QuikSCAT scatterometer wind data impact on tropical cyclone

lkj & bl v/;;u esa eslksLdsy fun’kZ ¼,e- ,e- 5½ dk mi;ksx djrs gq, m".kdfVca/kh; pØokr fo’ys"k.kksa vkSj iwokZuqekuksa ij fDodLdsV LdsVªksehVj vk¡dM+ksa ds ldkjkRed izHkko dk mYys[k fd;k x;k gSA fDodLdsV ds vk¡dM+s fo’ks"k :i ls blfy, Hkh ewY;oku gSa D;kasfd os m".kdfVca/kh; pØokrksa ds eqf’dy ls izkIr gksus okys vk¡dM+ksa ds {ks=ksa esa gh ugha cfYd es?kkPNUu vkSj o"kkZ dh fLFkfr;ksa esa Hkh miyC/k jgrs gSaA bl v/;;u ds fy, mi;ksx fd;k x;k fun’kZ ,e- ,e- 5 ik¡poha ih<+h ds ,u- lh- ,- vkj- @ isu LVsV eslksLdsy fun’kZ ds uke ls tkuk tkrk gSA fDodLdsV LdsVªªksehVj  iou vk¡dM+ksa ds izHkko dks le>us vkSj mldh tk¡p djus ds fy, 1999 ls 2003 dh vof/k ds nkSjku dqN m".kdfVca/kh; pØokrksa ds fy, LdsVªªksehVj  vk¡dM+ksa dk lekos’ku lfgr vkSj fcuk lekos’ku ds izfr:i.k fd;k x;k gSA pØokrh fLFkfr gsrq ml le; fo|eku dqN iksrksa ij fy, x, vk¡dM+sa vkSj dqN rVh; vFkok }hiksa ds dsUnzksa ij izkIr fd, x, vk¡dM+sa gh miyC/k gSaA izs{k.k }kjk izkIr fd, x, vk¡dM+ksa dk ,e- ,e- 5 esa lfEefyr djus ds fy, vyx&vyx le;ksa ij fy, x, fDodLdsV ds dqN iklsa miyC/k gSaA vk¡dM+ksa dks lfEefyr  djus ds fy, bu vfrfjDr vk¡dM+ksa ls izkjEHk esa fy, x, vk¡dMksa esa o`f) gqbZ gSA buls izkIr gq, ifj.kkeksa ls ;g irk pyk gS fd LdsVªªksehVj  vk¡dM+ksa ds lekos’ku ls izkjfEHkd {ks= okLrfod fLFkfr ds vf/kd fudV FkkA iwokZuqeku tk¡p ls ;g Hkh irk pyk gS fd mixzg ls izkIr fd, x, vk¡dM+ksa ds lekos’ku ls 48 ?kaVs dh vof/k rd dk iwokZuqeku nsus esa lq/kkj gqvk gSA   This study describes the positive impact of QuikSCAT Scatterometer data on tropical cyclone analyses and forecasts using a Mesoscale Model (MM5). QuikSCAT data is especially valuable because they are available in the data sparse genesis regions of tropical cyclones, and because they are available in cloudy and rainy conditions. The model used in the study, MM5 is known as fifth generation NCAR/Penn State Mesoscale model (MM5). In order to understand and investigate the impact of QuikSCAT Scatterometer wind data, simulation with and without assimilation of scatterometer data has been performed for a few tropical cyclone cases during the period 1999 to 2003. For a cyclonic situation, data of few ships of opportunity and of some coastal or island stations are only available. For the assimilation of observed data into MM5, a few passes of QuikSCAT at different times are available. These additional data strengthen the initial data for assimilation. The results showed that the initial field with the inclusion of scatterometer data was nearer to the actual situation. In the prediction experiment, it was also shown that the inclusion of satellite data improved the prediction up to 48 hrs.