ENSO and monsoon induced sea level changes and their impacts along the Indian coastline

Indian Journal of Marine Sciences Vol. 35(2), June 2006, pp. 87-92 ENSO and monsoon induced sea level changes and their impacts along the Indian coastline O.P.Singh* Monsoon Activity Centre, India Meteorological Department, New Delhi-110003, India *[E-mail : op_singh54@yahoo.com ] Recevied 27 Decmber 2004, revised 15 June 2005 For preparedness programmes aimed at combating sea level - associated disasters, it is necessary to carry out comprehensive studies on different aspects of sea level variability. On many occasions the interannual modes dominate the long term trends of mean sea level (MSL). In South Asian region El Niño-Southern Oscillation (ENSO) induced variation is an important component of sea level variability on the interannual time scale. In the present paper focus is on the ENSO and monsoon modes of interannual variability of MSL along the Indian coast. The results have revealed that good concurrent correlations exist between the Southern Oscillation Index (SOI) and the Mean Tidal Level (MTL) at Visakhapatnam during the intense cyclone period of the year, i.e. May, October and November. Also, in the end phase of the southwest monsoon (i.e. during September) MTL is significantly correlated to the SOI. During the cold phase of ENSO (i.e. positive SOI) MSL is higher over the east coast of India enhancing the hazardous potential of the Bay of Bengal tropical cyclones. ENSO seems to have relatively lesser impact on the MSL variation over the west coast of India. However, during September (southwest monsoon) the correlations between the MTL and SOI are significant, both at Mumbai and Kochi. Thus ENSO appears to influence the MSL along the west coast of India during the ending phase of the southwest monsoon. The SOI-sea level relationship has prognostic utility also. High positive correlations exist between MSL along the east coast of India during the intense cyclone period (May, October and November) and the SOI of preceding month which can provide predictive indications of sea level one month in advance. Significant concurrent correlations have been found between monthly rainfall and MSL over the west coast of India during the southwest monsoon season. The correlation coefficients of the order of ~ +0.5 have been observed between the seasonal monsoon rainfall over Konkan and Goa coast and seasonal MSL at Mumbai; and seasonal monsoon rainfall over Kerala and seasonal MSL at Kochi. It is interesting to note that correlations between the monsoon rainfall and MSL over the east coast of India are poor, implying that the southwest monsoon rainfall has very little influence on the sea level variations over the east coast of India. It may be pointed out that southeast coast of India receives substantial amount of rainfall during the northeast monsoon season (October to December) during which northeasterly winds prevail there. The lag correlations between the southwest monsoon rainfall and sea level over the west coast and the northeast monsoon rainfall and sea level over the east coast could also be looked into for the purpose of predictability aspect of the sea level along the Indian coast. [Key words: Mean sea level, mean tidal level, El Nino / Southern Oscillation (ENSO), monsoon, southern oscillation index (SOI), sea surface temperature, sea level, tidal level ] Introduction Interannual variations of mean sea level (MSL) are very important in some coastal regions of the world. Singh et al. 1,2 have documented the interannual modes of MSL variation along the Bangladesh coast which is highly vulnerable to the impacts of sea level rise. As a matter of fact, the interannual variations dominate the long term trends there. The authors have also shown that the El Niño-Southern Oscillation (ENSO) induced variation is an important component of sea level variability along the Bangladesh coast. Keeping * Fax: +91-11-24699216 Phone: +91-11-24635667 in view the world-wide impacts of ENSO 3-5, it becomes pertinent to investigate the influence of ENSO on the sea level variability along the Indian coast. Singh et al. 6,7 have shown that ENSO has significant impacts on SST and cyclogenesis in the Bay of Bengal. Similarly, the association of ENSO with the Asian summer monsoon is also well known 8,9. As interannual variations of MSL are closely linked to the SST and rainfall variations, it is natural to have linkages with the ENSO. In the present paper an effort has been made to examine the relationships between the ENSO (Southern Oscillation Index) and the MSL along the west and east coasts of India. These diagnostic and prognostic

88 INDIAN J. MAR. SCI., VOL. 35, NO. 2, JUNE 2006 relationships provide useful indications of interannual variations of MSL along the Indian coast. The weather and climate of South Asian region is significantly influenced by the monsoons. The southwest monsoon season from June to September produces major part of the annual rainfall received by the Indian subcontinent. In a recent study the author has found that about 50% of the observed rising trends in sea level along the Bangladesh coast was monsoon induced 10. In any vulnerability assessment of the South Asian coastal region to the sea level rise phenomenon it is pertinent to investigate the relationship between the monsoon rainfall and sea level along the coastal regions of this area. Asian summer monsoon possesses large interannual and other variations of higher time scales 11-13. There are some studies on the sea level variability in relation to the monsoon rainfall 10,14,15 but there is a need to investigate the direct linkages between the interannual variabilities of monsoon rainfall and the MSL. Materials and Methods The sources of data utilized in this paper are: rainfall data published in Mausam (published by the India Meteorological Department, Survey of India), Permanent Service of Mean Sea Level (PSMSL), U.K and Sea Level Centre University of Hawaii, U.S.A 16 (monthly mean sea level data). Rainfall data of the meteorological subdivisions of Konkan and Goa; Kerala and coastal Andhra Pradesh have been utilized for the study of relationships between the rainfall of above subdivisions with the mean tidal levels at Mumbai (Bombay), Kochi (Cochin) and Visakhapatnam respectively. Figure 1 depicts the map showing the study area and locations of stations. Percentage departures from the normal rainfall for each monsoon month, i.e. June, July, August and September as well as seasonal rainfall departures for the southwest monsoon (June to Sept.) have been correlated with the corresponding MSL. The sources of data on Southern Oscillation Index (SOI) are Climate Prediction Centre, Washington, D.C. U.S.A. and the Bureau of Meteorology, Australia (http://www.bom.gov.au/climate/current/soihtml. shtml). The correlation coefficients (CCs) between the monthly SOI and the mean tidal level (MTL) at Mumbai, Kochi and Visakhapatnam have been computed for each month from January to December. Standardized anomalies of monthly MTL have been computed from the formula: Standardized MTL = anomaly MTL - MTL Standard deviation of for the total period MTL where MTL = monthly MTL for a particular year and MTL = mean MTL for that month for the total period. The results have been presented for those cases only where good relations are found. Results and Discussion The correlation coefficients (CCs) between SOI and MTL for January is highest for Kochi (+0.363) followed by those for Visakhapatnam (+0.358) and Mumbai (+0.217) (Table 1). Keeping in view the Fig. 1 The map showing the locations of stations. Table 1 Zero-lag correlation coefficients between mean tidal level (MTL) and southern oscillation index (SOI) Months Station (1937-1991) Mumbai Kochi Visakhapatnam January February March April May June July August September October November December 0.217 0.154 0.250.0.127 0.027-0.046 0.014 0.007 0.248-0.034-0.072 0.109 0.363 0.113 0.147 0.278-0.019-0.026 0.057 0.111 0.385-0.072 0.169 0.272 0.358 0.221 0.122 0.002 0.532 0.046 0.041 0.173 0.321 0.552 0.536 0.169

SINGH: SEA LEVEL CHANGES 89 large degrees of freedom these CCs can not be overlooked. As a matter of fact all these CCs are statistically significant (at 95% level). The magnitudes of CCs decrease during February but the positive correlations between SOI and MSL at all the three stations indicate that during the La Niña conditions (+ve SOI) higher sea levels and during the El Niño conditions (-ve SOI) lower sea levels are expected along the Indian coast during the winter season (especially during January). For Mumbai the other worth mentioning CCs are for March (+0.250) and September (+0.248). For Kochi good correlation was found between the SOI and MTL for September (+0.385). There is a striking difference between the ENSO-sea level relationships for west and east coasts of India. High positive CCs were found between SOI and MTL at Visakhapatnam (Fig. 2) for the intense tropical cyclone period (i.e. May, October and November). The CCs are +0.532, +0.552 and +0.536 respectively. These results show the significant impact of ENSO conditions on the sea level along the east coast of India. The Fig. 2 Standardized anomalies of mean tidal level (MTL) alongwith concurrent southern oscillation index (SOI) during May (A), October (B) and November (C). correlation between SOI and MTL at Visakhapatnam for September is also good (+0.321). Thus good concurrent correlations exist between the Southern Oscillation Index and the MSL along the east coast of India during the intense cyclone period of the year. During the cold phase of ENSO, MSL along the east coast of India is generally higher enhancing the hazardous potential of the Bay of Bengal cyclones. The sea level along the east coast is also higher in the end phase of the southwest monsoon (i.e. September) and the beginning of the winter (January) during the La Niña epochs. The results have shown that during the El Niño epochs lower MSL is expected over the east coast of 7-9, 17,18 India during the cyclone period. Recent studies have established that the frequency of tropical cyclones is generally lower over the Bay of Bengal during the cyclonic periods of El Niño epochs. Present results combined with above findings show that the vulnerability of east coast of India to the inundation due to storm surges is considerably less during the El Niño epochs. The inundation risk in the end phase of southwest monsoon season is also lesser during the El Niño as the CC between SOI and MTL for Kochi is +ve during September. This is certainly a positive aspect of El Niño for the South Asia region. During the La Niña, however, better preparedness is required to combat sea level associated disasters along east coast of India. West coast of India, however, seems to be less responsive to the ENSO conditions. To depict the interannual variability of MSL along the east coast of India in relation to the ENSO (Fig. 2) the MTL time-series along with the SOI for intense cyclone months have been presented. A cursory look at these figures would provide useful indications of the variabilities of MTL and SOI which are generally in phase. Therefore, in addition to the long term trends of MSL the interannual variations are also very important for the Indian coast (especially for the east coast of India). These variations are required to be considered when we prepare ourselves for the impacts of sea level rise phenomenon as the magnitude of year-to-year variability is quite significant. The La-Nina years would require better preparedness as compared to El-Nino years due to higher sea levels. Lag relationships between ENSO and sea level The prognostic relationships between the Southern Oscillation Index (SOI) and MTL have been presented in Table 2. Again, the relationships are

90 INDIAN J. MAR. SCI., VOL. 35, NO. 2, JUNE 2006 better for the east coast. The striking feature is that during the cyclone and flooding periods the SOI shows very high correlations with future sea level variations. Table 2 reveals that in the postmonsoon season (October to December) high positive correlations exist between the SOI of preceding month and the sea level of a particular postmonsoon month. For instance, the CC between the SOI of September and MTL of October is +0.64 which is based on SOI and MTL data of the 55 years period (1937-1991). Thus during the positive phases of Southern Oscillation (i.e. La Niña conditions) there is a tendency for the enhanced sea level along the east coast of India during the postmonsoon cyclone season. During May also, which is the main cyclone month of premonsoon season, the CC between the SOI of preceding month (i.e. April) and MTL of May is significant (+0.36). During the second half of the southwest monsoon season (i.e. August-September) the SOI of preceding months are positively correlated to the MTL. Therefore, during the intense cyclonic periods i.e. May, October and November and during the second half of the southwest monsoon season, which are important periods for the sea level associated disasters for the east coast of India, the SOIs can give good indications of future sea levels (Fig. 3). This is an important observation, which can be utilized in the disaster management programmes aimed at mitigating the impacts of the natural disasters associated with sea level. As shown by Table 2, over the west coast of India the SOI can give good indications of MTL in the beginning of the year, i.e. January-March but during the southwest monsoon season or in other seasons SOI-sea level relationships are not good. It would be interesting to investigate as to why ENSO has a selective impact on the sea level variabilities along the east and west coasts of India. Relationships between seasonal rainfall and seasonal MTL Time-series of seasonal rainfall departures alongwith corresponding MTL are presented in Fig. 4. The values of correlation coefficients between these two parameters are presented in Table 3. There exists a significant correlation between the southwest monsoon rainfall over Konkan and Goa and the seasonal MSL at Mumbai (Fig. 4A). Both the timeseries oscillate in almost similar manner. Notable peaks in the rainfall time-series are observed during the years 1964, 1970, 1983 and 1988. In MTL time Table 2 Lag correlation coefficients between the Southern Oscillation Index and Mean Tidal Level (SOI vs MTL of succeeding month) Months (1937-1991) Station Mumbai Kochi Visakhapatnam January 0.216 0.160 0.436 February March April May June July August September October November December 0.407 0.182-0.029 0.112-0.088 0.034 0.287-0.067-0.229 0.186 0.273 0.213 0.091-0.043 0.171-0.067 0.175 0.338-0.159-0.087 0.415 0.409 0.201 0.036 0.355 0.355-0.044 0.323 0.323 0.641 0.478 0.374 0.375 Fig. 3 Lag relationships between SOI and MTL at Visakhapatnam April SOI vs May MTL (A), September SOI vs October MTL (B) and October SOI vs November MTL (C).

SINGH: SEA LEVEL CHANGES 91 Table 3 Correlations between mean tidal level ( MTL ) at different stations and the percentage departures of monsoon rainfall over respective meteorological subdivisions Period Station June July August September June to Sept (seasonal) Mumbai 0.09 0.34 0.24 0.48 0.47 Kochi 0.56 0.56 0.45 0.59 0.48 Visakhapatnam 0.11 0.0 0.19 0.04 0.03 Fig. 4 Variabilities of southwest monsoon rainfall and average seasonal MTL at Mumbai (A), Kochi (B) and Visakhapatnam (C). series also sea level maxima are observed during 1970, 1983 and 1988. During 1964, however, due to non availability of MTL data it is not possible to make a comparison. This is reflected in Fig 4A as a break in MTL time-series. During the deficient rainfall years 1966, 1968, 1972, 1979 and 1987 there is a general tendency for the reduced sea levels. Table 3 provides a quantitative footing for the phased oscillations observed in the rainfall and MTL timeseries as revealed by Fig. 4A. The correlation coefficient between the monsoon rainfall over Konkan and Goa and MTL at Mumbai is +0.47 which is significant at 99% level. Thus the interannual variations in the monsoon MSL at Mumbai are intimately linked to the interannual variations of the monsoon rainfall amount. Figure 4B shows more or less similar relationship between Kerala rainfall and Kochi MTL as observed between Konkan and Goa rainfall and Mumbai rainfall. The data reveals the close relationships between rainfall and sea level along the west coast of India (Fig. 4A,B). The CC between Kerala rainfall and Kochi MTL during the southwest monsoon is +0.48 (Table 3) which is again significant at 99% level. It is worth investigating the lag relationships between the rainfall and sea level for prognostic utility of such relationships. The relationship between the southwest monsoon rainfall and the sea level over the east coast of India (i.e. at Visakhapatnam) is not good (Fig. 4C). The CC between coastal Andhra Pradesh rainfall and MTL at Visakhapatnam is only +0.03 showing non-existent impact of southwest monsoon rainfall over the sea level along the east coast of India. This may be due to the fact that stronger monsoon produces much more rainfall over the west coast as compared to the east coast. Further, the impacts of monsoonal southwesterly winds will also be different over the east coast. Conclusion The results have shown that 1 There exist high positive correlations between the Southern Oscillation Index and the MSL along the east coast of India during the intense cyclone period of the year (i.e. May, October and November). The MSL is considerably higher/lower during the cyclonic period of La Niña / El Niño epochs. Thus the hazardous potential of La Niña tropical cyclones is much higher as compared to those forming during the El Niño epochs.the SOIs of preceding months can provide predictive indications of MSL along the east coast during intense cyclone months. 2 The MSL is higher over the west and east coasts of India during the ending phase of La Niña southwest monsoons. 3 ENSO has generally lesser impact on the sea level variability over the west coast of India as compared with that over the east coast of India. 4 Significant concurrent correlations exist between the seasonal monsoon rainfall and MSL along the west coast of India during southwest monsoon. 5 The correlations between the monsoon rainfall and MSL are poor over the east coast of India. 6 Over the east coast of India the relationship between the northeast monsoon rainfall and MSL needs further study.

92 INDIAN J. MAR. SCI., VOL. 35, NO. 2, JUNE 2006 Acknowledgement The author is thankful to the Director General of Meteorology, India Meteorological Department, New Delhi for according permission to publish this paper. References 1 Singh O P, Khan T M A & Rahman M S, The vulnerability assessment of SAARC coastal region due to sea level rise: Bangladesh case. SMRC Report No. 3 (SAARC Meteorological Research Centre, Dhaka, Bangladesh) 2000, pp.111. 2 Singh O P, Khan T M A & Rahman M S, Sea level changes along Bangladesh coast in relation to the Southern Oscillation phenomenon, Mar Geodesy, 24 (2001) 65-72. 3 Shukla J, Interannual variability of monsoon (John Wiley & Sons, New York) 1987, pp. 632. 4 Chang C P & Krishnamurti T N, Monsoon meteorology, (Oxford University Press, Oxford) 1987, pp. 544. 5 Shukla J & Paolino D A, The Southern Oscillation and long range forecasting of summer monsoon rainfall over India, Mon. Weather Rev., 111(1983)1830-1837. 6 Singh O P, Khan T M A, Rahman M S & Salahuddin M, Summer monsoon rainfall over Bangladesh in relation to multivariate ENSO Index, Mausam, 51(2000) 255-260. 7 Singh O P, Khan T M A & Rahman M S, Changes in the frequency of tropical cyclones over the North Indian Ocean, Meteorol. Atmos. Phys., 75 (2000) 11-20. 8 Thapliyal V, Long range prediction of summer monsoon rainfall over India: Evolution and development of new models, Mausam, 41 (1990) 339-346. 9 Singh O P, Khan T M A & Rahman M S, Tropical cyclone frequency over the North Indian Ocean in relation to Southern Oscillation phenomenon, Mausam, 52 (2000) 511-514. 10 Singh O P, Cause effect relationships between sea surface temperature, precipitation and sea level along the Bangladesh Coast, Theor. Appl. Climatol., 68 (2001) 233-243. 11 Rao Y P, Southwest monsoon, Met. Monograph, Synoptic Meteorology, No,1/1976 (India Meteorological Department, New Delhi) 1976, pp. 376. 12 Singh O P, Variability of wind stress and wind stress curl over the north Indian Ocean during pre-monsoon and monsoon seasons of 1987 and 1988, Mahasagar (Bull. Natn. Inst. Oceanogr.), 26 (1993) 9-16. 13 Singh O P, Multivariate ENSO index and Indian monsoon rainfall: relationships on monthly and subdivisional scales, Meteorol. Atmos. Phys., 78 (2001) 1-9. 14 Shetye S R, The movement and implications of Ganges- Brahmputra run off on entering the Bay of Bengal, Curr. Sci., 64 (1993) 32-38. 15 Shankar D & Shetye S R, Are interdecadal sea level changes along the Indian coast influenced by variability of monsoon rainfall?, J. Geophys Res., 104(C11), (1999) 26031-26042. 16 Caldwell P, Sea level data processing on IBM-PC compatible computers (Year 2000 compliant) (University of Hawaii/NOAA, HI, USA, JMAR Contribution No. 98, 319) 1998, pp. 72. 17 Singh O P & Rout R K, Frequency of cyclonic disturbances over the North Indian Ocean during ENSO years in Proceeding of TROPMET-99, (Indian Meteorological Society, Chennai, India) 1999, pp. 297-301. 18 Singh O P & Khan T M A, Changes in the frequencies of cyclonic storms and depressions over the Bay of Bengal and the Arabian Sea. SMRC Report No. 2 (SAARC Meteorological Research Centre, Dhaka, Bangladesh) 1999, pp. 121.