Artificial intelligence in forecasting central pressure drop and maximum sustained wind speed of cyclonic systems over Arabian Sea: skill comparison with conventional models

Author(s):  
Ishita Sarkar ◽  
Sutapa Chaudhuri ◽  
Jayanti Pal
MAUSAM ◽  
2022 ◽  
Vol 64 (1) ◽  
pp. 135-148
Author(s):  
MANJUSHA CHOURASIA ◽  
R.G. ASHRIT ◽  
JOHN.P. GEORGE

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'.


Author(s):  
Elio Roca-Flores ◽  
Gerardo G. Naumis

The ranking of events is a powerful way to study the complexity of rare catastrophic events as earthquakes and hurricanes. Hurricane activity can be quantified by the annual accumulated cyclone energy index (ACE), which contains the information of the maximum sustained wind speed, duration and frequency of the tropical cyclone season. Here, the ranking of the Northeast Pacific annual ACE is obtained and fitted using nonlinear regression with several two- and three-parameter ranking laws that fit the tail and head of the data, where lives the information of relevant events for human society. The logarithmic like function [Formula: see text] overperforms all other fits. A sliding window analysis of the parameters [Formula: see text] and [Formula: see text] of such a function shows that forcing and dissipation processes are anticorrelated.


2022 ◽  
pp. 0309524X2110500
Author(s):  
Gustavo Richmond-Navarro ◽  
Mariana Montenegro-Montero ◽  
Pedro Casanova-Treto ◽  
Franklin Hernández-Castro ◽  
Jorge Monge-Fallas

There are few reports in the literature regarding wind speed near the ground. This work presents a model for wind speed from 4 m above the ground, based on year-round measurements in two meteorological towers. Each tower is equipped with anemometers at five heights, as well as thermometers and pressure and relative humidity sensors. The data is processed using Eureqa artificial intelligence software, which determines the functional relationship between variables using an evolutionary search technique called symbolic regression. Using this technique, models are found for each month under study, in which height and temperature are the variables that most affect wind speed. The model that best predicts the measured wind speeds is then selected. A polynomial function directly proportional to height and temperature is identified as the one that provides the best predictions of wind speed on average, within the rough sub-layer. Finally, future work is identified on testing the model at other locations.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 83347-83358 ◽  
Author(s):  
Hai Tao ◽  
Sinan Q. Salih ◽  
Mandeep Kaur Saggi ◽  
Esmaeel Dodangeh ◽  
Cyril Voyant ◽  
...  

2014 ◽  
Vol 14 (5) ◽  
pp. 1371-1381 ◽  
Author(s):  
P. R. Shanas ◽  
V. Sanil Kumar

Abstract. Temporal variations in wind speed and significant wave height (SWH) at a location in the eastern Arabian Sea are studied using ERA-Interim reanalysis data from 1979 to 2012. A shallow water location is selected for the study since measured buoy data are available close to the location for comparison with the reanalysis data. The annual mean wind speed shows a statistically significant decreasing trend of 1.5 cm s−1 year−1, whereas a statistically insignificant increasing trend of 3.6 cm s−1 year−1 is observed for annual maximum wind speed due to the local events that altered the trend in annual maximum wind speed. Weakening of SWH during one of the peak monsoon months (August) is identified from the monthly analysis of SWH, which shows a higher upward trend in SWH during the southwest monsoon period, with an exception during August. The annual mean SWH shows a slight upward trend (0.012 cm year−1), whereas a larger upward trend (1.4 cm year−1) is observed for annual maximum SWH. Both identified trends are statistically insignificant. The influence of tropical cyclone activity is also studied and it is found that the maximum SWH and wind speed during 1996 are directly related to the cyclonic event.


2013 ◽  
Vol 8 (6) ◽  
pp. 1090-1095 ◽  
Author(s):  
Minoru Noda ◽  
◽  
Fumiaki Nagao

Three tornadoes almost simultaneously hit the northern Kanto region north of Tokyo, Japan, on May 6, 2012. One peeled away and scattered asphalt 4 m wide, 30mlong and 50mmthick from roads in Tochigi prefecture. According to the Japan Meteorological Agency, the F scale of this tornado was between F1 and F2. A few F1-F2 tornadoes occur in Japan each year, but the scale of road damage following an F1-F2 tornado has not been previously observed. To determine the wind speed behind this road damage, a new approach was adopted focusing on the speed of flying debris and the pressure drop. The resulting determined a wind speed of approximately 100 m/s.


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