Seasonality in the relationship between equatorial-mean heat content and interannual eastern equatorial Atlantic sea surface temperature variability

Interannual sea surface temperature (SST) variations in the tropical Atlantic Ocean lead to anomalous atmospheric circulation and precipitation patterns with important ecological and socioeconomic consequences for the semiarid regions of sub-Saharan Africa and northeast Brazil. This interannual SST variability is characterized by three modes: an Atlantic meridional mode featuring an anomalous cross-equatorial SST gradient that peaks in boreal spring; an Atlantic zonal mode (Atlantic Niño mode) with SST anomalies in the eastern equatorial Atlantic cold tongue region that peaks in boreal summer; and a second zonal mode of variability with eastern equatorial SST anomalies peaking in boreal winter. Here we investigate the extent to which there is any seasonality in the relationship between equatorial warm water recharge and the development of eastern equatorial Atlantic SST anomalies. Seasonally stratified cross-correlation analysis between eastern equatorial Atlantic SST anomalies and equatorial heat content anomalies (evaluated using warm water volume and sea surface height) indicate that while equatorial heat content changes do occasionally play a role in the development of boreal summer Atlantic zonal mode events, they contribute more consistently to Atlantic Niño II, boreal winter events. Event and composite analysis of ocean adjustment with a shallow water model suggest that the warm water volume anomalies originate mainly from the off-equatorial northwestern Atlantic, in agreement with previous studies linking them to anomalous wind stress curl associated with the Atlantic meridional mode.

Seasonal variations, trend in the tropopause height/temperature over Indian stations and its modulations by SST anomalies of east Pacific Ocean

Global warming due to increase in the Green House Gases is now well known. There are several studies, also, suggesting discernible changes over the years in respect of meteorological parameters like, rainfall events, frequency and intensity of tropical cyclones/hurricanes, maximum/minimum temperature, SST of oceans etc, on regional as well as global scale. The present study besides finding out seasonal variations in tropopause height and temperature across each 5° latitude over India based on a longer data set, has demarcated the locations where significant trend in respect of temperature and height was observed over Indian region on annual scale besides investigating the possible causes of this trend. The study has also confirmed significant linear associationship between tropopause temperature/height over Indian stations and SST anomalies of east Pacific Ocean with SST leading by one year.

Predictive relationships between Indian Ocean sea surface temperatures and Indian summer monsoon rainfall

Monthly sea surface temperature (SST) data of 49 years (1950-98) have been analysed to examine the relationship of SST anomalies in the Indian Ocean with Indian summer monsoon rainfall (ISMR) and to derive useful predictors for long-range forecasts of ISMR. There is significant positive relationship between ISMR and SST anomalies over the Arabian Sea during November to January and also in May. SST anomalies over southeast Indian Ocean during February to March and over North Pacific during May are also positively correlated with ISMR. The composite analysis revealed that in Non-ENSO drought years (1966, 1968, 1974 and 1979) negative SST anomalies are observed over south Indian Ocean from February which slowly spread towards equator during the subsequent months. These negative SST anomalies which persist during the monsoon season may be playing an important role in modulating ISMR especially in non-ENSO years. We have derived two indices, ARBSST (SST anomalies in Arabian Sea averaged over 15o - 25o N, 50o -70o E and November-December-January) and SIOSST (SST anomalies over south Indian Ocean averaged over 15o -30o S, 70o -110o E and February and March) as useful predictors for the long-range forecasts of ISMR. The correlation coefficient (for the period 1950-98) of ARBSST and SIOSST with ISMR is 0.45 and 0.46 respectively which is statistically significant at 99.9 % level. SIOSST index has shown consistently stable relationship with ISMR. However the ARBSST index showed significant correlation with ISMR only after 1976.

A simple coupled model of the wind-evaporation-SST feedback with a role for stability

The wind-evaporation-SST (WES) feedback describes a coupled mechanism by which an anomalous meridional sea surface temperature (SST) gradient in the tropics evolves over time. As commonly posed, the (positive) WES feedback depends critically on the atmospheric response to SST anomalies being governed by a process akin to that argued by Lindzen and Nigam (1987), and omits an alternative process by which SST anomalies modulate surface wind speed through vertical momentum mixing as proposed by Wallace et al. (1989) and Hayes et al. (1989). A simple model is developed that captures the essential coupled dynamics of the WES feedback as commonly posed, while also allowing for momentum entrainment in response to evolving SST anomalies. The evolution of the coupled system depends strongly on which effects are enabled in the model. When both effects are accounted for in idealized cases near the equator, the initial anomalous meridional SST gradient grows over a time scale of a few months, but is damped within one year. The sign and magnitude of the WES feedback depend on latitude within the tropics and exhibit hemispheric asymmetry. When constrained by realistic profiles of prevailing zonal wind, the model predicts that the WES feedback near the equator is stronger during boreal winter, while the domain over which it is positive is broader during boreal summer, and that low-frequency climate variability can also modulate the strength and structure of the WES feedback. These insights may aid in the interpretation of coupled climate behavior in observations and more complex models.

Simulation, Precursor Analysis and Targeted Observation Sensitive Area Identification for Two Types of ENSO using ENSO-MC v1.0

The global impact of an El Niño-Southern Oscillation (ENSO) event can differ greatly depending on whether it is an Eastern-Pacific-type (EP-type) event or a Central-Pacific-type (CP-type) event. Reliable predictions of the two types of ENSO are therefore of critical importance. Here we construct a deep neural network with multichannel structure for ENSO (named ENSO-MC) to simulate the spatial evolution of sea surface temperature (SST) anomalies for the two types of events. We select SST, heat content, and wind stress (i.e., three key ingredients of Bjerknes feedback) to represent coupled ocean-atmosphere dynamics that underpins ENSO, achieving skillful forecasts for the spatial patterns of SST anomalies out to one year ahead. Furthermore, it is of great significance to analyze the precursors of EP-type or CP-type events and identify targeted observation sensitive area for the understanding and prediction of ENSO. Precursors analysis is to determine what type of initial perturbations will develop into EP-type or CP-type events. Sensitive area identification is to determine the regions where initial states tend to have greatest impacts on evolution of ENSO. We use saliency map method to investigate the subsurface precursors and identify the sensitive areas of ENSO. The results show that there are pronounced signals in the equatorial subsurface before EP events, while the precursory signals of CP events are located in the North Pacific. It indicates that the subtropical precursors seem to favor the generation of the CP-type El Niño and the EP-type El Niño is more related to the tropical thermocline dynamics. And the saliency maps show that the sensitive areas of the surface and the subsurface are located in the equatorial central Pacific and the equatorial western Pacific, respectively. The sensitivity experiments imply that additional observations in the identified sensitive areas can improve forecasting skills. Our results of precursors and sensitive areas are consistent with the previous theories of ENSO, demonstrating the potential usage and advantages of the ENSO-MC model in improving the simulation, understanding and observations of two ENSO types.

VARIABILITY OF INDIAN SUMMER MONSOON : RELATIONSHIP WITH GLOBAL SST ANOMALIES

(iloh,tlcurr("!,1111111 ll111p .o; uflhe SlIllll1lt" r mUn!\4 lOn prt>cipil:lliull anomalies a nti St"a SU l f.IC(" Tt"mpt"1 a1lln"' (SST) a nUllul!it'.'i are pTt'St'IlI("d . n lir1 ) -)l' /u (1950..1479) rime St' 1; ("S uf 11l0n...nnn ind("x b co rn' l a h~d ....; Ih Iht"SST tillll' Sl'riCS al t"nch 1° ;<2° latitLIl1co! u nl:iluJt" box uf th t" \\(1(111 (>I,:eans usi ng COADS (Comprehensive O..:eanAllno...pl1("fl." Dala S('1)dn ta ttl "3riOUS timc IJgs o f lUonth s (i.t' .. l1luI11 h,'S of year s p recedi ng 'lI1.1 conc urrcnI lu Ihe1ll011Stllll1-)l'at) , Ctl lTclal ion..mups :'I ll' pn.-pUTl,.f 111111 Illaly"I'" 1(1 i.lclltify Il' IN."Oll lle ct it ln "-' Ilf llln ll....oon pTt'I,:ipil<ttiunwilh glubal S ~Ts.It is I'olin.! th ai tlll' lag,orrelatiuns .... ilh SST (Will 1:('01(31 and t'ilstt"m t'lluHt orial Padlic (Ninu-rl'l!inniliresuggl·..liw of IWlI I>p t' S o f inlt"raetjuns .....ith Ihe munsoun. The first on e, .... h il.:h sho ws pmili\'c <:orre lnlio n of summermonsoon pf('\.-ipililtion anoll1alit"s ",i lh Ihe ct"nlral and l":Jsl ..-mequaturial P<lciftc SST nnoUlal ies aboul a yea r be forelilt" 1l10 nsollfl. sUggl°.!>1Sthat lhe monsoon which follo ws abmlt a )'t'lir la ll'r ur tX'currence ofwaml t"pisode of EI..Nin~Suut hem Oscillatiun (ENSO) is generally ....-eltc It is also suggestetJ Ihal this inleract io n might be taki ng placelhruugh Ihe in llue nce or nOr1h em hemisp here int er tempera tures. Th e seco nd I)-PC of inleraclion of equ alorialPaci fic SST ....i lh mon soon is revealed through the strung n~al ive co rrela tio ns bqinning befo re lh e summer monsoon an d continuing ....; lh g~ a l er magnitud e an d o~ r ....i der extent. suuest ing th ai a .....arm SST anomaly j ust precedineanll concurrent to monsoon ~aso n weaken s th e monsson.AiNt"li intcf<n'lions bctween Ihe Indian Ocean and monsoon are also emph a si ~d in the anal ysis. Two key~ginns are ide nt ified. Th e cen tra l Indian Ocun south o f th e equalor shoW!strong positive corre la tions during (helalt' no n hl'm ",inler a nd spring. Th e other key Tq!'ion is in the north Ind ian Geran. Th e correlations are significanllynt'ga li\'e. Some teleconnections with th e Atlantic basin are also revealed which are ralhe rdifficuh to explain but ma yfind usefu l ap plications in monitoring and long-range forecas line of the monsoon.

ASSESSMENT OF POSSIBLE CHANGES IN THE EL NINO AND LA NINA REPEATABILITY BY THE END OF THE XXI CENTURY USING THE CMIP6 MODELS

The quality of SST anomalies revealed in the equatorial Pacific associated with El Niño (EN) and La Ni-ña (LN) in the CMIP6 project models (KIOST-ESM, MIROC-ES2L and INM-CM4-8) was evaluated by comparing with real events in the period 1950 to 2014 using the ERSSTv5 data sets. It is shown that the ensemble model estimation of the number, intensity and duration of EN and LN corresponds quite well to real conditions. On this basis, the corresponding model ensemble calculations of their future possible changes in 2021-2085 relative to the historical 1950-2014 period were carried out for two possible sce-narios: business-as-usual (SSP2-4.5) and negative (SSP5-8.5).

Relationship between Indian summer monsoon rainfall and sea surface temperature anomalies over equatorial central and eastern Pacific

Sea surface temperature (SST) variations over the three key regions over equatorial Pacific, viz., Nino (1+2), Nino 3 and Nino 4 and their relationships with Indian summer monsoon rainfall have been examined in this study. On monthly scale, SST anomalies over the three key regions show an oscillatory type of lagged correlations with Indian monsoon rainfall, positive correlations almost one year before the monsoon season (CC's are of the order of 0.3) which gradually change to significant negative correlation peaking in September/October during/after the monsoon season. The variations on seasonal scale also exhibit the same pattern of monthly variations but more smooth in nature. Composites of similar monsoon years show that during deficient (excess) monsoon years SST anomalies over all the three regions have warmer (cooler) trend which starts about 6 months prior to monsoon season. Tendencies of SST anomalies from previous winter (DJF) to summer (MAM) seasons over Nino 3 and Nino 4 regions are better predictors than EI-Nino categories currently being used in IMD's operational LRF model. By using tendency of SST over EI- Nino -4 region, in place of the category of EI-Nino, the 16 parameter operational Power Regression Model of IMD has been modified. The new forecast model shows better reduction in the forecast error.

Influence of some circulation anomalies on Indian northeast monsoon rainfall

The relationship between Indian northeast monsoon rainfall over Tamil Nadu (TNR) and southeast India (SER) as well as two indices of southern oscillation (SOI), and sea surface temperature (SST) anomalies over different Nino regions of equatorial Pacific Ocean and seven tropical circulation indices (TCI), have been studied for different periods. The study indicates that northeast monsoon rainfall (TNR) shows significant inverse relationship with SOI (I-D) during previous MAM (March- April-May) season. significant direct relationship with SST anomalies over Nino-4 region during previous JJA (June-July- August) and significant direct relationship with TCI (C-N) during previous DJF, The SOI (I-D), MAM correlates I significantly and negatively with both the northeast monsoon rainfall series, the TNR rainfall series displaying the better correlation. The strongest correlation is observed during 1961-90. For SSTA, the strongest correlation is during 1964-85 and for TCI, the highest correlation is observed during 1958-82.