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'.

Observation impact study of an Arctic cyclone associated with a Tropopause Polar Vortex (TPV)-induced Rossby wave initiation event

A case study characterized by Arctic cyclogenesis following a tropopause polar vortex (TPV)-induced Rossby wave initiation event is used to better understand how well existing observations constrain analyses of processes influencing Arctic cyclone predictive skill. Complementary techniques of observation system experiments (OSE) and ensemble sensitivity analysis (ESA) are used to investigate the impacts of existing observation networks on predictions for this case. The ESA reveals that the large-scale Rossby wave structure correlated with both Arctic cyclone track and amplitude errors. The ensemble analyses of mid-level moisture in the warm conveyor belt region were correlated with forecast cyclone amplitude, but this feature was poorly sampled in existing observations. There is also a sensitivity of Arctic cyclone forecast amplitude error to low level temperature in the air mass of the cyclogenesis region at analysis time and a sensitivity of Arctic cyclone forecast track error to low level temperature in the region of an Arctic cold front and a coastal front at the analysis time. The OSEs for this case reveal that Arctic cyclone track error is more sensitive to denial of existing observations than amplitude error. While lower level (below 700 hPa) observations had greatest impact on the surface cyclone during the early stages, upper level (above 500 hPa) observations had the dominant impact during its later evolution. Denying temperature from just three well-placed sondes substantially increased track error by degrading analyses of the TPV amplitude and its interaction with the waveguide and developing Rossby wave packet. These results are encouraging for further Arctic cyclone forecast improvements through addition of even a small number of well-placed observations.

Sensitivity Study of Planetary Boundary Layer Parameterization Schemes for the Simulation of Tropical Cyclone ‘Fani’ Over the Bay of Bengal Using High Resolution Wrf-Arw Model

Comprehensive sensitivity analyses on physical parameterization schemes of WRF-ARW (V3.8.1) model have been carried out for the simulation of Tropical Cyclone (TC) Fani that formed in the Bay of Bengal (BoB) and crossed the Bangladesh and Odisha coast of India on 3rd May 2019. Global Forecasting System (GFS) data 1⁰ and 0.25⁰ from National Centre for Environment Prediction (NCEP) is used as initial and lateral boundary conditions. The six different Planetary Boundary Layer (PBL) schemes used in this research are YSU, BouLac, TEMF, Shin-Hong, GBM and MRF. The meteorological parameters, which have been studied to identify the effect of PBL during the propagation and movement of TC Fani are Estimated Central Pressure (ECP), Maximum Wind Speed (MWS) at 10m height, average relative humidity (%), temperature (⁰C) and potential temperature (0K) at 2m height, Modified Convective Available Potential Energy (MCAP), average PBL height and average high clouds (%). The area considered for these averages are 82-92 ⁰E and 7-22 ⁰N inside the model domain. The simulated ECP by TEMF scheme are 930, 932, 937, 929, 944 and 932 hPa for the Initial Conditions (ICs) at 0000 UTC of 27, 28, 29, 30 April, and 01 May and 02 May, respectively and observed ECP was 932 hPa. The intensity of pressure fall by the TEMF scheme is similar to that observed up to the time of crossing the land of TC Fani. The MWS simulated by the TEMF scheme is almost similar to that of the observed MWS at 10m height and all other schemes have simulated much lower MWS. The temperature at 2m height is positively correlated with the ECP and MWS at 10m height. The TEMF scheme has simulated maximum high clouds for all ICs and for all through the simulation time. The error was systematic for all PBL schemes for the ICs at 0000 UTC of 30 April at 0.25⁰ and 1⁰ GFS data but the track error was much less for 1⁰ GFS data than that of 0.25⁰ GFS data. The TEMF scheme has simulated the most deviated track and MRF scheme has simulated less deviated track for all through the simulation. The study has shown large variations of track and intensity among the different PBL schemes. The PBL schemes have a major impact on the track and intensity of TC Fani. The intensity simulated by the TEMF scheme is better but the track error is higher than that of other schemes. Journal of Engineering Science 11(2), 2020, 1-18

IMPACT OF THE CROSS-TRACK ERROR DISTRIBUTION LAW ON SAFE NAVIGATION IN NARROW WATERS

The paper indicates that navigation in narrow waters requires navigators to use means of passage safety assessment prior to choosing a route. It is pointed out that a relevant factor when assessing the safe passage probability is the cross-track error distribution law, whose impact is the subject of the research. The article analyses recent developments and publications that have begun investigating this subject, and highlights previously unsolved parts of the general problem. The results revealed two equivalent approaches, as well as a navigational safety parameter, which are used to determine the probability of safe navigation in narrow waters on the chosen route. The need to develop advanced predictive vessel motion models is noted, while many researchers study the design of an information system for vessel motion simulation with complex dynamic models and an intelligence system for vessel motion prediction that imitates the learning process of an autonomous control unit created with the use of the artificial neural network. Methods for identification of vessel manoeuvring models are shown. Based on the analysis of vessel hydrodynamics, a nonlinear model frame of vessel manoeuvring is established. The available publications suggest using compound laws of the first and second types for describing random errors in navigation measurements as an alternative to the normal distribution law. The article examines the dependence of the safe narrow waters passage probability on the cross-track error distribution law. The normal law and compound laws of the first and second types are considered as the cross-track error distribution laws. A formula for estimating the safe passage probability in the manoeuvring area is given, and expressions for the distribution function of the normal law and compound laws of both types are obtained. To assess the impact of the cross-track error distribution law for the same route, the safe passage probability for the normal distribution law, as well as compound laws of the first and second types, was calculated. For the same route, the probability of safe passage was calculated with the use of onedimensional and two-dimensional density models. It is shown that the average relative difference between the estimated safe passage probability for both models is 0.3%, which confirms the validity of using a one-dimensional cross-track error distribution density.

Maneuvering Ability-Based Weighted Potential Field Framework for Multi-USV Navigation, Guidance, and Control

Numerous types of unmanned surface vehicles (USVs) are currently available for different applications with a wide spectrum of maneuvering capabilities. We present a generalized multi-USV navigation, guidance, and control framework adaptable to specific USV maneuvering response capabilities for dynamic obstacle avoidance. The proposed method integrates offline optimal path planning with a safety distance constrained A* algorithm, and an online extended adaptively weighted (EAW) artificial potential field-based path following approach with dynamic collision avoidance, based on USV maneuvering response times. The framework adaptively weighs inter-USV interaction, waypoint following, and collision avoidance based on USV maneuvering capabilities. The EAW system allows USVs with fast maneuvering abilities to react late and slow USVs to react sooner to oncoming moving obstacles gradually, with a carefully designed series of repulsive potential with diminishing weighting along the predicted path of detected moving obstacles, such that a smooth path is followed by the USV group with reduced cross-track error and reduced maneuvering effort. We emphasize the importance of such requirements in constrained and busy maritime environments such as narrow channels in busy harbors. Simulation results validate the proposed EAW artificial potential field framework for different sized multi-USV teams showing reduced cross-track error and maneuvering effort compared to the unweighted or traditional approach, for both slow- and fast-maneuvering multi-USV teams.

Nonlinear guidance law algorithm applied to a small unmanned surface vehicle

The unmanned surface vehicles have been used most frequently in recent years in different applications, like environmental research. For this vehicles to accomplish their autonomous missions, a path-following algorithm is necessary to reduce the cross-track error in the presence of environmental disturbance. This article presents a control scheme based on the path-following nonlinear guidance law for a small unmanned surface vehicle called Krick Felix which follows a straight path. A dynamic model of 3 degrees of freedom for this vehicle is presented. The control scheme consists of a cascade control loop that is capable of guaranteeing zero cross-track error in the presence of environmental disturbance without adding an integral action. A nonlinear Lyapunov stability analysis is carried out for this control scheme taking in consideration the dynamics of both the inner loop and the external loop. The simulation was realized by implementing the 3-degree-of-freedom nonlinear model of the Krick Felix. The simulation also took account of the environmental factors, that is, marine currents. An experimental test is carried out with the Krick Felix where the control scheme present satisfactory results.

Introducing Along-Track Error Correlations for Altimetry Data in a Regional Ocean Prediction System

Because of the systematic error in the processing of altimetry data, sea level anomaly (SLA) observation errors are likely affected by nonnegligible spatial correlations. To account for these, we exploit the synergy of altimetry data with in situ profiles from gliders, piloted to follow the altimetry tracks during the Long-Term Glider Mission for Environmental Characterization 2017 (LOGMEC17) observational campaign in the Ligurian Sea. The assimilation of along-track unfiltered sea level anomalies in a regional ocean analysis and forecast system is consequently optimized by means of introducing spatial correlations for the SLA observation errors. In particular, collocated data of glider and altimetry are used to derive an along-track error covariance model for the sea level anomaly assimilation, assuming that most of the covariance behavior versus separation distance stems from altimetry. Spatial scales of the altimetry error are found to have a correlation radius of about 12 km for the dataset utilized in the Ligurian Sea, using a simple Gaussian shape for the error correlation, shorter than the correlation radius found through assimilation output diagnostics. A variational data assimilation system is modified to relax the usual assumption of uncorrelated altimetry observation errors, thus allowing for along-track error correlations. Its implementation provides promising results in the regional ocean prediction system, outperforming in most verification skill scores the use of uncorrelated observational errors without compromising the analysis scheme efficiency.

Dependence of Probabilistic Quantitative Precipitation Forecast Performance on Typhoon Characteristics and Forecast Track Error in Taiwan

This study investigates the probabilistic quantitative precipitation forecast (PQPF) performance of typhoons that affected Taiwan during 2011–16. In this period, a total of 19 typhoons with a land warning issued by the Central Weather Bureau (CWB) are analyzed. The PQPF is calculated using the ensemble precipitation forecast data from the Taiwan Cooperative Precipitation Ensemble Forecast Experiment (TAPEX), and the verification data, verification thresholds, and typhoon characteristics are obtained from the CWB. The overall PQPF performance of TAPEX has an acceptable reliability and discrimination ability, and the higher probability error is distributed at the mountainous area of Taiwan. The PQPF performance is significantly influenced by typhoon characteristics (e.g., typhoon tracks, sizes, and forward speeds). The PQPFs for westward-moving, large, or slow typhoons have higher reliability and discrimination ability, and lower-probability error than those for northward-moving, small, or fast typhoons, except for similar reliability between fast and slow typhoons. Because northward-moving or small typhoons have larger forecast track error, and their PQPF performance is sensitive to the accuracy of the forecast track, a higher probability error occurs than that for westward-moving or large typhoons. Furthermore, because there is no difference in track error between fast and slow typhoons, the larger track spread for slow typhoons increases the rainfall forecast spread and reduces the probability error. The orientation of Taiwan’s topography and the topographic effect also influence and increase the distribution and value of probability error for northward-moving, small, or fast typhoons. In summary, forecast track characteristics are influenced by typhoon characteristics and further affect the PQPF performance.