 257 12 of 17 large radar reflectivity are apparent in the northern, western and southern parts of the typhoon inner core,typhoon which inner indicates core, that which the indicates convective that process the convec on thetive left process and right on sidesthe left of and the typhoon’sright sides directionof the of movementtyphoon’s direction is relatively of movement homogeneous is relatively but the ho convectivemogeneous process but the at convecti the frontve of process the typhoon at the isfront more severeof the than typhoon at the is back. more Thus,severe heatingthan at the due back. to cumulus Thus, heating convective due to condensationcumulus convective at this condensation point has little impactat this on point the speedhas little of impact the typhoon on the butspeed it makes of the typhoon the typhoon but it deviate makes the to thetyphoon left, causing deviate theto the typhoon left, trackcausing to deviate the typhoon to the south.track to In deviate SN1, theto the areas south. of largeIn SN1, radar the reflectivityareas of large at radar 850 hPa reflectivity (Figure 6ate) 850 and 500hPa hPa (Figure (Figure 6e)6b) and are 500 centered hPa (Figure in the 6b) eastern are centered part of thein the typhoon eastern innerpart of core. the Thus,typhoon the inner convective core. processThus, atthe the convective back of theprocess typhoon at the is back relatively of the typhoon strong, makingis relatively the strong, local steering making flowthe local deviate steering to the rightflow and deviate the typhoon to the right track and deviate the typhoon to the north.track deviat In SN3,e to there the north. are areas In SN3, of largethere radarare areas reflectivity of large at 850radar hPa reflectivity (Figure6f) at in 850 the hPa northern (Figure and 6f) southernin the nort partshern and of the southern typhoon parts inner of the core, typhoon with ainner small core, area of largewith a radar small reflectivityarea of large in radar the northernreflectivity part in the at 500northern hPa (Figurepart at 5006c). hPa Generally, (Figure 6c). the Generally, distribution the of areasdistribution with large of radarareas with reflectivity large radar is relatively reflectivity uniform; is relatively thus, uniform; the impact thus, of the convective impact of processesconvective on theprocesses typhoon on track the istyphoon relatively track small. is relatively In addition, small. the In distributionaddition, the ofdistribution wind speed of wind is related speed to is the related to the distribution of severe convection. In CTRL (Figure 6a,b) the areas with a large wind distribution of severe convection. In CTRL (Figure6a,b) the areas with a large wind speed are located speed are located on the northern and western sides of the typhoon inner core, while the distribution on the northern and western sides of the typhoon inner core, while the distribution of areas with a of areas with a large wind speed are relatively uniform in SN1 (Figure 6b,e) and SN3 (Figure 6c,f). large wind speed are relatively uniform in SN1 (Figure6b,e) and SN3 (Figure6c,f). Because the wind Because the wind on the western side of the typhoon is mainly a strong north wind, it causes the on the western side of the typhoon is mainly a strong north wind, it causes the typhoon to deviate to typhoon to deviate to the south. Thus, the distribution of areas with a large wind speed contributes theto south. the simulated Thus, the track distribution deviating of to areas the south with in a largeCTRL. wind Therefore, speed under contributes the combined to the simulated effect of the track deviatingsteering toflow the and south the indistribution CTRL. Therefore, of severe underconvection the,combined as well as the effect impact of the of steeringstrong wind flow centers, and the distributionthe simulated of severe typhoon convection, location and as well track as are the similar impact to of the strong observation wind centers, in CTRL the during simulated the landfall typhoon locationperiod. and track are similar to the observation in CTRL during the landfall period.

Figure 6. Distribution of radar reflectivity (dashes, units: dBZ) and wind speed (solid lines, units: m s−1) Figure 6. Distribution of radar reﬂectivity (dashes, units: dBZ) and wind speed (solid lines, units: m s−1) by CTRL (a,d), SN1 (b,e), SN3 (c,f) at 500 hPa (a–c) and 850 hPa (d–f) at the making-landfall moment by CTRL (a,d), SN1 (b,e), SN3 (c,f) at 500 hPa (a–c) and 850 hPa (d–f) at the making-landfall moment (0600 UTC 18); red typhoon symbols represent the simulated typhoon centers while purple typhoon (0600 UTC 18); red typhoon symbols represent the simulated typhoon centers while purple typhoon symbols represent the observed typhoon centers. symbols represent the observed typhoon centers. At the moment of deflection (0600 UTC 20 October), the local steering flow at 850 and 500 hPa is mainly a southeaster (Figure 4a). In CTRL, the areas with large radar reflectivity at 850 hPa (Figure

Atmosphere 2017, 8, 257 13 of 17

Atmosphere 2017, 8, 257 13 of 17 At the moment of deflection (0600 UTC 20 October), the local steering flow at 850 and 500 hPa is mainly7d) and a 500 southeaster hPa (Figure (Figure 7a)4 a).are In centered CTRL, thein the areas sout withhern large part radar of the reflectivity typhoon atinner 850 hPacore, (Figure indicating7d) andthat500 the hPaconvective (Figure 7processa) are centered at the back in the of southernthe typhoon part is of relatively the typhoon strong, inner causing core, indicating it to deviate that to the the convectivenorth. In SN1, process the distribution at the back of of areas the typhoon with large is relatively radar reflectivity strong, causingat 850 hPa it to(Figure deviate 7e) to are the uniform north. Inand SN1, the the areas distribution at 500 hPa of (Figure areas with 7b) largeare centered radar reflectivity in the northwestern at 850 hPa (Figure and southeastern7e) are uniform parts and of the the areastyphoon. at 500 Generally, hPa (Figure the7 distributionb) are centered is relatively in the northwestern uniform; thus, and the southeastern impact of the parts convective of the typhoon. process Generally,on the typhoon the distribution track is relatively is relatively small. uniform;In SN3, th thus,ere are the small impact areas of thewith convective large radar process reflectivity on the on typhoonthe southeastern track is relativelyside at both small. 850 hPa In SN3, (Figure there 7f) are and small 500 hPa areas (Figure with large 7c), which radar reflectivityslows the typhoon on the southeasterndown slightly. side The at distribution both 850 hPa of (Figure wind 7speedf) and is 500 also hPa related (Figure to 7thec), whichdistribution slows of the severe typhoon convection down slightly.at this point. The distribution The areas with of wind a large speed wind is alsospeed related are located to the distributionon the southeastern of severe side convection of the typhoon at this point.inner Thecore areasin CTRL with (Figure a large 7a,b), wind speedwhile arethey located are located on the on southeastern the eastern sideside ofin theSN1 typhoon (Figure inner7b,e). core The indistribution CTRL (Figure is relatively7a,b), while uniform they are in locatedSN3 (Figure on the 7c,f). eastern The side wind in at SN1 the (Figure southern7b,e). side The of distribution the typhoon isis relativelymainly a westerly uniform wind, in SN3 which (Figure causes7c,f). the The typhoon wind at to the deviate southern to the side east. of the Thus, typhoon the distribution is mainly aof westerlyareas with wind, a large which wind causes speed the causes typhoon the simulated to deviate trac to thek to east. deviate Thus, to thethe distributioneast in CTRL. of In areas all, during with a largethe deflection wind speed period, causes the the distribution simulated track of severe to deviate convection to the east and in wind CTRL. speed In all, causes during the deflectionsimulated period,typhoon the to distribution deviate to the of severeeast. Thus, convection the typhoon and wind track speed simulated causes by the CTRL simulated deviates typhoon substantially to deviate to tothe the east east. compared Thus, the to typhoon the observed track simulatedtrack. by CTRL deviates substantially to the east compared to the observed track.

−1 FigureFigure 7.7. DistributionDistribution ofof radarradar reﬂectivityreflectivity(dashes, (dashes,units: units: dBZ)dBZ) andandwind wind speed speed (solid (solid lines, lines, units: units: m m s s−1)) byby CTRLCTRL (a,d), SN1 SN1 ( (bb,e,e),), SN3 SN3 (c (,cf,)f at) at 500 500 hPa hPa (a– (ca)– andc) and 850 850 hPa hPa (d–f ()d at–f the) at deflection the deﬂection moment moment (0600 (0600UTC UTC20); 20);red redtyphoon typhoon symbols symbols represent represent the the simu simulatedlated typhoon typhoon centers centers while while purplepurple typhoontyphoon symbolssymbols representrepresent the the observed observed typhoon typhoon centers. centers.

TheThe distributionsdistributions of of severe severe mesoscale mesoscale convective convective systems systems and and strong strong wind wind in the intyphoon the typhoon core areacore arearea controlled are controlled and inﬂuenced and influenced by the by large-scale the large-scal environmentale environmental ﬁeld to field a great to extent.a great Rogersextent. etRogers al. [32 et] conductedal. [32] conducted a high-resolution a high-resolution numerical numerical simulation simula oftion hurricane of hurricane Bonnie Bonnie (1998) (1998) and provedand proved that that the accumulatedthe accumulated rainfall rainfall was distributedwas distributed symmetrically symmetrically across across the track the when track thewhen vertical the vertical shear was shear strong was strong and across track. It is generally acknowledged that the maximum precipitation area is located on the left side of the wind shear vector in the eye area [33,34]. Environmental wind shear can affect the asymmetric flow in the eye area in a variety of ways. The vertical wind shear can generate vortex

Atmosphere 2017, 8, 257 14 of 17 tilt. During the initial state of vortex tilt, the associated balance response will produce an updraft in the downshear direction [35–37]. In addition, the vertical wind shear affects the development, movement and symmetrization process of convective cloud formation. In a quasi-balanced downshearAtmosphere 2017environment,, 8, 257 a direction of movement to the left of mesoscale severe convective14of bands 17 provides favorable conditions for the genesis and development of convective cells [38]. andBased across on track.the studies It is generally referred acknowledged to above, Figure that 8 the shows maximum the environmental precipitation area mean is locatedwind profiles on the at bothleft the side moment of the windof making shear vectorlandfall in (0600 the eye UTC area 18 [33 October),34]. Environmental and deflection wind (0600 shear UTC can 20 affect October). the Theasymmetric vertical wind flow shear in the is eyemeasured area in by a variety the shea ofr ways. of the The environmental vertical wind mean shear wind can generate between vortex 200 and 850tilt. hPa. During At 0600 the UTC initial 18 state October, of vortex the wind tilt, the shea associatedr vectors balance in CTRL response (Figure will 8a) produce and SN3 an (Figure updraft 8c) pointin theto the downshear west, while direction in SN1 [35 (Figure–37]. In 8b), addition, the wind the shear vertical vector wind points shear affectsto the south. the development, According to the movementtheory that and the symmetrization maximum precipitation process of convective area is loca cloudted on formation. the left Inside a quasi-balanced of the wind shear downshear vector in the environment,eye area, the asouthern direction part of movement of the typhoon to the inne left ofr core mesoscale in CTRL severe and convective SN3, as well bands as the provides western partfavorable in SN1, conditionsshould be for the the areas genesis of severe and development convection, of which convective corresponds cells [38]. with the distribution of Based on the studies referred to above, Figure8 shows the environmental mean wind profiles at radar reflectivity at this point (Figure 6). At 0600 UTC 20 October, the wind shear vectors in CTRL both the moment of making landfall (0600 UTC 18 October) and deflection (0600 UTC 20 October). (Figure 8d) and SN1 (Figure 8e) point to the southwest and northwest, respectively, while the wind The vertical wind shear is measured by the shear of the environmental mean wind between 200 and shear vector in SN3 (Figure 8f) points to the northwest, while deviating westward. The areas with 850 hPa. At 0600 UTC 18 October, the wind shear vectors in CTRL (Figure8a) and SN3 (Figure8c) largepoint radar to thereflectivity west, while are in located SN1 (Figure in the8b), southern the wind part shear of vectorthe typhoon points toinner the south.core in According CTRL. Into SN1, the thedistribution theory that of the areas maximum with precipitationlarge radar areareflectivity is located is on relative the leftly side uniform, of the wind with shear areas vector of inlarge reflectivitythe eye area,in the the southwestern southern part ofpart the of typhoon the typhoon inner core inner in CTRLcore in and SN3 SN3, (Figure as well 7). as Generally, the western the distributionpart in SN1, of radar should reflectivity be the areas corresponds of severe convection, to the vertical which wind corresponds shear. Therefore, with the distribution it is concluded of thatradar the large-scale reflectivity atenvironmental this point (Figure adjustment6). At 0600 modi UTCfies 20 October,the environmental the wind shear vertical vectors wind in CTRL shear to change(Figure the8 d)location and SN1 and (Figure symmetry8e) point of to the the inner southwest severe and convection, northwest, thus respectively, affecting while the thedeflection wind of typhoonshear vectortrack. in SN3 (Figure8f) points to the northwest, while deviating westward. The areas with largeIn conclusion, radar reflectivity the large-scale are located inenvironmental the southern partfield of interacts the typhoon with inner the coreinner in CTRL.structure In SN1,of the typhoon,the distribution influencing of areas the withdistribution large radar of reflectivity severe convection is relatively and uniform, wind with speed areas in of the large core reflectivity area and affectingin the southwesternthe typhoon parttrack. of theLarge-scale typhoon inner enviro corenmental in SN3 (Figureadjustments7). Generally, change the the distribution environmental of verticalradar wind reflectivity shear, corresponds causing the to thelocation vertical and wind symm shear.etry Therefore, of severe it is convection concluded that in the large-scalecore area to change,environmental thus influencing adjustment the modifiestyphoon the track. environmental vertical wind shear to change the location and symmetry of the inner severe convection, thus affecting the deflection of typhoon track.

Figure 8. Environmental mean wind proﬁle of CTRL (a,b), SN1 (b,e), SN3 (c,f) at 0600 UTC 18 (a–c) Figure 8. Environmental mean wind profile of CTRL (a,b), SN1 (b,e), SN3 (c,f) at 0600 UTC 18 (a–c) and 0600 UTC 20 (d–f). The stars in the ﬁgure represent the coordinate system’s origin. and 0600 UTC 20 (d–f). The stars in the figure represent the coordinate system’s origin.

In conclusion, the large-scale environmental ﬁeld interacts with the inner structure of the typhoon,

inﬂuencing the distribution of severe convection and wind speed in the core area and affecting the typhoon track. Large-scale environmental adjustments change the environmental vertical wind shear,

Atmosphere 2017, 8, 257 15 of 17 causing the location and symmetry of severe convection in the core area to change, thus inﬂuencing the typhoon track.

5. Conclusions and Discussion In this study, an SN technique is applied to improve the simulation of typhoon Megi (2010). Sensitivity tests are conducted to investigate the effect of different large-scale environmental factors on the typhoon’s movement and to enable a detailed discussion of the response of its movement to the main factors. It is found that the adoption of the SN technique to nudge different variables effectively decreases the mean track error during the whole period and the effect of dynamical factors is more significant than the effect of thermal factors. Comparing the mean track error during different periods of the typhoon’s evolution, it is found that the adoption of the SN technique improves the simulated track when the typhoon is moving over the ocean but increases the simulation error when the typhoon passes over high terrain. A further diagnostic analysis of the results of sensitivity tests indicate that the nudging of large-scale environmental flow could directly adjust the local steering flow and influence the typhoon track. During the original integration period and the deflection period, this direct large-scale wind flow adjustment effectively modifies the local steering flow of the whole and lower troposphere; thus, achieving the goal of improving the simulation of the typhoon track. During the landfall period, SN1 weakens the low-level wind field adjustment generated by high terrain and the typhoon system itself in CTRL, increasing the error of the simulated track in SN1. On the other hand, large-scale environmental adjustment changes the environmental vertical wind shear, causing the location and symmetry of severe convections in the core area to change and therefore the typhoon track changes as well. After adjusting the large-scale environmental thermal factors, the environmental wind field responds and the simulated intensity of the typhoon is relatively weak. This influences the movement of the typhoon to a certain extent but the impact of environmental thermal factors is not significant compared to the impact of environmental dynamical factors. The SN technique improves the simulated typhoon track by nudging background information in the simulation process but it weakens the simulation of relatively small-scale physical processes, which is likely due to the limited experimental design by spuriously amplifying the role of large-scale circulation at the lower atmosphere levels. Therefore, future studies should construct and optimize the initial vortex of similar typhoons and then analyze the effect of the inner processes on the typhoon track under the impact of external forcing.

Acknowledgments: This research was primarily supported by National Natural Science Foundation of China (41275002, 40775055). Author Contributions: Xingliang Guo performed the experiments and wrote this paper. Wei Zhong conceived the idea and designed the structure of this paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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