Tropical cyclone Genesis Potential Parameter (GPP) and it’s application over the north Indian Sea

bl 'kks/k i= esa mRrjh fgUn egklkxj esa m".kdfVca/kh; pØokr ds cuus ds foHko izkpy ¼th- ih- ih-½ dk fo’ys"k.k fd;k x;k gSA dksVy }kjk fodflr ¼2009½ pØokr cuus ds foHko izkpy dk vkdyu pkj ifjofrZrkvksa ds vk/kkj ij fd;k x;k gS tks bl izdkj gS % 850 gSDVkikLdy ij Hkzfeyrk] e/; {kksHkeaMyh; lkisf{kd vknzZrk] e/; {kksHkeaMyh; vfLFkjrk vkSj ml LFkku ds lHkh fxzM IokbaVksa ij m/okZ/kj iou vi:i.kA bu fLFkfr;ksa esa fxzM IokbaV ij th-ih-ih- ij ;g fopkj fd;k x;k fd lHkh ifjorhZ Hkzfeyrk] e/; {kksHkeaMyh; lkisf{kd vknzZrk] e/; {kksHkeaMyh; fLFkjrk vkSj m/okZ/kj iou vi:i.k 'kwU; ls cM+k gS vkSj ;g ekuk x;k gS fd tc buesa ls dksbZ Hkh ifjorhZ 'kwU; ls de ;k cjkcj gks rks og 'kwU; gh ekuk tk,xkA ;wjksih; e/;kof/k ekSle iwokZuqeku dsUnz ¼b-lh-,e-MCY;w-,Q-½ fun’kZ vk¡dM+ksa dk mi;ksx djrs gq, bu ifjofrZrkvksa dk vkdyu fd;k x;k gSaA b- lh- ,e- MCY;w- ,Q- fun’kZ dh lwpukvksa ¼http://www.imd.gov.in/section/nhac/dynamic/analysis.htm ij miyC/k½ dk okLrfod le; dk mi;ksx djrs gq, lkr fnuksa rd ds fy, tsusfll izkpy ds iwokZuqeku Hkh rS;kj fd, x,A ml {ks= esa th-ih-ih- ds mPprj ekuksa ls ml LFkku ds tsfufll ds mPprj foHko dk irk pyk gSA ml LFkku ij th-ih-ih- ds eku 30 ds cjkcj vFkok vf/kd gksus dh fLFkfr esa pØokr mRifRr ds fy, mPp foHko {ks= ik;k x;k gSA izkpy ds fo’ys"k.k vkSj 2010 esa pØokrh fo{kksHkksa ds nkSjku budh izHkko’khyrk ls mRrjh fgUn egklkxj esa pØokr mRifÙk ds fy, iwokZuqeku lwpd flaxuy ¼4&5 fnu igys½ ds :i esa vkSj fodkl dh vkjafHkd voLFkkvksa esa fodflr vkSj xSj&fodflr iz.kkfy;ksa ds rzhohdj.k ds fy, foHko dk fu/kkZj.k gsrq budh mi;ksfxrk dh iqf"V gqbZ gSA An analysis of tropical cyclone genesis potential parameter (GPP) for the North Indian Sea is carried out. The genesis potential parameter developed by Kotal et al. (2009) is computed based on the product of four variables, namely: vorticity at 850 hPa, middle tropospheric relative humidity, middle tropospheric instability and the inverse of vertical wind shear at all grid points over the area. The GPP at a grid point is considered under the conditions that all the variables vorticity, middle tropospheric relative humidity, middle tropospheric instability and the vertical wind shear are greater than zero and it is taken as zero when any one of these variables is less or equal to zero. The variables are computed using the European Centre for Medium Range Weather Forecast (ECMWF) model data. Forecast of the genesis parameter up to seven days is also generated on real time using the ECMWF model output (available at http://www.imd.gov.in/section/nhac/dynamic/Analysis.htm). Higher value of the GPP over a region indicates higher potential of genesis over the region. Region with GPP value equal or greater than 30 is found to be high potential zone for cyclogenesis. The analysis of the parameter and its effectiveness during cyclonic disturbances in 2010 affirm its usefulness as a predictive signal (4-5 days in advance) for cyclogenesis over the North Indian Sea and for determining potential for intensification of developing and non-developing systems at the early stages of development.

Real time forecasting of the Bay of Bengal cyclonic storm “RASHMI” of October 2008 – A statistical-dynamical approach

A four-step statistical-dynamical approach is applied for real time forecasting of the Bay of Bengal cyclonic storm “RASHMI” of October 2008 which made landfall near Khepupara (Bangladesh) around 2200 UTC of 26 October 2008. The four-step approach consists of (a) Analysis of Genesis Potential Parameter (GPP), (b) Track prediction, (c) Intensity Prediction by Statistical Cyclone Intensity Prediction (SCIP) model and (d) Prediction of decaying intensity after the landfall. The results show that the analysis of Genesis Potential Parameter (GPP) at early stages of development strongly indicated that the cyclone “RASHMI” had enough potential to reach its cyclone stage. The 48 hours landfall forecast position error based on 0000 UTC on 25 October shows that the error varies from around 10 km to 95 km and landfall time error varies from 12 hours early to 23 hours delay by different numerical models (NWP). The consensus forecast (ensemble) based on these NWP models shows that landfall forecast position error is around 10 km and landfall time error is around 2 hours delay. The updated 24 hours forecast based on 0000 UTC of 26 October shows improvement in the forecast. The model predicted landfall position error varies from around 10 km to 55 km with landfall time 6 hours early to 3 hours delay. The Multiple Model Ensemble (MME) forecast shows that the landfall forecast position is close to observed landfall point and the landfall time is early by 2 hours. The JMA (Japan Meteorological Agency) and ensemble forecasts are found to be consistent both in terms of 24-hourly forecasts position, landfall point and landfall time. The 12–hourly intensity prediction up to 24 hours forecasts based on 0000 UTC on 26 October show that the model (SCIP) could pick up the intensification of the cyclone. The model forecasts till the landfall point show that there is an underestimation of intensity by 2 knots and 8 knots at 12 hour and 24 hour forecasts respectively. The 6-hourly decaying intensity forecast after the landfall shows an overestimation of 6 knots and 10 knots at 6-hour and 12-hour forecasts respectively. The approach provided useful guidance to the forecasters for real time forecasting of the cyclone.

Dynamical Stability and Geometrical Diagnostic of the Power Law K-Essence Dark Energy Model with Interaction

We investigate the cosmological evolution of the power law k-essence dark energy (DE) model with interaction in FRWL spacetime with the Lagrangian that contains a kinetic function F(X)=−X+X. Concretely, the cosmological evolution in this model are discussed by the autonomous dynamical system and its critical points, together with the corresponding cosmological quantities, such as Ωϕ, wϕ, cs2, and q, are calculated at each critical point. The evolutionary trajectories are drawn in order to show the dynamical process on the phases plan around the critical points. The result that we obtained indicates that there are four dynamical attractors, and all of them correspond to an accelerating expansion of universe for certain potential parameter and coupling parameter. Besides that, the geometrical diagnostic by the statefinder hierarchy S3(1) and S4(1) of this scalar field model are numerically obtained by the phase components, as an extended null diagnostic for the cosmological constant. This diagnostic shows that both the potential parameter λ and interaction parameter α play important roles in the evolution of the statefinder hierarchy.

Logistic Regression Under Sparse Data Conditions

The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias.