Impact of cyclone bogusing and regional assimilation on tropical cyclone track and intensity predictions

bl v/;;u dk mÌs’; vYi vof/k iwokZuqeku esa pØokr ds iFk vkSj mldh rhozrk dk iwokZuqeku yxkus ds fy, MCY;w-vkj-,Q- lehdj.k vkSj iwokZuqeku iz.kkyh esa m".kdfVca/kh; dkYifud pØokr ds vk/kkj ij mlds izHkko dk fu/kkZj.k djuk gSA bl izHkko dks pØokr ds izHkko dh =qfV] dsUnzh; nkc vkSj vf/kdre lrr iou xfr ds :i esa crk;k x;k gSA ;g v/;;u o"kZ 2010 esa cus rhu pØokrksa uker% ‘ySyk’ ¼caxky dh [kkM+h½] ‘fxjh’ ¼caxky dh [kkM+h½ vkSj ‘QsV’ ¼vjc lkxj½ ij vk/kkfjr gSA MCY;w- vkj- ,Q- ekWMy izpkyukRed ,u-lh-,e- vkj-MCY;w-,Q- Vh- 382 ,y 64 ds fo’ys"k.k vkSj iwokZuqekuksa dk mi;ksx djrk gS vkSj bl ekWMy dks pØokr ds iFk vkSj bldh rhozrk dk iwokZuqeku yxkus ds fy, 72 ?kaVs rd lekdfyr fd;k x;k gSA bl ijh{k.k ds pkj lSVksa dh tk¡p dh xbZ ¼i½ fu;a=.k ijh{k.k ¼lh-,u-Vh-,y-½ ftlesa uk rks lehdj.k vkSj uk gh dkYifud pØokr dks vk/kkj ekuk x;k gSA bl ekWMy dk vkjaHk varoZsf’kr HkweaMyh; ekWMy fo’ys"k.k dk mi;ksx djrs gq, fd;k x;kA ¼ii½ lehdj.k ijh{k.k ¼oh-,-vkj-½ esa MCY;w- vkj- ,Q- oh- ,- vkj- vk¡dM+k lehdj.k iz.kkyh ¼fcuk dkYifud vk/kkj ij ekuk x;k pØokr½ dk mi;ksx djrs gq, ekWMy dh vkjafHkd fLFkfr;k¡ rS;kj dh xbaZA ¼iii½ pØokr ds ijh{k.k ¼ch-vks-th-½ lehdj.k ds fcuk dsoy dkYifud pØokr dks ekurs gq, dkYifud vk/kkj ij pØokr ds iz;ksx fd, x, gSaA bl ekeys esa dkYifud vk?kkj ij pØokr dk mi;ksx djrs gq, ekWMy ds izFke vuqeku dks la’kksf/kr fd;k x;k vkSj bldk vkjafHkd fLFkfr;ksa ds :i esa mi;ksx fd;k x;k gSA ¼iv½ pkSFks ijh{k.k esa dkYifud vk/kkj ij pØokr ds ckn MCY;-w vkj- ,Q- vk¡dM+k lehdj.k ¼ch- vks- th- oh- ,- vkj-½ nksuksa dk mi;ksx djrs gq, ekWMy dh vkjafHkd fLFkfr;k¡ rS;kj dh xbZA buls izkIr gq, ijh.kkeksa ls vkjafHkd fLFkfr;ksa esa dkYifud pØokr ds mYys[kuh; izHkko dk irk pyk gSA ;s rhuksa gh pØokr dkYifud ¼ch-vks-th- vkSj oh-,-vkj-½ iz;ksxksa dh vkjafHkd fLFkfr;ksa ¼0000 ;w- Vh- lh-½ esa ik, x, tk ldrs gSa tks vU;Fkk dkYifud vk/kkj ij rS;kj fd, x, pØokrksa ds vHkko esa ¼oh- ,-vkj- vkSj lh- ,u- Vh- ,y-½ iz;ksx esa ugha gksrh gSA ch- vks- th- oh- ,- vkj- ijh{k.k ds iFk =qfV;ksa esa mYys[kuh; deh ns[kh xbZ gSA oh- ,- vkj- dh rqyuk esa ch- vks- th- oh- ,- vkj- esa iFk =qfV esa vf/kdre deh Øe’k% ‘ySyk’ esa 76-8 izfr’kr] ‘fxjh’ esa 87-3 izfr’kr vkSj ‘QsV’ esa 51-5 izfr’kr jghA ‘ySyk’ vkSj ‘fxjh’ ds fy, oh-,-vkj- dh rqyuk esa ch-vks-th-oh-,-vkj- esa fy, x, izs{k.k vf/kdre lrr@Øfed iou xfr vkSj vf/kdre dsUnzh; nkc ds fudV gSaA The aim of this study is to assess the impact of tropical cyclone bogusing in WRF assimilation and forecast system for cyclone track and intensity prediction in short range forecast. The impact is demonstrated in terms of track error, central pressure, and maximum sustained wind speed. The study is based on the three cyclones; namely 'LAILA' (Bay of Bengal), 'GIRI' (Bay of Bengal) and 'PHET' (Arabian Sea), formed in the year 2010. The WRF model makes use of the operational NCMRWF T382L64 analysis and forecasts and the model is integrated upto 72 hrs for producing the cyclone track and intensity forecast. Four sets of experiments were performed: (i) The control experiment (CNTL) in which neither assimilation nor cyclone bogusing is done. The model is initialized using interpolated global model analysis. (ii) In assimilation experiment (VAR), model initial condition is prepared using WRF VAR data assimilation system (without cyclone bogusing). (iii) The cyclone bogusing experiment (BOG) featuring cyclone bogusing alone without assimilation. In this case the model first guess is modified using cyclone bogusing and used as the initial condition. (iv) In the forth experiment, the initial condition of the model is prepared with both cyclone bogusing followed with WRF data assimilation (BOGVAR). Results indicate remarkable impact of cyclone bogusing on the initial condition. All three cyclones can be located in the initial conditions (0000 UTC) of bogus (BOG and BOGVAR) experiments which were otherwise absent in no-bogus (VAR and CNTL) experiments. Significant reductions in track errors occurred in BOGVAR experiment. The maximum reduction in track error in BOGVAR compare to VAR is 76.8 % in 'LAILA', 87.3 % in 'GIRI' and 51.5 % in 'PHET' respectively. Maximum sustained wind speed and minimum central pressure are close to observations in BOGVAR compared to VAR for 'LAILA' and 'GIRI'.

Prediction of tropical cyclones by numerical models A review

ABSTRACT. This paper contains a review of some past and recent developments in cyclone track prediction problem by dynamical models. The early attempts aimed at predicting tropical cyclone motion by using simple barotropic models based on vertically integrated vorticity tendency equation. Barotropic models are still used operationally in some centres due to their simplicity. However, current emphasis is on advanced primitive equation models incorporating physical processes, like cumulus convection, which are necessary to account for a major component of the cyclone movement. An important aspect of cyclone prediction by dynamical models is prescription of a correctly analysed synthetic vortex in the initial fields for running a forecast model. Several approaches developed by various groups for generating synthetic vortex are discussed. Examples of some cases of track prediction by limited area model in IMD and by global models are illustrated.

Massive Damage to Coastal Region of Bangladesh by the Cyclone Storm YASS

Background: Tropical cyclones have significant destructive features like strong winds, heavy rainfall, and storms. It happens frequently in Bangladesh because of its geographical position. The southern parts of Bangladesh suffer most, especially the south-western region. Cyclone YASS hit the same parts of the country as cyclone Amphan did in 2020. These areas are still reeling from the effects of the prior tragedies. Methods: Secondary data has used to full fill the objective of the study investigating the damages of cyclone YASS in Bangladesh. Results: Wind and storm surge of the cyclone affected the south-western of Bangladesh. In Patuakhali and Jhalokathi districts, people were mostly affected and houses were mostly damaged in Patuakhali district. Paddy fields were mostly damaged and fish farms in Satkhira district were mostly damaged due their proximity to the cyclone track. Some places have been affected due to the storm surge. Conclusion: Due to the lack of suitable embankments in the coastal region, these areas are flooded by the storm surge. Authorities and government has to take necessary steps to overcome the losses.

Cyclone track forecast by combining persistence, climatology and synoptic method

lkj & Å".kdfVca/kh; pØokr fouk’kdkjh izkÑfrd vkink gksrs gSaA buls tku eky dh cM+h gkfu gksrh gSA pØokr ds /kjkry ls Vdjkus ds ckn eq[; fouk’k mldh izpaM iouksa rFkk rwQkuh ty rjaxksa ls gksrk gSA pØokr ds /kjkry ls Vdjkus ds lgh LFkku dk iwokZuqeku djuk iwokZuqekudrkZvksa rFkk ,tsfUl;ksa] tks lqj{kk ds mik;ksa vFkok iquokZl dk;ksZa esa yxs gSa] ds fy, vR;ar egRoiw.kZ gksrk gSA bl ’kks/k Ik= esa pØokr ds /kjkry ls Vdjkus ds LFkku rFkk le; dk iwokZuqeku djus dk iz;kl fd;k x;k gSA O;fDrxr daI;wVj ij vk/kkfjr ekxZ iwokZuqeku ekWMy Hkkjr ekSle foKku foHkkx ds fofHkUu iwokZuqeku dk;kZy;ksa esas mi;ksx esa gSA izpfyr ekWMy ds fy, nzks.kh ds pØokr ekxZ dh tyok;q rFkk pØokrksa ds iwoZ dh fLFkfr dh tkudkjh dh vko’;drk gksrh gSA lkekU;r;% pØokr ds /kjkry ls Vdjkus ds 24 ls 36 ?kaVs iwoZ rV ds fdukjs dk ok;qnkc de gks tkrk gSA bl v/;;u esa ekxZ iwokZuqeku ds fy, bl izkpy dk leku egRo ds vU; nks izkpyksa ds la;kstu ds lkFk vFkkZr~ 1@3 ¼LFkkf;Ro + tyok;q + nkc ifjorZu½ mi;ksx fd;k x;k gSA blds ifj.kke dsoy tyok;q ,oa LFkkf;Ro ¼DykbesV ,.M ijflLVsaV½ ds mi;ksx ls izkIr fd, x, ifj.kkeksa dh rqyuk esa T;knk lgh gSaA ;fn pØokr ds /kjkry ls Vdjkus ds 12 ls 24 ?kaVs ds vanj dh mldh izfØ;k ij fopkj fd;k tk; rks 24 ?kaVs ds vanj dk nkc ifjorZu] tyok;q ,oa LFkkf;Ro dh rqyuk esa vf/kd egRoiw.kZ gks tkrk gS rFkk /kjkry ls Vdjkus ds 12 ?kaVs iwoZ dk ?kaVkokj nkc ifjorZu pØokr ds /kjkry ls Vdjkus ds lgh LFkku dk irk yxkus esa enn djrk gSA Tropical cyclones are deadly natural disasters. They came large loss of lives and properties. After the landfall, the main damages from cyclones are due to strong winds and storm surges. The forecast of landfall point is most important to forecasters as well as the agencies who are engaged to take safety measures or rehabilitation works. In this paper an attempt has been made to forecast point and time of landfall. Personnel computer based, track forecast models are already in use, in India Meteorological Department’s (IMD) different forecasting offices. The existing model requires cyclone track climatology of the basin and past positions of cyclones. Generally pressure falls along the coast, 24 to 36 hours in advance of cyclone’s landfall. This parameter, in combination with other two, with equal weightage i.e., 1/3 (Persistence + Climatology + Pressure change) have been used for track forecasting in this study. Results are comparatively superior to the results obtained only by using climatology and persistence. When the system is within 12 to 24 hour prior to landfall, the 24 hour pressure change becomes more important than Climatology and Persistence and 12 hour prior landfall the hourly pressure change helps in pinpointing the landfall point.

Numerical prediction of the Orissa super cyclone (1999) : Sensitivity to the parameterisation of convection, boundary layer and explicit moisture processes

& ih- ,l- ;w- @ ,u- lh- ,- vkj- ,e- ,e- 5 dk mi;ksx djds mM+hlk esa 1999 esa vk, egkpØokr dh xfrfof/k;ksa vkSj mldh rhozrk ds la[;kRed iwokZuqeku dk bl 'kks/k&i= esa v/;;u fd;k x;k gSA laogu] xzgh; ifjlhek Lrj vkSj fuf’pr ueh Ldheksa dh izkpyhdj.k ;kstukvksa dh Hkwfedk dk v/;;u djus ds fy, laosnu’khyrk iz;ksx fd, x, gSaA caxky dh [kkM+h esa 90] 30 vkSj 10 fd-eh- {kSfrt varjkyksa ds rhu ikjLifjd iz{ks=ksa ¼Mksesu½ dk irk yxkus ds fy, bl ekWMy dh ifjdYiuk dh xbZ gSA ,d va’k ds varjky ij miyC/k gq, ,u- lh- bZ- ih- ,Q- ,u- ,y- vk¡dM+ksa dk mi;ksx djds izkjafHkd {ks=ksa vkSj fHkUu le; ds ifjlhek ifjorhZ rFkk 12 ?kaVs ds varjky ij leqnz lrg rkieku miyC/k djk, x, gSaA laogu] xzgh; ifjlhek Lrj vkSj fuf’pr ueh izfØ;kvksa ds laca/k esa pØokr ds ekxZ dk iwokZuqeku vkSj mldh rhozrk dh laosnu’khyrk dk v/;;u djus ds fy, rhu iz;ksx fd, x, gSaA blls izkIr gq, ifj.kkeksa ls pØokr ds ekxZ ds iwokZuqeku esa laoguh; izfØ;kvksa dh egRoiw.kZ Hkwfedk dk irk pyk gS rFkk dSu&fÝ’k 2 Ldhe ls pØokr ds ekxZ dk lcls lVhd <ax ls irk yxk;k tk ldk gSA blds vykok ;g irk pyrk gS fd xzgh; ifjlhek Lrj izfØ;k,¡ esyj&;eknk Ldhe ds lg;ksx ls lcls izpaMre pØokr dh rhozrk dks Kkr dj ldrh gSaA fuf’pr ueh izfØ;k,¡ pØokr dh xfr dks fu;af=r djrh gSa tks Hkhrjh iz{ks= ¼Mksesu½ ds 10 fd-eh- ds lw{e foHksnu ds QyLo:Ik laHko gks ldrk gSA dSu&fÝz’k 2 vkSj esyj&;eknk dh la;qDr pj.kc) ;kstuk ls pØokr ds ekxZ vkSj mldh rhozrk ds laca/kksa dks csgrj <ax ls izfr:fir fd;k x;k gSA fdlh ,dek= iz;ksx dh rqyuk esa lHkh feystqys iz;ksxksa ls pØokr ds ekxZ vkSj mldh rhozrk dk csgrj vkdyu fd;k tk ldk gSA izfr:fir pØokr esa ,diw.kZ fodflr pØokr ds] m".k ØksM] dsanz vkSj dsanz&fHkfRr tSls lHkh y{k.k ik, x, gSaA ekWMy ls izfr:fir o"kkZ forj.k vkSj rhozrk izs{k.kksa ds vuq:Ik ikbZ xbZ gSA Numerical prediction of the movement and intensification of the Orissa Super Cyclone (1999) is studied using PSU/NCAR MM5. Sensitivity experiments were made to study the role of the parameterisation schemes of convection, planetary boundary layer and explicit moisture schemes. The model is designed to have three interactive domains with 90, 30 and 10 km horizontal resolutions covering the Bay of Bengal region. The initial fields and time varying boundary variables and sea surface temperatures at 12 hour interval are provided from NCEP FNL data available at 1° resolution. Three groups of experiments were performed to study the sensitivity of the cyclone track prediction and intensification to the schemes of convection, planetary boundary layer and explicit moisture processes. The results indicate that convective processes play an important role in the cyclone track prediction and the scheme of Kain-Fritsch 2 produces the best track and the planetary boundary layer processes control the intensification with the scheme of Mellor-Yamada producing the strongest cyclone. The explicit moisture processes modulate the movement of the cyclone, which may be due to the fine resolution of the 10 km for the innermost domain. The mixed-phase scheme in combination with Kain-Fritsch 2 and Mellor-Yamada produce the best simulation in terms of the track as well as intensification. The ensemble mean of all the conducted experiments estimate the track positions and intensification better than any individual experiment. The simulated cyclone shows all the characteristics of a mature cyclone, with warm core, formation of the eye and eye wall. The model simulated rainfall distribution and intensity have good agreement with the observations.

Tropical cyclone track prediction by a high resolution limited area model using synthetic observations

ABSTRACT. Results of tropical cyclone track prediction experiments in die Indian seas by a high resolution limited area numerical weather prediction model (1° × 1° lat./long. grid) are presented. As the tropical cyclones form in data sparse regions of tropical oceans, and are, therefore, not well analysed in die initial fields, a scheme has been developed for generation of synthetic observations -based on die empirical structure of tropical cyclones, and their assimilation into the objective analysis, for preparing initial fields for running a forecast model. Experiments on track prediction have beat : conducted for die cyclones forming in the Bay of Bengal and Arabian Sea during the period 1990-95. Forecast errors of the model for 24 hr and 48 hr forecasts have been computed. A sensitivity experiment has been carried out to demonstrate the importance of initial humidity field on forecast model performance. The experiment brings out crucial important of the initial humidity field prescription in accurate track prediction by die forecast model.

A Novel Deep Learning Model by BiGRU with Attention Mechanism for Tropical Cyclone Track Prediction in Northwest Pacific

Tropical cyclones are amongst the most powerful and destructive meteorological systems on earth. In this paper, we propose a novel deep learning model for tropical cyclone track prediction method. Specifically, the track task is regarded as a time series predicting challenge, and then a deep learning framework by Bi-directional Gate Recurrent Unit network (BiGRU) with attention mechanism is developed for track prediction. This proposed model can excavate the effective information of the historical track in a deeper and more accurate way. Data exepriments are conducted on tropical cyclone best track data provided by the Joint Typhoon Warning Center (JTWC) from 1988 to 2017 in the Northwest Pacific. As results, our model performs well in tracks of 6h, 12h, 24h, 48h and 72h in the future. The prediction results show that our proposed combined model are superior to state-of-the-art deep learning models, include Recurrent Neural Network (RNN), Long Short-Term Memory neural network (LSTM), Gate Recurrent Unit network (GRU) and BiGRU without the use of attention mechanism. Compared with China Meteorological Administration (CMA), Japan Meteorological Agency (JMA) and Joint Typhoon Warning Center (JTWC), our method has obvious advantage in the mid- to long-term track forecasting, especially in the next 72 hours.

WRF-model sensitivity test and assimilation studies of Cempaka tropical cyclone

The WRF model was used to forecast the most intensive stage of Cempaka Tropical Cyclone (TC) on 27 - 29 November 2017. This study evaluates the combination of cumulus and microphysics parameterization and the efficiency of assimilation method to predict pressure values at the center of the cyclone, maximum wind speed, and cyclone track. This study tested 18 combinations of cumulus and microphysics parameterization schemes to obtain the best combination of both parameterization schemes which later on called as control model (CTL). Afterward, assimilation schemes using 3DVAR cycles of 1, 3, 6 hours, and 4DVAR, namely RUC01, RUC03, RUC06, and 4DV, were evaluated for two domains with grid size of each 30 and 10 km. GFS data of 0.25-degree and the Yogyakarta Doppler Radar data were used as the initial data and assimilation data input, respectively. The result of the parameterization test shows that there is no combination of parameterization schemes that constantly outperform all variables. However, the combination of Kain-Fritsch and Thompson can produce the best prediction of tropical cyclone track compared to other combinations. While, the RUC03 assimilation scheme was noted as the most efficient method based on the accuracy of track prediction and duration of model time integration.