scholarly journals Relationship between monsoon onset over Thiruvananthapuram and Mumbai and rainfall over Kerala and Konkan

MAUSAM ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 445-450
Author(s):  
M. P. SHEWALE ◽  
A. S. PONKSHE

Lkkj & bl ’kks/k&Ik= esa nks LFkkuksa uker% fFk:ouUriqje vkSj eqEcbZ dk p;u djds ;g irk yxkus dk iz;kl fd;k x;k gS fd D;k ekulwu ds vkxeu dh rkjh[k dk Øze’k% dsjy vkSj dksad.k esa gksus okyh o"kkZ ds lkFk dksbZ laca/k gS A lewps ns’k ds fy, Hkkjrh; xzh"edkyhu ekulwu o"kkZ ¼vkbZ- ,l- ,e- vkj-½ ds lkFk ekulwu ds vkxeu dh rkjh[k ds laca/k dh Hkh tk¡p dh xbZ gS A bl v/;;u ds fy, 100 o"kksaZ ¼1901&2000½ ds vk¡dM+ksa dk mi;ksx fd;k x;k gS A             fo’ys"k.k dh lgk;rk ls vk¡dM+ksa dh ,d:irk vkSj o"kkZ ds vU; y{k.kksa dh tk¡p dh xbZ gS A dsjy vkSj dksad.k esa vdky vkSj ekSle laca/kh ck<+ dh ledkfyd ?kVukvksa dh vko`fr dk irk yxk;k x;k gS vkSj mldh tk¡p dh xbZ gS A             bl v/;;u ls ;g irk pyk gS fd ekulwu ds vkxeu ds laca/k esa fFk:ouUriqje vkSj eqEcbZ ds chp egRoiw.kZ laca/k gS A fFk:ouariqje vFkok eqEcbZ vkSj vkbZ- ,l- ,u- vkj- ds chp ekulwu ds vkxeu ds ckjs esa fdlh egRoiw.kZ laca/k dk irk ugha pyk gS A dsjy dh rqyuk eas dksad.k esa ekSle laca/kh ck<+ vf/kd vkrh gS A In this paper, choosing two locations viz., Thiruvananthapuram and Mumbai, an attempt has been made to find whether the onset date of monsoon has any bearing on monsoon rainfall over Kerala and Konkan respectively.   Association of the onset dates with Indian Summer Monsoon Rainfall (ISMR) for the country as a whole has also been explored.  The study utilizes 100 years’ (1901-2000) data. Homogeneity of the data and other rainfall features have been examined with the help of  analysis.  Frequency of simultaneous occurrence of droughts and meteorological floods at Kerala and Konkan have been determined and examined.    The study showed that onset over Thiruvananthapuram and Mumbai are significantly related.  It revealed absence of any significant relationship between onset over Thiruvananthapuram or Mumbai and the ISMR. Meteorological floods seem to be more frequent over Konkan compared to Kerala.

2021 ◽  
Author(s):  
Stella Jes Varghese ◽  
Kavirajan Rajendran ◽  
Sajani Surendran ◽  
Arindam Chakraborty

&lt;p&gt;Indian summer monsoon seasonal reforecasts by CFSv2, initiated from January (4-month lead time, L4) through May (0-month lead time, L0) initial conditions (ICs), are analysed to investigate causes for the highest Indian summer monsoon rainfall (ISMR) forecast skill of CFSv2 with February (3-month lead time, L3) ICs. Although theory suggests forecast skill should degrade with increase in lead-time, CFSv2 shows highest skill with L3, due to its forecasting of ISMR excess of 1983 which other ICs failed to forecast. In contrast to observation, in CFSv2, ISMR extremes are largely decided by sea surface temperature (SST) variation over central Pacific (NINO3.4) associated with El Ni&amp;#241;o-Southern Oscillation (ENSO), where ISMR excess (deficit) is associated with La Ni&amp;#241;a (El Ni&amp;#241;o) or cooling (warming) over NINO3.4. In 1983, CFSv2 with L3 ICs forecasted strong La Ni&amp;#241;a during summer, which resulted in 1983 ISMR excess. In contrast, in observation, near normal SSTs prevailed over NINO3.4 and ISMR excess was due to variation of convection over equatorial Indian Ocean, which CFSv2 fails to capture with all ICs. CFSv2 reforecasts with late-April/early-May ICs are found to have highest deterministic ISMR forecast skill, if 1983 is excluded and Indian monsoon seasonal biases are also reduced. During the transitional ENSO in Boreal summer of 1983, faster and intense cooling of NINO3.4 SSTs in L3, could be due to larger dynamical drift with longer lead time of forecasting, compared to L0. Boreal summer ENSO forecast skill is also found to be lowest for L3 which gradually decreases from June to September. Rainfall occurrence with strong cold bias over NINO3.4, is because of the existence of stronger ocean-atmosphere coupling in CFSv2, but with a shift of the SST-rainfall relationship pattern to slightly colder SSTs than the observed. Our analysis suggests the need for a systematic approach to minimize bias in SST boundary forcing in CFSv2, to achieve improved ISMR forecasts.&lt;/p&gt;


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