Normalized anomaly patterns of meteorological elements: A case study of Northeast monsoon 2002 and 2004

Abstract

ekSle foKkfud vk¡dM+ksa dks lkekU;h—r folaxfr;ksa ds laca/k esa crkuk izk;% lgk;d jgrk gS D;ksafd blls lkekU; cuke vlkekU; ekuksa dks igpkuuk ljy gks tkrk gSA blds vykok blls LFkku ds izHkko rFkk vk¡dM+ksa ds izlkj dk izHkko nwj gksrk gS vkSj nks fHkUu LFkkuksa esa izs{k.kksa dh rqyuk lqfo/kktud gks tkrh gSA bl izdkj lkekU;h—r folaxfr ¼,u- ,-½ iSVuZ vFkkZr fu/kkZfjr le; esa folaxfr;ksa dk LFkkfud forj.k izfrdwy ekSle dh ?kVukvksa esa iwokZuqekudrkZvksa ds fy, ,d l’kDr midj.k cu tkrk gSA

bl 'kks/k i= esa mRrjiwohZ ekWulwu 2002 dh varj&ekSleh fof’k"V iz—fr ij fopkj djrs gq, ekSle dh izfrdwy ?kVukvksa dk fo’ys"k.k djus ds fy, ,u- ,- iSVuZ ds mi;ksx ij dk;Z fd;k x;k gSA mRrj iwohZ ekWulwu 2002 ds nkSjku lw[ks tSlh fLFkfr;ksa ds ckjs esa foLrkj ls ppkZ dh xbZ gS vkSj muds dkj.kksa dh tk¡p  dh xbZ gSA ;g Hkh ns[kk x;k gS fd mRrj iwohZ ekWulwu 2002 ds varj ekSleh iz—fr iSVuZ esa izsf{kr lw[ks tSls fLFkfr dk ,d dkj.k 200 ,p- ih- ,- Åijh ry fjt dk gksuk vFkok ldkjkRed HkwfoHko Å¡pkbZ folaxfr] uoEcj esa lkbcsfj;u gkbZ esa udkjkRed ek/; leqnz Lrj nkc folaxfr] 200 ,p- ih- ,- iou folaxfr dh rhozrk gks ldrk gSA fuEu es?k ek=k] 'kq"d cYc rkieku vkSj lkis{k vknzZrk ls mRrj iwohZ ekWulwu 2002 esa lw[ks tSlh fLFkfr;ksa dk irk pyk tcfd vkSlr iou xfr  ds ,u- ,- ls caxky dh [kkM+h esa pØokrksa ds {kh.k gksus vkSj izk;}hih; Hkkjr rd ugha igq¡pus ds ckjs esa irk pykA mRrj iwohZ ekWulwu 2004 ds fy, fuEu es?k ek=k] lkis{k vknzZrk] 'kq"d cYc rkieku rFkk vkSlr iou xfr ds ,u- ,- iSVuZ ls mRrj iwohZ ekWulwu 2002 ds ekeys esa bu ekSle foKkfud izkpyksa ds fy, ,u- ,- iSVuZ esa lw[ks tSls fLFkfr;ksa ds izs{k.kksa dh iqf"V gqbZA

It is often helpful to express the meteorological data in terms of normalized anomalies as they make it easier to discern normal versus unusual values. Also it removes influence of location and spread from data and facilitates the comparison of observations at two different locations. Thus, Normalized Anomaly (NA) patterns i.e., spatial distribution of anomalies at specified time make a powerful tool in hand of forecasters to analyze extreme events.

The present study explores the utilization of NA patterns for the purpose of analyzing extreme events by focusing on the inter-seasonal peculiar behavior of Northeast monsoon 2002. A detailed discussion is given and reasons are explored for droughts like situations during Northeast monsoon 2002. It was also noticed that the persistence of 200 hPa upper level ridge or positive geopotential height anomaly, negative mean sea level pressure anomaly over Siberian High during November, strength of 200 hPa wind anomaly can be one of the reasons for drought-like situation observed in the inter-seasonal behavior pattern of Northeast monsoon 2002. NA patterns of low cloud amount, dry bulb temperature and relative humidity captured drought-like situations during Northeast monsoon 2002 while NA of average wind speed captured the scenario of dissipating cyclones in the Bay of Bengal itself and not reaching to Peninsular India. The NA patterns of low cloud amount, relative humidity, dry bulb temperature and average wind speed for Northeast Monsoon 2004 confirm the observations of drought like situations seen in NA patterns for these meteorological parameters in case of Northeast monsoon 2002.