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'.

Impact of Highest Maximum Sustained Wind Speed and Its Duration on Storm Surges and Hydrodynamics Along Krishna-Godavari Coast

The storm surge and hydrodynamics along the Krishna-Godavari (K-G) basin are examined based on numerical experiments designed from assessing the landfalling cyclones in Bay of Bengal (BoB) over the past 38 years with respect to its highest maximum sustained wind speed and its duration. The model is validated with the observed water levels at the tide gauge stations at Visakhapatnam during Helen (2013) and Hudhud (2014). Effect of gradual and rapid intensification of cyclones on the peak water levels and depth average currents are examined and the vulnerable locations are identified. The duration of intensification of a rapidly intensifying cyclone over the continental shelf contributed to about 10-18 % increase in the peak water levels, whereas for the gradually intensifying cyclone the effect is trivial. The inclusion of the wave-setup increased the peak water levels up to 39% compared to those without wave-setup. In the deep water region, only rapidly intensifying cyclones affected the peak MWEs. Intensification over the continental slope region significantly increases the currents along the shelf region and coast. The effect on peak maximum depth averaged current extends up to 400 km from the landfall location. Thus, it is necessary to consider the effect of various combinations of the highest cyclone intensity and duration of intensification for identifying the worst scenarios for impact assessment of coastal processes and sediment transport. The study is quite useful in improving the storm surge prediction, in preparedness, risk evaluation, and vulnerability assessment of the coastal regions in the present changing climate.

Northeast Pacific annual accumulated cyclonic energy rank-profile

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.

Tropical Cyclone Characteristics Associated with Extreme Precipitation in the Northern Philippines

<p>The Philippines is exposed to Tropical Cyclones (TCs) throughout the year due to its location in the western North Pacific. While these TCs provide much-needed precipitation for the country’s hydrological cycle, extreme precipitation from TCs may also cause damaging hazards such as floods and landslides. This study examines the relationship between TC extreme precipitation and TC characteristics, including movement speed, intensity, and season, for westward-moving TCs crossing Luzon, northern Philippines. We measure extreme precipitation by the Weighted Precipitation Exceedance (WPE), calculated against a 95<sup>th</sup> percentile threshold, which considers both the magnitude and spatial extent of TC-related extreme precipitation.</p><p>WPE has a significant, moderate positive relationship with TC intensity and a significant, weak negative relationship with TC movement speed. When TCs are classified by pre-landfall intensity, Typhoons (1-minute maximum sustained wind speed > 64 knots) tend to yield higher WPE than non-Typhoons (< 64 knots). On the other hand, when TCs are classified by pre-landfall speed, Slow TCs (movement speed < 11.38 knots) tend to yield higher WPE than Fast TCs (movement speed > 11.38 knots). However, while distributions of WPE are similar between the Southwest Monsoon (June-September) and Northeast Monsoon (October-December) seasons, the relationship between pre-landfall TC intensity and WPE is more pronounced during June-September. These results suggest that it is important to consider the pre-landfall cyclone movement speed, intensity, and season to anticipate extreme precipitation of incoming TCs. A decision table considering these factors is devised to aid in TC extreme precipitation forecasting.</p>

Impacts of Topsoil and Surface Water Salinity on Agriculture: A Study at Paikgachha, Khulna

Studying the structure, intensity and track of tropical cyclone is very important in effective tropical cyclone warning. In this study, an attempt has been made to simulate the Super Cyclone Amphan to reproduce the structure, intensity and track of the storm that occurred over the Bay of Bengal and made landfall over the coastal zone of Sundarban between Western Bangladesh and Eastern West Bengal of India on 20 May 2020. The Weather Research and Forecasting (WRF) Model was run 120 hours from 0000 UTC of 16 May to 0000 UTC of 21 May 2021 with 9 km horizontal resolution to simulate the selected storm. The model simulated intensity and track of the storm were compared with that of best track data of India Meteorological Department (IMD). The results obtained from the WRF model indicated that the intensity of the selected cyclone in terms of Mean Sea Level Pressure (MSLP) and Maximum Sustained Wind speed (MSW) were 905 hPa and 243 kph whereas the observed MSLP and MSW were close to 920 hPa and 241 kph respectively. It was also indicated that the model predicted the track of the cyclone reasonably well and it was quite close to the best track data throughout its path till landfall with very small deviation and the cyclone made landfall at 7-8 hours before the actual landfall with 167.4 km position error. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 8(2), 2019, P 25-32

Estimating the True Maximum Sustained Wind Speed of a Tropical Cyclone from Spatially Averaged Observations

The maximum sustained wind speed Vm of a tropical cyclone (TC) observed by a sensor varies with its spatial resolution. If unaccounted for, the difference between the “true” and observed Vm results in an error in estimation of Vm. The magnitude of the error is found to depend on the radius of maximum wind speed Rm and Vm itself. Quantitative relationships are established between Vm estimation errors and the TC characteristics. A correction algorithm is constructed as a scale factor to estimate the true Vm from coarsely resolved wind speed measurements observed by satellites. Without the correction, estimates of Vm made directly from the observations have root-mean-square differences of 1.77, 3.41, and 6.11 m s−1 given observations with a spatial resolution of 25, 40, and 70 km, respectively. When the proposed scale factors are applied to the observations, the errors are reduced to 0.69, 1.23, and 2.12 m s−1. A demonstration of the application of the correction algorithm throughout the life cycle of Hurricane Sergio in 2018 is also presented. It illustrates the value of having the scale factor depend on Rm and Vm, as opposed to using a fixed value, independent of TC characteristics.