Indian summer monsoon and the east equatorial pacific sea surface temperature

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1 Atmosphere-Ocean ISSN: (Print) (Online) Journal homepage: Indian summer monsoon and the east equatorial pacific sea surface temperature D.A. Mooley & B. Parthasarathy To cite this article: D.A. Mooley & B. Parthasarathy (1984) Indian summer monsoon and the east equatorial pacific sea surface temperature, Atmosphere-Ocean, 22:1, 23-35, DOI: / To link to this article: Published online: 15 Nov Submit your article to this journal Article views: 173 View related articles Citing articles: 24 View citing articles Full Terms & Conditions of access and use can be found at

2 Indian Summer Monsoon and the East Equatorial Pacific Sea Surface Temperature D.A. Mooley and B. Parthasarathy Indian Institute of Tropical Meteorology Pune, India [Original manuscript received 4 July 1983; in revised form 15 November 1983] ABSTRACT A detailed examination has been made of the relationship between the space and time variations of the Indian summer monsoon rainfall and the equatorial eastern-pacific sea surface temperature (SST) anomaly in different seasons for the 108-year period, There is a strong inverse relationship between the two. The correlation coefficients between All-India monsoon rainfall and the sea surface temperature anomaly for the concurrent season; June, July and August (JJA) and for the succeeding seasons; September, October and November (SON) and December, January and February (DJF) are consistently and highly significant. Even a random sample of 50 years gave values significant at the 0.1 percent level. The sliding window correlation analysis of 10-, 20- and 30-year widths indicates that the relationships between All-India monsoon rainfall and the sea surface temperature anomaly for the concurrent JJA and the succeeding SON and DJF seasons exhibit stability and consistency in significance. For contiguous meteorological sub-divisions west of longitude 80 E the relationship is highly significant for JJA and for succeeding SON and DJF seasons. RÉSUMÉ On effectue un examen minutieux du rapport qui existe entre la variation dans le temps et l'espace des pluies estivales de la mousson indienne et l'anomalie de la température superficielle de la mer au cours des différentes saisons au cours des 108 années s'étendant de 1871 à Il existe un rapport inverse éminent entre les deux. Les coefficients de corrélation entre les pluies de la mousson de toutes les Indes et les anomalies de la température superficielle de la mer pour la même saison, notamment juin, juillet, août (JJA) et entre les saisons successives septembre, octobre, novembre (SON) et décembre, janvier et février suivants (DJF), sont systématiquement et fortement significatifs. Un échantillon de 50 années aléatoires a généré des valeurs significatives à un niveau de signification de 0.1%. L'analyse des corrélations mouvantes à 10, 20 et 30 ans d'intervalles révèle que le rapport entre les chutes de pluies de la mousson sur toutes les Indes et l'anomalie de la température superficielle de la mer pour les mois de JJA et les mois des saisons successives de SON et DJF reflète une signification stable et systématique. La relation est fortement significative pour JJA et les saisons de SON et DJF qui la succède dans les subdivisions météorologiques contiguës à l'ouest de la longitude de 80 E. ATMOSPHERE-OCEAN 22(1) 1984, /84/ $01.25/0 Canadian Meteorological and Océanographie Society

3 24 / D.A. Mooley and B. Parthasarathy 1 Introduction India is a predominantly agricultural country with a low percentage of area under irrigation and a high concentration (75 to 90%) of annual rainfall occurring during the four months of the summer monsoon (June to September). In view of this situation, the failure of the monsoon has a very adverse impact on the economy of the country (Mooley et al., 1981, 1982; Mooley and Parthasarathy, 1982). As the human suffering resulting from monsoon failure is large, there has been a growing desire and effort to better understand the monsoon. The first official monsoon forecast was issued by Henry Blanford on 4 June 1886, and was based entirely on the excessive winter and spring snowfall in the Himalayan and Hindukush mountains. He found that this snowfall is prejudicial to the subsequent Indian monsoon rainfall. John Eliot soon realized that Indian conditions alone were not sufficient and used extra-indian data, e.g. observations on the Southeast trades of Mauritius, Zanzibar and Seychelles, in the monsoon forecast for Sir Gilbert Walker was the first meteorologist to systematically examine the relationship between Indian monsoon rainfall and global circulation factors; he selected 28 factors to issue a monsoon forecast during Some of the parameters used by Walker are still in use in the India Meteorological Department. Walker discovered that when the surface pressure was low over Indonesia it was high over the Pacific near Easter Island and vice versa; this so-called "Southern Oscillation" has since been shown to account for much of the variation of rainfall in many of the tropical areas (Bjerknes, 1969). The Walker Circulation or Southern Oscillation is an important mode of operation of the tropical atmosphere generally characterized by the exchange of air between the Eastern (predominantly land) and Western (predominantly ocean) Hemispheres. The interaction between the atmosphere and the sea at the air-sea interface results in the coupling of the circulation systems of the atmosphere at the ocean. Since 70% of the earth's surface is covered with water and changes in sea surface temperature are much slower than atmospheric fluctuations, it is apparent that the interannual variability of sea surface temperature may be responsible for the variability of the atmospheric circulation and may well be reflected in the rainfall regimes. It has gradually been realized that the ocean plays an important part in the mechanism of teleconnections. Much work has been done on the relationship between the Indian monsoon and the sea surface temperature of the Indian Ocean, notably by Shukla and Misra (1977), Weare (1979), Anjaneyulu (1981), Ramesh Babu et al. (1981) and Joseph (1981). The relationship between the Indian monsoon and the Pacific Ocean sea surface temperature has been studied by Khandekar (1979, 1982), Sikka (1980), Angelí (1981), Webster (1981), Rasmusson and Carpenter (1982, 1983) and Mooley and Parthasarathy (1983a). Rowntree (1972), Shukla (1975), Julian and Chervin (1978) and Keshavamurty (1982) used general circulation models to study the response of the atmosphere to a fixed sea surface temperature anomaly in the tropical Pacific and showed that the atmosphere is much more closely coupled to the state of the underlying ocean in the tropics than elsewhere. Bjerknes (1969) showed that, during episodes of the El Niño off the west coast of South America, ocean temperatures became higher than usual in the tropical Pacific. Rasmusson and Carpenter (1983)

4 Indian Monsoon and the East Equatorial Pacific SST / 25 and Mooley and Parthasarathy (1983b) demonstrated a strong relationship between El Niño events off the Peru coast and deficient rainfall over India. It is the purpose of this study to examine the detailed relationships between the monsoon rainfall of India as well as its subdivisions and eastern equatorial Pacific sea surface temperature anomalies during different seasons and for different time lags. 2 Details of data a Indian Summer-Monsoon Rainfall The validity of any statistical analysis depends primarily on the quality of the data used in the analysis. To avoid inhomogeneity owing to a network varying from year to year, a fixed network of long-period rain-gauge stations consisting of one rain-gauge from each district (a district being a small administrative unit in India) has been selected. This network consists of 306 stations located throughout the country except in the hilly areas. Since the areal representativeness of rain-gauges in hilly areas is small and the network density inadequate the area of the country parallel to the Himalayan mountain ranges has not been considered; this includes Jammu and Kashmir, Himachal Pradesh, the hills of west Uttar Pradesh, Sikkim of sub- Himalayan west Bengal and Arunachal Pradesh of Assam (shown by the hatching in Fig. 1). Two island subdivisions far away from the mainland, i.e. Bay Islands (Subdivision No. 1) and Arabian Sea Islands (Subdivision No. 33), which are not shown in Fig. 1, have not been considered also. The study area measured 2.88 X 10 D km 2 and is 90 per cent of the total area. Hereafter, this area will be referred to as India or the country. The June to September rainfall amounts at the 306 stations were obtained from the relevant India Meteorological Memoirs (for details, see Mooley et al., 1981 ; Mooley and Parthasarathy, 1983a). Summer monsoon (June to September) rainfall averages for the 29 meteorological subdivisions of this study have been computed for each of the years, , by weighting the station rainfall by the area of the district that it represents. In a similar way, the monsoon rainfall series of India taken as one unit (hereafter referred to as the All-India monsoon rainfall) has also been computed for the 108-year period. We have thus prepared two types of rainfall series on two space scales, one for All-India and the other for the 29 meteorological subdivision^ The statistical properties of these two rainfall series were examined. The homogeneity of each series was examined by Swed and Eisenhert's test (WMO, 1966) on the number of runs above and below the median. The AlMndia and 29-subdivision series show that the number of runs lie within the required limits at the 5% significance level. The nature of the frequency distribution was tested by the Chi-square statistic with 10 equal probability class intervals (Cochran, 1952). The normality test shows that the All-India and the 29-subdivision rainfall series are not different from normally distributed at the 5% level. The Markov-type persistence of the series has been tested examining the autocorrelation coefficients up to 3 lags. The rainfall series do not show any persistence at the 5% level. It is therefore inferred that these series, i.e. All-India and 29-subdivision summer monsoon rainfall for the period , are homogeneous, Gaussian-distributed and do not show any significant persistence.

5 26 / D.A. Mooley and B. Parthasarathy 68*E 72* 76* 80* 84* 8 8* 92* 96*E 36' " (CAKNICOtAK 72 76* 80 84* E 2 NORTH ASSAM 12 PUNJAB 3 SOUTH ASSAM 13 HIMACHAL PRADESH 4 SUB-HIMALAYAN WEST 14 JAMMU AND KASHMIR BENGAL 5 WEST RAJASTHAN 3 SANGET.C WEST BENGAL )6EAST RAJASTHAN 6 ORISSA 17 WEST MADHYA 7 BIHAR PLATEAU PRADESH B BIHAR PLAINS 9 EAST UTTAR PRADESH 19 GUJARAT 18 EAST MADHYA PRADESH 28 TAMIL NADU 10 WEST UTTAR PRADESH 20 SAURASHTRA A KUTCH 11 HARAYANA 21 KONKAN 22 MADHYA MAHARASHTRA 23 MARATHWADA 24 VI DARBHA 25 COASTAL ANDHRA PRADESH 2 6 TELANGANA 27 RAYALSEEMA 29 COASTAL KARNATAKA 30 NORTH KARNATAKA 31 SOUTH KARNATAKA 32 KERALA Fig. 1 Meteorological subdivisions of contiguous India for the study area, excluding the hilly area (hatched).

6 Indian Monsoon and the East Equatorial Pacific SST / 27 TABLE 1. Correlation coefficient between the All-India summer monsoon rainfall and Angell's (1981) SST anomaly for different seasons All-India Summer Monsoon Periods SST Season 108 years ( ) 54 years ( ) 54 years ( ) DJF (Preceding) MAM (Preceding) IJA (Concurrent) SON (Succeeding) DJF (Succeeding) * t t t * t t t t t t Significant at the 5% level. tsignificant at the 0.1% level. b Sea Surface Temperature (SST) Anomalies in the Equatorial Eastern Pacific Ocean Much work has been done on the relationship between the Indian monsoon and the sea surface temperature of the Pacific Ocean, mainly by Khandekar (1979), Angelí (1981), Rasmusson and Carpenter (1983) and Mooley and Parthasarathy (1983b). Angelí (1981) has found that the variations of sea surface temperature in the equatorial Pacific lag behind those of the Indian monsoon rainfall by one or two seasons; and Rasmusson and Carpenter (1982,1983) have shown that the wanner sea surface temperatures or an El Niño event actually leads to below-normal Indian monsoon rainfall. We, therefore, considered that the link between the interannual variations of Indian monsoon rainfall in space and time and homogeneous rainfall data in space and time and equatorial tropical Pacific sea surface temperature anomaly should be investigated in detail. The seasonal sea surface temperature anomaly values of Angelí (1981), which are averaged over a wide area (0-10 S, W) of the equatorial Pacific Ocean and which are available for the long period from 1860 to 1979, have been used in this study. The anomaly series for the 108-year period, , were divided into standard seasons relative to the major rainfall season - June, July and August (JJA) as follows: the preceding December, January and February (DJF); the preceding March, April and May (MAM); the concurrent June, July and August (JJA); the succeeding September, October and November (SON) and the succeeding December, January and February. These series were subject to Swed and Eisenhart's test and found to be generally homogeneous at the 5% ievel. The examination of the first three autocorrelations of these series did not indicate any persistence. 3 Relationship between Indian monsoon rainfall and the east equatorial Pacific sea surface temperature anomaly Our study is primarily based on correlation analysis of the different time series. As such, the autocorrelations within individual series must be considered when assessing the significance of the cross-correlations between any two series (Quenouille, 1952; Sckemarnrnano, 1979). Since we have found that none of the series investigated has

7 28 / D.A. Mooley and B. Parthasarathy 20-YEAR SLIDING WINDOW 10-YEAR SLIDING WINDOW Fig. 2 Variation of the correlation coefficient (CC) between All-India summer monsoon rainfall and Angell's SST-MAM anomaly for 10-, 20- and 30-year sliding window widths over the period The dashed line indicates the CC value significant at the 1% level. 30-YEAR SLIDING WINDOW Fig. 3 As Fig. 2, except for Angell's SST-JJA anomaly. significant persistence, there is no change in the degrees of freedom (N 2) to be used in assessing the correlations, where N is the length of the series. a All-India Rainfall Series 1 RELATIONSHIP FOR THE WHOLE PERIOD AND FOR THE TWO HALVES OF THE PERIOD The correlation coefficients between the All-India monsoon rainfall series and the sea surface temperature anomaly were calculated for (i) preceding DJF, (ii) preceding MAM, (iii) concurrent JJA, (iv) succeeding SON and (v) succeeding DJF for the whole series as well as for the two halves of the series; strong negative correlations

8 Indian Monsoon and the East Equatorial Pacific SST / 29 Fig. 4 As Fig. 2, except for Angell's SST-SON anomaly. Fig. 5 As Fig. 2, except for Angell's SST-DJF anomaly. were found. The main results are shown in Table 1, namely: (a) the inverse relation between monsoon rainfall and sea surface temperature anomaly is significant at the 0.1% level for SST-JJA, SST-SON and the succeeding SST-DJF, both for the whole series as well as for each of its two halves, (b) the relationship for the SST-MAM season is significant at the 5% level for the whole series and the first half of the series, but not for second half and (c) there is no significant relationship with

9 *' ? 92*ī 72' ^SIGNIFICANT CC AT 5% LEVEL [ļļļļļļ SIGNIFICANT CC AT 0-1% LEVEL ;:ff/ SIGNIFICANT CC AT I'/. LEVEL. Fig. 6 Angell's SST-MAM series. Fig. 7 Angell's SST-JJA series.

10 " 84 08' J SIGNIFICANT CC AT 01% LEVEL [T-Y-Vl SIGNIFICANT CC AT 1% LEVEL Fig. 8 Angell's SST-SON series. 88* 9TĒ SIGNIFICANT CC AT 01% LEVEL [rnr^] SISNIFICANT CC AT I% LEVEL Fig. 9 Angell's SST-DJF series. Figs. 6-9 Correlation coefficient (CC) between the summer monsoon rainfalls in different meteorological subdivisions and specific Angell's series forthe 108-year period

11 3 2 / D.A. Mooley and B. Parthasarathy SST-DJF of the preceding season. It should be noted that from the studies of Mooley et al. (1982) and Mooley and Parthasarathy (1982, 1983b) a rather larger number of abnormal monsoon rainfall years have occurred during the first half of the period (i.e ) than during the second half (i.e ). To examine the stability and consistency of the relationship, a random sample of 50 years was selected such that no year was repeated and no two years were contiguous. The correlation coefficients between the All-India monsoon rainfall and the sea surface temperature anomaly for the concurrent JJA and succeeding SON were computed and found to be and 0.61, respectively. These values are significant at the 0.1 % level indicating that the relationships are stable and consistent. 2 VARIATIONS IN THE RELATIONSHIP OVER DIFFERENT SLIDING PERIODS The consistency of the relationship for different periods was examined by calculating the correlation coefficient using the "sliding window" method (Bell, 1977) with window widths of 10,20 and 30 years. The relationship with earlier seasons may find an application in seasonal forecasting, and the concurrent relationships will be useful for the modelling of the monsoon general circulation incorporating teleconnections. The relationship with the later sea surface temperature anomalies may be useful in forecasting those anomalies. The variation of the correlation coefficient between the All-India summer monsoon rainfall and the sea surface temperature anomalies for the MAM, JJA, SON and succeeding DJF seasons are shown in Figures 2, 3, 4 and 5, respectively. The correlation coefficient value significant at the 1% level is indicated in each figure by a dashed line; the value for a particular sliding interval is plotted against the first year of the interval. Thus all curves commence in 1871 and terminate in different years as given by ( W) + 1, where W is the width of the sliding window. It is generally observed from all of these figures that the 10-year sliding values are more oscillatory than the 20- and 30-year values. For the 10-year sliding window, the variation of the correlation coefficient is highest for the MAM season. Some of the values are significant at the 5% level. For the concurrent and succeeding seasons, most of the correlation coefficients are significant at the 5% level. The values for the 20-year window are less variable and the significance levels are higher for the concurrent and succeeding seasons than for the preceding season. The correlation coefficients are more stable for the 30-year sliding widths and they are generally significant at the 1% level or better. The inverse relationship is thus significant and consistent, almost in every season for the 30-year window. It is clear that the sea surface temperature anomaly is an important feature to be taken into account while formulating the seasonal forecasting relationships for Indian rainfall. The variability in the relationship could be due to other independent factors that have variable relationships with the monsoon rainfall. The noise in the data series may also contribute to changes in the correlation coefficients. Consistency of the correlation coefficients is a feature that cannot be expected when several factors/ parameters have an influence on rainfall. However, if the relationship between the monsoon rainfall and a particular parameter is high, then it is possible for the relationship to be consistently significant over different periods.

12 Indian Monsoon and the East Equatorial Pacific SST / 33 b Subdivision Rainfall Series It is observed that India is perhaps too large to be considered as a single unit, since the inter-correlations between All-India rainfall and the rainfall amounts in some meteorological subdivisions are not significant at the 1% level. These subdivisions are: (i) North Assam, (ii) South Assam, (iii) sub-himalayan west Bengal, (iv) Gengetic west Bengal, (v) the Bihar Plateau and (vi) the Bihar plains located in northeast India. The remaining 23 subdivision rainfall series are highly correlated and have correlation coefficients that are mostly significant at the 1% level. In view of this we have examined the relationship between the sea surface temperature anomalies for the different seasons and the monsoon rainfall series of the different Indian meteorological subdivisions. The correlation coefficients between the monsoon rainfall series of the 29 meteorological subdivisions and the sea surface temperature anomalies for the preceding season, the current season, one succeeding season and two succeeding seasons, have been calculated for the whole period and the results are shown in Figs. 6 to 9. The correlation coefficients for the SST-MAM (Fig. 6) are generally negative. There are 7 subdivisions for which the values are significant at the 5% level but these are scattered around the country. The relationships with the concurrent SST-JJA (Fig. 7) and the succeeding SST-SON (Fig. 8) are much stronger with values significant at the 1% level for more than 18 subdivisions (65% of the area of the country) in the former and 20 subdivisions (66% of the area) in the latter. This relationship is also evident in the values for two seasons (Fig. 9) where 20 subdivisions have values significant at the 1% level. The relationship between the SST anomaly and the monsoon rainfall is generally negative and significant at the 5% level or better over most contiguous Indian regions for concurrent and succeeding seasons. The correlation coefficients are higher for the concurrent and succeeding seasons than for the preceding season. 4 Conclusions The study of the Indian summer monsoon rainfall and its associations with sea surface temperature anomalies for different seasons has revealed the following results: (i) The correlations between Indian monsoon rainfall and the sea surface temperature anomalies for different seasons are invariably negative suggesting an inverse relationship. (ii) The relationship between the All-India monsoon rainfall and the sea surface temperature anomalies for the concurrent season (JJA) and for the succeeding seasons (SON and DJF) are consistently significant at the 1% level or better, (iii) The relationship for the contiguous subdivisions of the country west of 80 E is significant at the 1% level for the SST-JJA, SST-SON and SST-DJF seasons. The large-scale behaviour of the monsoon over the Indian subcontinent must be regarded as an important planetary-scale phenomenon having an association with sea surface temperatures and raises important questions of cause and effect.

13 34 / D.A. Mooley and B. Parthasarathy Acknowledgements The authors are grateful to Dr Bh.V. Ramana Murty, Director, Indian Institute of Tropical Meteorology, Pune, for his interest and encouragement and for providing the facilities to pursue this study, and to the Deputy Director General of Meteorology (Research), Pune, for making available the necessary rainfall data. They would like to convey their deep gratitude to Dr J.K.- Angell, NOAA, Air Resources Laboratories, U.S.A. for supplying the sea surface temperature anomaly data for the eastern equatorial Pacific Ocean. The authors also thank Mrs N. A. Sontakke and Mr A.A. Munot for their assistance in the computations and Mrs S.P. Lakade for typing the manuscript. References ANGELL, J.K Comparison of variations in atmospheric quantities with sea surface temperature variations in the equatorial eastern Pacific. Mon. Weather Rev. 109: ANJANEYULU, T.S.S A study of the air and sea surface temperature over the Indian Ocean. Mausam, 31: BELL, G.J Changes in sign of the relationship between sunspots and pressure, rainfall and the monsoon. Weather, 32: BJERKNES, J Atmospheric teleconnections from the equatorial Pacific. Mon. Weather Rev. 97: CocHRAN, w.g Chi-square test of goodnessof-fit. Ann. Math. Stat. 23: JOSEPH, P.V Ocean-atmosphere interaction on a seasonal scale over north Indian Ocean and Indian monsoon rainfall and cyclone tracks - A preliminary study. Mausam, 32: JULIAN, p.r. and R.M. CHERViN A study of the Southern Oscillation and Walker Circulation phenomenon. Mon. Weather Rev. 106: KESHAVAMURTY, R.N Response of the atmosphere to sea surface temperature anomalies over the equatorial Pacific and the teleconnections of the Southern Oscillation. J. Atmos. Sci. 39: KHANDEKAR, M.L Climatic teleconnections from the equatorial Pacific to the Indian monsoon, analysis and implications. Arch. Meteorol. Geophys. Bioklimatol. A28: Comments on "Planetary-scale phenomena associated with the Southern Oscillation". Mon. Weather Rev. 110: MOOLEY, D.A.; B. PARTHASARATHY, N.A. SON- TAKKE and A.A. MUNOT Annual rainwater over India, its variability and impact on the economy. J. Climatol. 1: and Fluctuations in the deficiency of the summer monsoon over India, and their effect on economy. Arch. Meteorol. Geophys. Bioklimatol. B30: ; and N.A. SONTAKKE An index of summer monsoon rainfall excess over India and its variability: Arch. Meteorol. Geophys. Bioklimatol. B31: and. 1983a. Variability of the Indian summer monsoon and tropical circulation features. Mon. Weather Rev. 111: and. 1983b. Indian summer monsoon and El Niño. Pure Appl. Geophys. 102: (in print). QUENOUILLE, M.H Associated Measurements. Butterworths Scientific Publications, London, 242 pp. RAMESH BABU, V.; L.V.G. RAO and V.V.R. VARA- DACHARI Sea temperature variations in the north Arabian Sea in relation to the southwest monsoon. In: Monsoon Dynamics. J. Lighthills and R.P. Pearce, Eds, Cambridge Univ. Press, London, pp RASMUSSON, E.M. and T.H. CARPENTER Variations in tropical sea surface temperature and surface wind field associated with the Southern Oscillation/El Niño. Mon. Weather Rev. 110: and The relationship between eastern equatorial Pacific sea surface temperature and rainfall over India and Sri Lanka. Mon. Weather Rev. 111: ROWNTREE, P.R The influence of tropical east Pacific ocean temperatures on the atmosphere. Q.J.R. Meteorol. Soc. 98: SciREMAMMANO, F., JR A suggestion for the presentation of correlations and their significance levels. J. Phys. Oceanogr. 9:

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