NOTES AND CORRESPONDENCE. Variations of the SO Relationship with Summer and Winter Monsoon Rainfall over India:

Similar documents
An ocean-atmosphere index for ENSO and its relation to Indian monsoon rainfall

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

Relationship between ail-lndia summer monsoon rainfall and southern oscillation/eastern equatorial Pacific sea surface temperature

Effect of sea surface temperature on monsoon rainfall in a coastal region of India

INTRA-SEASONAL, INTER-ANNUAL AND DECADAL SCALE VARIABILITY IN SUMMER MONSOON RAINFALL OVER INDIA

Decadal changes in the relationship between Indian and Australian summer monsoons

Variation in the relationship of the Indian summer monsoon with global factors

LONG- TERM CHANGE IN PRE- MONSOON THERMAL INDEX OVER CENTRAL INDIAN REGION AND SOUTH WEST MONSOON VARIABILITY

Effect of late 1970 s Climate Shift on Interannual Variability of Indian Summer Monsoon Associated with TBO

Interannual variation of northeast monsoon rainfall over southern peninsular India

El Niño / Southern Oscillation (ENSO) and inter-annual climate variability

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

Biennial Oscillation of Tropical Ocean-Atmosphere System Associated with Indian Summer Monsoon

INDIA METEOROLOGICAL DEPARTMENT (MINISTRY OF EARTH SCIENCES) SOUTHWEST MONSOON-2010 END OF SEASON REPORT

The Child. Mean Annual SST Cycle 11/19/12

Understanding El Nino-Monsoon teleconnections

Global Impacts of El Niño on Agriculture

- terminology. Further Reading: Chapter 07 of the text book. Outline. - characteristics of ENSO. -impacts

Investigation of Common Mode of Variability in Boreal Summer Intraseasonal Oscillation and Tropospheric Biennial Oscillation

Influence of El Nino Southern Oscillation and Indian Ocean Dipole in biennial oscillation of Indian summer monsoon

Subsurface Ocean Indices for Central-Pacific and Eastern-Pacific Types of ENSO

Local vs. Remote SST Forcing in Shaping the Asian-Australian Monsoon Variability

The impact of the El Niño Southern Oscillation. on Rainfall Variability in Timor-Leste

ENSO RELATIONSHIP TO THE RAINFALL OF SRI LANKA

Changes in the in-phase relationship between the Indian and subsequent Australian summer monsoons during the past five decades

Some characteristics of low pressure systems and summer monsoon rainfall over Orissa

Variability in the tropical oceans - Monitoring and prediction of El Niño and La Niña -

APPENDIX B NOAA DROUGHT ANALYSIS 29 OCTOBER 2007

ENSO Wrap-Up. Current state of the Pacific and Indian Ocean

Unraveling The Mystery of Indian Monsoon Failure During El Niño

Role of Mid-Latitude Westerly Trough Index at 500 h Pa and its Association with Rainfall in Summer Monsoon over Indian Region

Appendix E Mangaone Stream at Ratanui Hydrological Gauging Station Influence of IPO on Stream Flow

Overview. Learning Goals. Prior Knowledge. UWHS Climate Science. Grade Level Time Required Part I 30 minutes Part II 2+ hours Part III

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 8 March 2010

NOTES AND CORRESPONDENCE. Timing of El Niño Related Warming and Indian Summer Monsoon Rainfall

Trade winds How do they affect the tropical oceans? 10/9/13. Take away concepts and ideas. El Niño - Southern Oscillation (ENSO)

Lecture 20. Active-weak spells and breaks in the monsoon: Part 1

Rajast. Earth System. Press Release. Subject: forecast. country as. Normal. Regions Rainfall (mm) LPA -29% -61% -34% -4% -9%

Lecture 14. Heat lows and the TCZ

Lecture 24. El Nino Southern Oscillation (ENSO) Part 1

Long period waves in the coastal regions of north Indian Ocean

The General Circulation and El Niño. Dr. Christopher M. Godfrey University of North Carolina at Asheville

General Introduction to Climate Drivers and BoM Climate Services Products

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 4 September 2012

Tropical Pacific Ocean remains on track for El Niño in 2014


Mechanistic links between the tropical Atlantic and the Indian monsoon in the absence of El Nino Southern Oscillation events

The Tropospheric Biennial Oscillation and Asian Australian Monsoon Rainfall

El Niño climate disturbance in northern Madagascar and in the Comoros

Analysis of 2012 Indian Ocean Dipole Behavior

What happened to the South Coast El Niño , squid catches? By M J Roberts Sea Fisheries Research Institute, Cape Town

Indian Ocean dynamics and interannual variability associated with the tropospheric biennial oscillation (TBO)

Impacts of intraseasonal oscillation on the onset and interannual variation of the Indian summer monsoon

Long-term warming trend over the Indian Ocean

Subsurface Ocean Temperature Indices for Central-Pacific and Eastern-Pacific Types of El Niño and La Niña Events

SERIES ARTICLE The Indian Monsoon

Your web browser (Safari 7) is out of date. For more security, comfort and the best experience on this site: Update your browser Ignore

Changes of The Hadley Circulation Since 1950

Onset, active and break periods of the Australian monsoon

Influence of enhanced convection over Southeast Asia on blocking ridge and associated surface high over Siberia in winter

NORTHEAST MONSOON RAINFALL VARIABILITY OVER SOUTH PENINSULAR INDIA VIS-À-VIS THE INDIAN OCEAN DIPOLE MODE

GEOS 201 Lab 13 Climate of Change InTeGrate Module Case studies 2.2 & 3.1

Lecture 13 El Niño/La Niña Ocean-Atmosphere Interaction. Idealized 3-Cell Model of Wind Patterns on a Rotating Earth. Previous Lecture!

OCN 201 Lab Fall 2009 OCN 201. Lab 9 - El Niño

Interannual variability of surface air-temperature over India: impact of ENSO and Indian Ocean Sea surface temperature

Currents. History. Pressure Cells 3/13/17. El Nino Southern Oscillation ENSO. Teleconnections and Oscillations. Neutral Conditions

Variability in Summer Monsoon Rainfall over Pune, a Leeward Side Station of Western Ghats in India

The Relationship between ENSO/IOD and Rainfall Extremes in Australia

SST 1. ITCZ ITCZ. (Hastenrath and Heller 1977; Folland et al. 1986; Nobre and Shukla 1996; Xie and Carton 2004). 2. MIROC. (Namias 1972).

Weather drivers in South Australia

Forecasting of Lower Colorado River Basin Streamflow using Pacific Ocean Sea Surface Temperatures and ENSO

Module 3, Investigation 1: Briefing 1 What are the effects of ENSO?

Lecture 7. The Indian monsoon: is it a gigantic land-sea breeze?

Surface chlorophyll bloom in the Southeastern Tropical Indian Ocean during boreal summer-fall as reveal in the MODIS dataset

ENSO Update Eastern Region. Michelle L Heureux Climate Prediction Center / NCEP/ NOAA 29 November 2016

GEOS 513 ENSO: Past, Present and Future

United States Streamflow Probabilities and Uncertainties based on Anticipated El Niño, Water Year 2003

3. Climatic Variability. El Niño and the Southern Oscillation Madden-Julian Oscillation Equatorial waves

Global Learning And Evidence Exchange (GLEE) Climate Smart Agriculture: Africa

Intermountain West Climate Summary

The South Asian Monsoon and the Tropospheric Biennial Oscillation

Government of India Earth System Science Organization Ministry of Earth Sciences India

ENSO: El Niño Southern Oscillation

Indian Ocean warming its extent, and impact on the monsoon and marine productivity

Climate briefing. Wellington region, February Alex Pezza and Mike Thompson Environmental Science Department

Processes that Determine the Quasi-Biennial and Lower-Frequency Variability of the South Asian Monsoon

The Great Paradox of Indian Monsoon Failure (Unraveling The Mystery of Indian Monsoon Failure During El Niño)

N.V. Nanda Kumar, A. Nagarjuna and D.C. Reddy

Influences of ENSO and SST variations on the interannual variability of rainfall amounts in southern Africa

Goal: Describe the principal features and characteristics of monsoons

Traditional El Niño and El Niño Modoki Revisited: Is El Niño Modoki Linearly Independent of Traditional El Niño?

Weakening of the Winter Monsoon and Abrupt Increase of Winter Rainfalls over Northern Taiwan and Southern China in the Early 1980s

Factors controlling January April rainfall over southern India and Sri Lanka

Multifarious anchovy and sardine regimes in the Humboldt Current System during the last 150 years

Impact of ENSO and the Indian Ocean Dipole on the north-east monsoon rainfall of Tamil Nadu State in India

The Asian Australian Monsoon and El Niño Southern Oscillation in the NCAR Climate System Model*

Chart Discussion: Fri-17-Aug-2018 (Harvey Stern) Combining Forecasts (Apr 13th to Aug 15th)

Evaluation of monsoon seasonality and the tropospheric biennial oscillation transitions in the CMIP models

REMINDERS: UPCOMING REVIEW SESSIONS: - Thursday, Feb 27, 6:30-8:00pm in HSS 1330

Lecture 29. The El-Niño Southern Oscillation (ENSO) La Niña = the girl; corresponds to the opposite climate situation

Transcription:

3486 JOURNAL OF CLIMATE VOLUME 12 NOTES AND CORRESPONDENCE Variations of the SO Relationship with Summer and Winter Monsoon Rainfall over India: 1872 1993 G. NAGESWARA RAO Department of Meteorology and Oceanography, Andhra University, Visakhapatnam, India 19 October 1998 and 15 April 1999 ABSTRACT The lag correlations of the monthly and seasonal pressures at Darwin with the rainfall over India during summer (June September) and winter (October December) monsoons and their variations over 29 meteorological subdivisions in India are examined by using long time data for 122 yr (1872 1993). It is found that the summer monsoon rainfall over India has significant (at 5% level) positive correlation with the Darwin pressures during the previous June August period, and significant negative correlation with the pressures during the concurrent March May period and with the seasonal pressure tendency from winter to spring (March May minus December February). Of these, the correlations with the concurrent May ( 0.36) and the winter to spring seasonal pressure tendency ( 0.30) are strong. Similarly, the all-india rainfall during winter monsoon is found to have significant negative correlation with the Darwin pressures during the concurrent July and August. In this case, the correlation with the concurrent July pressures is strong ( 0.21). During the winter monsoon season, southern peninsular India receives dominant rainfall and this rainfall is found to have only a weak positive correlation (0.17) with the concurrent September pressures at Darwin. The consistency of these relations during the period of study is examined by evaluating the 30-yr sliding window correlation coefficients. The anomaly rainfall patterns of the summer and winter monsoons over India during the years of the low and high values of the corresponding Southern Oscillation index are further examined. 1. Introduction The importance of the Indian summer monsoon (June September) rainfall, on which the country s agriculture, power generation, and industrial production heavily depend, is well known. The year to year fluctuations in Indian rice yield is largely determined by the success or failure of the summer monsoon. During this season, many parts of the country receive 70% 90% of their annual rainfall. The winter or northeast monsoon rainfall, which occurs mainly from October to December, is dominant over southern peninsular India, consisting of the six meteorological subdivisions, coastal Andhra Pradesh, Rayalaseema, south interior Karnataka, coastal Karnataka, Tamilnadu, and Kerala (Fig. 1). During this season, India receives about 11% of its annual rainfall, while many of the above subdivisions receive 17% 49% of their annual rainfall. Major agricultural operations in this southern part of the country are normally undertaken during this season. The winter monsoon rainfall is of considerable economic importance Corresponding author address: Dr. G. Nageswara Rao, Atmospheric Science Centre, Department of Meteorology and Oceanography, Andhara University, Visakhapatnam 530 003, India. for this region, which constitutes about 15% of the Indian subcontinent. The Indian summer monsoon rainfall is known to have considerable year to year variations (for reviews see, e.g., Shukla 1987; Mooley and Shukla 1987; Hastenrath 1991). A number of studies have been made to examine the association of the Indian summer monsoon rainfall with the Southern Oscillation (SO), which designates a seesaw in the sea level pressures between the Pacific and the Indian Ocean from Africa to Australia (Walker 1924; Walker and Bliss 1932; Pant and Parthasarathy 1981; Shukla and Paolino 1983; Bhalme et al. 1983; Rasmusson and Carpenter 1983; Mooley and Parthasarathy 1983, 1984; Parthasarathy and Pant 1985; Elliot and Angell 1987; Mooley and Munot 1993). The variations in the SO are measured by means of indices. Of the several indices, the pressure difference between Tahiti (17 33 S, 149 31 W) and Darwin (12 20 S, 130 52 E) representing the abovementioned two centers of action, is considered to be a better index of the SO (Chen 1982). As a long time record of Tahiti was not available, its pressure data have been extended back to 1876 (Roplelewski and Jones 1987). Several authors (Shukla and Paolino 1983; Elliot and Angell 1987; Mooley and Munot 1993) considered the individual pressures of Darwin as a measure of the Southern Os- 1999 American Meteorological Society

DECEMBER 1999 NOTES AND CORRESPONDENCE 3487 TABLE 1. Statistical details of all-india summer and winter monsoon rainfall (cm) during 1872 1993. Summer monsoon Winter monsoon Mean Standard deviation 85.2 8.4 12.1 3.4 Composite mean during the deficient years 71.6 7.2 Composite mean during the excess years 96.9 17.8 Composite mean during the 88.7 14.3 years of Darwin low pressure Composite mean during the years of Darwin high pressure ( 3%) 80.3 ( 6%) ( 21%) 11.1 ( 6%) FIG. 1. Meteorological subdivisions of India with state boundaries (solid line). The dotted lines divide states into subdivisions. Hatched hilly subdivisions are not considered in the study. cillation index (SOI). Trenberth (1991) stated that because Darwin is at one center of the SO, changes in Darwin sea level pressure can be used as an index of the SO. Further studies of Elliot and Angell (1987, 1988) and Parthasarathy et al. (1988) indicated that Darwin mean sea level (MSL) pressure is better related with Indian summer monsoon rainfall than Tahiti or Tahiti minus Darwin MSL pressures. There are a few studies on the relationship between the SO and Indian summer monsoon rainfall on regional scales. Parthasarathy et al. (1993) examined the SO relationship with summer monsoon rainfall in 29 meteorological subdivisions in India for the period 1951 80. The author (Nageswara Rao 1998) also examined the association of the summer monsoon rainfall in one of the central Indian river basins, Godavari with SO and its spatial variations within the basin. The studies pertaining to the winter monsoon season are very few in the literature, although this season s rainfall is quite important for southern peninsular India. Rao (1963) and Indian Meteorological Department (1973) provide a detailed description of the Indian northeast monsoon. Dhar and Rakhecha (1983) examined the association between the southwest and northeast monsoon rainfall over Tamilnadu for the 100-yr period (1877 1976) and found that the southwest monsoon rainfall is negatively correlated with that of the northeast monsoon. Recently, Singh (1995) studied the influence of Bay of Bengal on winter monsoon rainfall in two contrasting winter monsoon years 1987 and 1988. Similarly, Raj (1996) studied the thermodynamic structure of the atmosphere over coastal Tamilnadu during the northeast monsoon season. In all these studies, the authors mainly examined the characteristics of the northeast monsoon. In the present study, an attempt has been made to examine the subdivisional and time variations of the SO relationship with the rainfall over India during summer as well as winter monsoon seasons, by using long time data for the 122-yr period from 1872 to 1993. 2. Data The monthly and seasonal rainfall series for all India and 29 meteorological subdivisions during 1872 1993, as estimated by Parthasarathy et al. (1995) on the basis of 306 rain gauge stations over India, are used in the present study. As indicated by the earlier studies, the Darwin MSL pressure is considered as a measure of SO to study its relationship with the summer and winter monsoon rainfall over India. For this, the Darwin monthly MSL pressure data for 1872 1993 is taken from a publication of the Bureau of Meteorology (1987) and its later issues. The seasonal anomalies of SOI are then computed for the seasons, December (previous calendar year) February (DJF), March May (MAM), June August (JJA), and September November (SON) for each of the 122 yr. 3. Summer and winter monsoon rainfall over India and their interannual variations The statistical details of the summer and winter monsoon rainfall over India during 1872 1993 are presented in Table 1. India receives an average rainfall of 85.2 cm during the summer monsoon season (June September) and 12.1 cm during the winter monsoon season (October December), which are respectively 78% and 11% of the annual rainfall. The coefficient of variability, CV (std dev/mean)100 of the summer monsoon rainfall, is found to be 10%, while for the winter monsoon rainfall it is 28%. This shows that the winter monsoon rainfall over India is more variable than the summer monsoon rainfall. The rainfall statistics of southern pen-

3488 JOURNAL OF CLIMATE VOLUME 12 FIG. 2. Subdivisional variation of the mean summer monsoon rainfall (cm) in India during (a) 1872 1993 and (b) its correlation with Darwin CMAY pressures. Same as (a) but for the (c) winter monsoon rainfall and (d) its correlation with Darwin CJUL pressures. In (a) and (c), hatched subdivisions receive more rainfall than the corresponding all-india mean. In (b) and (d), subdivisions in which the correlation coefficient is significant at 5% level are hatched. insular India, over which the winter monsoon rainfall is dominant, are also evaluated. Over this region, the winter monsoon rainfall contributes about 28% of its annual rainfall. The mean summer and winter monsoon rainfall in each of the 29 subdivisions in India for the 122-yr period of study are also evaluated and presented in Figs. 2a and 2c. The subdivisions that receive more rainfall than the all-india mean rainfall are hatched. The

DECEMBER 1999 NOTES AND CORRESPONDENCE 3489 TABLE 2. Correlation coefficients between winter and summer monsoon rainfall over India during 1872 1993. AIWMR SPIWMR TNWMR AISMR SPISMR TNSMR 0.26* 0.05 0.18* * Significant at 5% level. 0.18* 0.14 0.27* 0.18* 0.08 0.24* summer monsoon rainfall is, in general, low in the northwest and southern peninsular India and high in the remaining subdivisions in the northeast and central India and along the west coast (Fig. 2a). It is the lowest (25.7 cm) in western Rajastan and highest (285.8 cm) in coastal Karnataka. During the winter monsoon season (Fig. 2c), the subdivisions in southern peninsular India and along the east coast and some subdivisions in the northeast India receive more rainfall than the corresponding all-india mean rainfall. Of these, the subdivisions in southern peninsular India receive relatively more rainfall. The winter monsoon rainfall is the highest in Kerala (47.6 cm) and lowest (0.95 cm) in western Rajastan. It is also high in Tamilnadu (45.3 cm). Of all the meteorological subdivisions in India, Tamilnadu has the unique feature that the rainfall received during summer monsoon (30.9 cm) is less than the rainfall received during winter monsoon (45.3 cm). In an attempt to foreshadow the winter monsoon rainfall over Tamilnadu by knowing the performance of the summer monsoon rainfall over the same region, Dhar and Rakhecha (1983) found that the summer and winter monsoon rainfall over Tamilnadu are inversely correlated (correlation coefficient, CC 0.38) with each other during the period 1877 1976. To investigate if there is any such relation between the summer and winter monsoon rainfall over India and over southern peninsular India, the correlation coefficients among them during 1872 1993 are evaluated and presented in Table 2. For comparison, similar correlation coefficients for Tamilnadu are also evaluated and presented in the same table. The all-india winter monsoon rainfall (AIWMR) is found to be positively correlated (Table 2) with the summer monsoon rainfall over India (AISMR), southern peninsular India (SPISMR), and Tamilnadu (TNSMR). Although all these correlations are significant at 5% level, they are weak. The winter monsoon rainfall over southern peninsular India (SPIWMR) has no significant correlation with the summer monsoon rainfall over any of the three regions (Table 2), while in the case of Tamilnadu, the winter monsoon rainfall (TNWMR) is inversely related with the summer monsoon rainfall over the above three regions. In this case also, the correlations are significant at 5% level but are weak. It is to be noted that the correlation between the summer and winter monsoon rainfall over Tamilnadu during the period 1872 1993 (CC 0.24) is smaller than that during 1877 1976 (CC 0.38) as obtained by Dhar and Rakhecha (1983). With the data used in the present study during the period 1877 1976, the correlation coefficient is found to be 0.33. The little variation in the two CCs is due to the difference in the datasets used in the two studies. However, the decrease of the correlation coefficient from the period 1877 1976 to the period 1872 1993 is interesting and shows the variation of this relationship in time. The normalized anomaly (X i X)/ (where X is the mean and is the standard deviation) of the summer and winter monsoon rainfall over India has been evaluated for each of the 122 yr and presented in Figs. 3 and 4, respectively. By considering the years with the summer monsoon rainfall anomaly less than 1.0 as the deficient summer monsoon years and the years with more than 1.0 as excess summer monsoon years, there are 22 deficient summer monsoon years (1873, 1877, 1899, 1901, 1904, 1905, 1911, 1918, 1920, 1928, 1941, 1951, 1965, 1966, 1968, 1972, 1974, 1979, 1982, 1985, 1986, and 1987) and 17 excess summer monsoon years (1874, 1878, 1892, 1893, 1894, 1916, 1917, 1933, 1942, 1947, 1956, 1959, 1961, 1970, 1975, 1983, and 1988) during 1872 1993. Similarly, there are 21 deficient winter monsoon years (1873, 1875, 1876, 1891, 1896, 1899, 1900, 1905, 1907, 1908, 1909, 1914, 1918, 1920, 1926, 1935, 1942, 1965, 1984, 1988, and 1989) and 18 excess winter monsoon years (1877, 1885, 1886, 1893, 1894, 1903, 1916, 1917, 1928, 1930, 1931, 1946, 1955, 1956, 1959, 1973, 1977, and 1987) during the 122-yr period. The composite mean rainfall over India for the deficient and excess years of the summer and winter monsoons are evaluated and presented in Table 1. The composite mean summer monsoon rainfall over India during the deficient and excess years varied from 19% to 12% of their corresponding mean. Similarly the composite winter monsoon rainfall varied from 40% to 48%. Over south peninsular India, the composite winter monsoon rainfall varied from 27% to 24%. These values also show that the winter monsoon rainfall is more variable than the summer monsoon rainfall. 4. Relationship of the summer and winter monsoon rainfall with Darwin MSL pressures The lag correlation coefficients of all-india summer monsoon (June September) rainfall with Darwin MSL pressures of the months, starting from the previous June to the concurrent May and during the seasons, previous JJA, previous SON, DJF, concurrent MAM, and the winter to spring seasonal pressure tendency (MAM DJF) are calculated over the period 1872 1993 and presented (significant CCs only) in Table 3. The all-india summer monsoon rainfall has significant (at 5% level) positive correlations with the Darwin MSL pressures during the previous June (PJUN) and during the previous JJA (PJJA). It has significant negative correlations with the pressures during the concurrent months, April and May (CAPR and CMAY), concurrent MAM (CMAM), and with the seasonal pressure tendency (SPT) from winter

3490 JOURNAL OF CLIMATE VOLUME 12 FIG. 3. Normalized anomaly of all-india summer monsoon rainfall (bars) and Darwin CMAY pressures (thin line) during (a) 1872 1993. 30-yr sliding window correlation coefficients of all- India summer monsoon rainfall with (b) Darwin CMAY pressures and with (c) Darwin winter to spring (MAM DJF) pressure tendency. The horizontal line in (b) and (c) represents 5% level of significance. to spring (MAM DJF). Of these, the correlations with the CMAY (CC 0.36) and the winter to spring SPT (CC 0.30) are strong. The normalized anomalies of the Darwin CMAY pressures during 1872 1993 are presented in Fig. 3a, along with the corresponding anomalies of the all-india summer monsoon rainfall. Except in a few years, the anomalies of both series vary inversely. Shukla and Paolino (1983), by using the data during 1901 81 showed that the all-india monsoon rainfall is better related with the Darwin MSL pressure tendency from winter to spring (MAM DJF) than with the seasonal pressures. The data used in the present study during the same period (1901 81) also revealed the same. However, over longer period (1872 1993), the CC with CMAY (CC 0.36) is stronger than with the winter to spring SPT (CC 0.30). This suggests

DECEMBER 1999 NOTES AND CORRESPONDENCE 3491 FIG. 4. (a) Same as Fig. 3a, but for winter monsoon rainfall (bars) and Darwin CJUL pressures. (b) Same as Fig. 3b, but for winter monsoon rainfall with Darwin CJUL pressures. The horizontal line in (b) represents 5% level of significance. the variation of this relationship in time. Therefore, to examine the consistency of these relationships, the 30- yr sliding window CCs of the all-india monsoon rainfall with the CMAY and the winter to spring SPT during the 122-yr period are calculated and presented in Figs. 3b and 3c, respectively. They clearly show that the CC with the CMAY pressures is more consistent than with the winter to spring SPT (MAM DJF). Figure 3c shows that the CC with the SPT during 1953 78 is stronger than with the CMAY pressures (Fig. 3b). However, except in some years during 1916 25, the CC with the SPT is not significant before 1953, whereas the CC with the CMAY pressures is insignificant only in some years during 1908 57. Thus, the CC with CMAY pressures is significant in more number of years than with the SPT and hence the former is more consistent than the latter. Similarly, the lag correlations of all-india winter monsoon rainfall with Darwin MSL pressures of the months, starting from the previous October to the concurrent September and during the seasons previous SON, DJF, concurrent MAM, and concurrent JJA, and the autumn to winter (DJF SON), winter to spring (MAM DJF), and spring to summer (JJA MAM) seasonal

3492 JOURNAL OF CLIMATE VOLUME 12 TABLE 3. Significant (5% level) correlation coefficients of all-india summer and winter monsoon rainfall with Darwin monthly/seasonal pressures during 1872 1993. P shows previous; C indicates concurrent. Summer monsoon Darwin pressure PJUN CAPR CMAY PJJA CMAM CMAM-DJF CC 0.18 0.20 0.36 0.20 0.27 0.30 Winter monsoon Darwin pressure CJUL CAUG CJJA CC 0.21 0.19 0.19 pressure tendencies during 1872 1993, are calculated and presented (significant CCs only) in Table 3. Similar CCs with the winter monsoon rainfall over southern peninsular India are also calculated. The all-india winter monsoon rainfall has significant but weak negative correlations with the Darwin pressures during the concurrent July and August (CJUL and CAUG). In this case, the correlation with the CJUL (CC 0.21) is stronger. The winter monsoon rainfall over southern peninsular India has a still weaker positive correlation (CC 0.17) with the concurrent September (CSEP) pressures only. The normalized anomalies of the Darwin CJUL pressures during the 122-yr period are presented in Fig. 4a, along with those of the all-india winter monsoon rainfall. The consistency of the relationship between all- India winter monsoon rainfall and the Darwin CJUL pressures is also examined by evaluating the 30-yr sliding window CCs during 1872 1993 (Fig. 4b). It shows that this relationship is significant during 1892 1917 and during 1954 71 only and during the remaining periods, it is insignificant. It is to be noted that the summer and winter monsoon rainfall over India have shown the highest correlation with different monthly pressures at Darwin; the summer monsoon rainfall has shown the high correlation with the CMAY pressures and the winter monsoon rainfall with the CJUL pressures. Hence, the summer and winter monsoon rainfall over India are considered to have different SO indices; CMAY Darwin pressures for the summer monsoon rainfall and CJUL Darwin pressures for the winter monsoon rainfall for further analysis. The CCs of the summer monsoon rainfall with the Darwin CMAY pressures and winter monsoon rainfall with the CJUL pressures are evaluated for the 29 meteorological subdivisions in India and presented in Figs. 2b and 2d. The subdivisions with significant (5% level) CCs are hatched. On a subdivisional basis also, the summer monsoon rainfall has negative correlations with the CMAY pressures (Fig. 2b). The CCs vary from 0.05 in Gangetic West Bengal to 0.32 in Marathwada. In the subdivisions in northeast, south, and northwest India, the CCs are insignificant. The CCs in the remaining subdivisions are significant. In the case of winter monsoon rainfall (Fig. 2d), some of the subdivisions have positive but weak CCs with the Darwin CJUL pressures. The CCs varied from 0.15 in Tamilnadu to 0.28 in Madya Maharashtra. The winter monsoon rainfall in some subdivisions in the northwest and some in central India only (Fig. 5d) have a significant relationship with the Darwin CJUL pressures. 5. Distribution of summer and winter monsoon rainfall over India during the years of low and high SO index The distributions of the summer and winter monsoon rainfall over India during the years of low and high values of the corresponding SO indices, Darwin CMAY pressures for summer, and Darwin CJUL pressures for winter monsoon rainfall are examined. For this, as in the case of rainfall, the years with the normalized anomaly of Darwin CMAY pressure less than or equal to 1.0 are identified as the low SOI years and the years with the value more than or equal to 1.0 as the high SOI years for the summer monsoon rainfall. There are 17 low SOI years (1882, 1883, 1886, 1887, 1890, 1916, 1921, 1938, 1942, 1950, 1955, 1956, 1960, 1968, 1973, 1978, and 1985) and 22 high SOI years (1873, 1896, 1902, 1912, 1913, 1928, 1929, 1930, 1935, 1937, 1940, 1947, 1951, 1953, 1957, 1966, 1972, 1976, 1982, 1987, 1991, and 1993) for the summer monsoon rainfall (Fig. 3a) during the period of study. The remaining years are taken as the normal or neutral years. The composite means of the summer monsoon rainfall over India during the years of the low and high Darwin CMAY pressures are evaluated to be 88.7 and 80.3 cm respectively, while the composite mean rainfall during the neutral years is 85.9 cm. The percentage departures based on the differences between the composite rainfall of the low and neutral years and also between that of the high and neutral years are evaluated. In this way, the influence of extreme years is eliminated. The statistical significance of the differences between the composite means is calculated by using Z statistic as follows: X1 X2 Z, 2 2 1/2 1 2 n n 1 2 where X 1, X 2 are the means; 1, 2 are the standard deviations; and n 1, n 2 are the number of years of data of the first and second populations, respectively. The percentage departures show that the summer monsoon rainfall over India would be about 3% (significant at 10% level) more in the years of low SO index and about 6% (significant at 5% level) less in the years of high SO index than that during the normal years. Similarly, the anomalies of summer monsoon rainfall during the years of the low and high CMAY Darwin pressures are also evaluated for each of the 29 subdivisions and presented in Figs. 5a and 5b, respectively. The subdivisions in which the difference between the

DECEMBER 1999 NOTES AND CORRESPONDENCE 3493 FIG. 5. Anomaly rainfall patterns (in %) of the summer monsoon during the years of (a) low and (b) high Darwin CMAY pressures. Same as (a) but for the winter monsoon during the years of (c) low and (d) high Darwin CJUL pressures. Subdivisions in which the difference between composite means is significant are hatched.

3494 JOURNAL OF CLIMATE VOLUME 12 composite means is significant, are hatched. During the years of the low SO index, as in the case of all-india rainfall, except in three subdivisions (hatched in Fig. 5a) in which also the anomalies are significant only at 10% level, in all the remaining subdivisions the rainfall anomalies are small and insignificant. During the years of the high SO index, in nine subdivisions (hatched in Fig. 5b) the summer monsoon rainfall is significantly (5% level) less than that during the neutral years. In these subdivisions the anomalies vary from 8% to 15%. Similarly, the years of the low and high SOI are evaluated for the winter monsoon rainfall over India based on the normalized anomaly of Darwin CJUL pressures. There are 20 low SOI years (1872, 1878, 1879, 1886, 1889, 1890, 1893, 1895, 1903, 1910, 1916, 1917, 1920, 1938, 1955, 1956, 1975, 1978, 1979, and 1981) and 22 high SOI years (1873, 1876, 1877, 1880, 1881, 1902, 1913, 1914, 1918, 1923, 1925, 1940, 1941, 1944, 1953, 1965, 1970, 1976, 1982, 1987, and 1992) for the winter monsoon rainfall (Fig. 4a). The remaining years during the period of study are considered as normal years. It is to be noted that the years of the low and high SO index for the summer and winter monsoon rainfall differ largely. This is because they are identified on the basis of two different SO indices: the Darwin CMAY pressures for the summer monsoon rainfall and the Darwin CJUL pressures for the winter monsoon rainfall, respectively. The composite mean winter monsoon rainfall over India during the years of the low and high SO index are found to be 14.3 and 11.1 cm and during the normal years, it is 11.8 cm. The percentage departures of these composite rainfall are evaluated (as described earlier) to be 21% and 6% (significant at 5% level). Similar percentage departures are also evaluated for the 29 subdivisions and the anomaly rainfall patterns are presented in Figs. 5c and 5d. During the years of low SO index, the subdivisions in the central and western parts of India (hatched in Fig. 5c) receive significantly (5% level) excess winter monsoon rainfall. However, it is to be noted that in the subdivisions in western India, the mean winter monsoon rainfall is less. During the years of the high SO index, seven subdivisions in the northeastern and eastern parts of India receive significantly (5% level) deficient winter monsoon rainfall, which varies from 20% to 34% less than their mean. 6. Discussion and conclusions The all-india rainfall during summer and winter monsoons and their interannual variations are examined during the 122-yr period (1872 1993). The winter monsoon rainfall, which is dominant over southern peninsular India is observed to be more variable (28%) than the summer monsoon rainfall (10%). In an attempt to investigate if there is any relation between the summer and winter monsoon rainfall over India, southern peninsular India, and Tamilnadu, it has been observed that the correlation of all-india winter monsoon rainfall with the summer monsoon rainfall over the above three regions is positive, while the Tamilnadu winter monsoon rainfall is having negative correlations. Although all these correlations are significant, they are weak and also vary in time. The association of the summer and winter monsoon rainfall over India with monthly and seasonal Darwin MSL pressures has been examined during the 122-yr period of study. The all-india summer monsoon rainfall is found to have stronger and consistent correlation with the concurrent May pressures (CC 0.36) than with the winter to spring (MAM DJF) seasonal pressure tendency (CC 0.30) during the period of study. The all-india winter monsoon rainfall has a significant but weak negative correlation with the Darwin MSL pressures during the concurrent July (CC 0.21). Hence, for the summer monsoon rainfall over India, the Darwin CMAY pressures and for the winter monsoon rainfall, the Darwin CJUL pressures are considered as the indices of SO. The subdivisional variation of the SO relationship with the summer and winter monsoon rainfall is also examined. In the case of the summer monsoon, it is observed that in the subdivisions in northeastern, northwestern, and southern India, the SO relationship is weak and insignificant. Similarly, in the case of winter monsoon rainfall also, only a few subdivisions in northwest and central India are having significant correlations. These subdivisional variations in the SO relationship may be due to the changes in the regional circulation patterns under the influence of local topography. The distribution of the summer monsoon rainfall over India during the years of low and high Darwin CMAY pressures and that of the winter monsoon rainfall during the years of low and high CJUL pressure is also examined. A series of similar studies was made earlier to examine large-scale precipitation patterns associated with the low index (Ropelewski and Halpert 1986, 1987) and also with the high index (Ropelewski and Halpert 1989) phases of the SO for several regions of the globe. Similarly, Kiladis and Diaz (1989) examined the global temperature and precipitation anomalies associated with the extremes in the SO. In the present study, during the low SO index years, the all-india summer and winter monsoon rainfalls are found to be about 3% and 21% more, while during the high SO index years, they are 6% lesser than their corresponding means during the normal years. On a subdivisional basis, the rainfall anomalies during the extreme years of the SO are significant in only a few subdivisions. There is large variation in the subdivisional distribution of the rainfall anomalies in both summer and winter monsoons during the high and low SOI years. Acknowledgments. The author wishes to express his thanks to the Department of Science and Technology

DECEMBER 1999 NOTES AND CORRESPONDENCE 3495 (DST), Government of India, for providing funds during the period of study under the Young Scientists Scheme. REFERENCES Bhalme, H. N., D. A. Mooley, and S. K. Jadhav, 1983: Fluctuations in the drought/flood area over India and relationships with the Southern Oscillation. Mon. Wea. Rev., 111, 86 94. Bureau of Meteorology, 1987: Appendix A Darwin monthly mean sealevel pressure data. Department of Science, Northern Territory, Australia, Vol. 6, No. 4. Chen, W. Y., 1982: Assessment of Southern Oscillation sea-level pressure indices. Mon. Wea. Rev., 110, 800 807. Dhar, O. N., and P. R. Rakhecha, 1983: Foreshadowing northeast monsoon rainfall over Tamilnadu, India. Mon. Wea. Rev., 111, 109 112. Elliot, W. P., and K. Angell, 1987: The relation between Indian monsoon rainfall, the Southern Oscillation and hemispheric air and sea temperature: 1884 1984. J. Climate Appl. Meteor., 26, 943 948., and, 1988: Evidence for changes in Southern Oscillation relationships during the last 100 years. J. Climate, 1, 729 737. Hastenrath, S., 1991: Climate Dynamics of the Tropics. Kluwer Academic, 488 pp. Indian Meteorological Department, 1973: Northeast monsoon. FMU Rep. IV-18.4. Kiladis, G. N., and H. F. Diaz, 1989: Global climatic anomalies associated with extremes in the Southern Oscillation. J. Climate, 2, 1069 1090. Mooley, D. A., and B. Parthasarathy, 1983: Variability of the Indian summer monsoon and tropical circulation features. Mon. Wea. Rev., 111, 967 978., and, 1984: Fluctuations in all-india summer monsoon rainfall during 1871 1978. Climatic Change, 6, 287 301., and J. Shukla, 1987: Variability and forecasting of the summer monsoon rainfall over India. Monsoon Meteorology, Monogr. Geology Geophys., Oxford University Press, 26 58., and A. A. Munot, 1993: Variation in the relationship of the Indian summer monsoon with global factors. Proc. Indian Acad. Sci. (Earth Planet. Sci.), 102, 89 104. Nageswara Rao, G., 1998: Interannual variations of monsoon rainfall in Godavari river basin Connections with the Southern Oscillation. J. Climate, 11, 771 774. Pant, G. B., and B. Parthasarathy, 1981: Some aspects of an association between the Southern Oscillation and Indian summer monsoon. Arch. Meteor. Geophys. Bioklimatol., Series B, 29, 245 252. Parthasarathy, B., and G. B. Pant, 1985: Seasonal relationships between Indian summer monsoon rainfall and the Southern Oscillation. J. Climatol., 5, 369 378., H. F. Diaz, and J. K. Eischeld, 1988: Prediction of all-india summer monsoon rainfall with regional and large-scale parameters. J. Geophys. Res., 93, 5341 5350., K. Rupa Kumar, and A. A. Munot, 1993: Homogeneous Indian monsoon rainfall: Variability and prediction. Proc. Indian Acad. Sci. (Earth Planet. Sci.), 102, 121 155., A. A. Munot, and D. R. Kothawale, 1995: Monthly and seasonal rainfall series for all-india, homogeneous regions and meteorological subdivisions: 1871 1994. Research Rep. RR-065, Indian Institute of Tropical Meteorology, Pune, India. Raj, Y. E. A., 1996: Inter and intra-seasonal variation of thermodynamic parameters of the atmosphere over coastal Tamilnadu during northeast monsoon. Mausam, 47 (3), 259 268. Rao, K. V., 1963: A study of the Indian northeast monsoon season. Ind. J. Meteor. Geophys., 14, 143 155. Rasmusson, E. M., and T. H. Carpenter, 1983: The relationship between Eastern Equatorial Pacific sea surface temperatures and rainfall over India and Sri Lanka. Mon. Wea. Rev., 111, 517 528. Ropelewski, C. F., and M. S. Halpert, 1986: North American precipitation and temperature patterns associated with the El Niño/ Southern Oscillation (ENSO). Mon. Wea. Rev., 114, 2352 2362., and, 1987: Global and regional scale precipitation patterns associated with the El Nino/Southern Oscillation. Mon. Wea. Rev., 115, 1606 1626., and P. D. Jones, 1987: An extension of the Tahiti Darwin Southern Oscillation index. Mon. Wea. Rev., 115, 2161 2165., and, 1989: Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Climate, 2, 268 284. Shukla, J., 1987: Interannual variability of monsoons. Monsoons, J. S. Fein and P. L. Stephens, Eds., Wiley and Sons, 399 464., and D. A. Paolino, 1983: The Southern Oscillation and long range forecasting of summer monsoon rainfall over India. Mon. Wea. Rev., 111, 1830 1837. Singh, O. P., 1995: Influence of Bay of Bengal on winter monsoon rainfall. Mausam, 46 (3), 307 312. Trenberth, K. E., 1991: General characteristics of El Nino Southern Oscillation. Teleconnections Linking Worldwide Climate Anamolies, M. H. Glantz, R. W. Katz, and N. Nicholls, Eds., Cambridge University Press, 13 42. Walker, G. T., 1924: Correlation in seasonal variations of weather, IX: A further study of world weather (world weather II). Mem. India Meteor. Dept., 24, 275 332., and E. W. Bliss, 1932: World weather V. Mem. Roy. Meteor. Soc., 4, 53 84.