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

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 34: (2014) Published online 20 March 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: /joc.3695 Interannual variability of surface air-temperature over India: impact of ENSO and Indian Ocean Sea surface temperature J. S. Chowdary, a * Nisha John a,b and C. Gnanaseelan a a Indian Institute of Tropical Meteorology, Pune , India b Sir Syed College, Taliparamba , India ABSTRACT: Interannual variability of the seasonal surface air-temperature over the Indian subcontinent is investigated using observations for the period of Our results demonstrate that air-temperature over India is remotely influenced by the El Niño-Southern Oscillation and locally through Indian Ocean sea surface temperature (SST) anomalies. The leading mode of variability (EOF-1, empirical orthogonal function) in the observed air-temperature displays a countrywide warming in all four seasons. The spatial pattern of EOF-1 is similar to that of composite air-temperature anomalies of warm/cold years. Above-normal air-temperature in India (country-wide warming) is positively correlated to a simultaneous El Niño conditions in the eastern Pacific during boreal summer. El Niño induced strong subsidence, weaker low-level winds, less moisture availability and enhanced incoming shortwave radiation over the north Indian Ocean and Indian subcontinent are responsible for air-temperature warming in summer. It is observed that during fall, air-temperature pattern of EOF-1 over India is highly correlated with SST over the tropical oceans. SST correlation is maximum in central Pacific and north Indian Ocean, indicating the importance of both remote and local forcing. During boreal spring and winter, air-temperature warming (EOF-1) is mainly influenced by Indian Ocean SST anomalies. Low moisture and negative sea level pressure anomalies over India indicate the existence of heat low with strong dry winds convergence, which are favourable for airtemperature warming in spring. Although El Niño peaks during winter, its impact on the air-temperature over the Indian subcontinent is weak during this season. The second EOF mode shows dipole-like air-temperature pattern with warming over the south-east and cooling in the north-western India during summer and winter, whereas spring shows opposite polarity. In case of boreal fall, EOF-2 of air-temperature displays a south-west and north-east orientation. Mechanisms responsible for these variabilities are studied in detail. KEY WORDS air-temperature; ENSO; Indian Subcontinent; Indian Ocean; sea surface temperature Received 21 September 2012; Revised 26 December 2012; Accepted 18 February Introduction Long-term trends in surface air-temperature (hereafter air-temperature) are key characteristics in identifying climate change. The variability of air-temperature proved to be very important in terms of detecting anthropogenic climate change (Santer et al., 1996). The Fourth Assessment Report (AR4) of the intergovernmental Panel on Climate Change (IPCC, 2007) reported that global mean surface air-temperature has increased by 0.7 C in the last century. The increasing concentrations of CO 2 and greenhouse gases in the atmosphere are considered as the major causes of global-mean rise in air-temperature during the 20th century (Meehl et al., 2007). This surface warming is much stronger over land because of less efficient evaporative cooling and smaller heat capacity compared to ocean (Sutton et al., 2007). Global distribution of annual mean air-temperature is illustrated in Figure 1. The mean annual air-temperature * Correspondence to: J. S. Chowdary, Indian Institute of Tropical Meteorology, Pune , India. jasti@tropmet.res.in is above 24 C over India, Maritime continent, central Africa, some parts of northern Australia, Mexico and South America. As the mean air-temperature over India is high, it reaches to 40 C in the interannual time scale (in some parts of India) and has serious impacts on vegetation distributions, human health and other social issues. Therefore, it is essential to understand the interannual variability of air-temperature over India. El Niño Southern Oscillation (ENSO) is known to have strong impact on the global to regional (including India) air-temperature variability (Kiladis and Diaz, 1989; Halpert and Ropelewski, 1992; Kothawale et al., 2010). Hingane et al. (1985) using air-temperature data from 73 stations reported 0.4 C increase in the mean annual temperature of India during the 20th century. This is of great concern as heat wave-induced casualties have increased over the Indian subcontinent in recent years (De et al., 2005). For example, heat wave conditions of 2003 prevailed during the pre-monsoon season with temperature rising up to 49 C in May causing a death toll of about 1500 people (De et al., 2005). The year 2010 is the warmest year according to the India Meteorological 2013 Royal Meteorological Society

2 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 417 Figure 1. Annual mean air-temperature ( C) over the globe for the period Department. Mean annual temperature of India in 2010 was 0.93 C above the long-term average ( ), and is the warmest year since the national records began in 1901 (NOAA-NCDC-2010). It is also reported that the decade is India s warmest decade on record, with an anomaly of 0.4 C surpassing the previous decadal record of 0.2 C set in De and Mukhopadhyay (1998) showed that the heat waves in 1998 are linked to El-Niño of Reports indicate that heat wave conditions during 1998 caused larger number of deaths in different parts of the world (De et al., 2005). The previous studies indicate that number of casualties from severe heat waves is more during the years succeeding an El Niño (e.g. 1998, 2003 and 2010). The heat wave conditions of April 1999 are associated with local anomalous circulation setting over India and its neighbourhood (De et al., 2005) and are not related to global warming and ENSO (Kalsi and Pareek, 2001). Above studies indicate that hot summers associated with heat waves over India are influenced both by El Niño and local circulation over the Indian Ocean. Kothawale et al. (2010) examined the interannual variability of annual mean surface air-temperatures over India. The role of ENSO and Tropical Indian Ocean on the regional air-temperatures over India in different seasons is not well-documented in literature. Specifically, Indian Ocean sea surface temperature (SST) impact on air-temperature is not known earlier. This study carried out the empirical orthogonal function (EOF) analysis to identify major patterns of seasonal air-temperature variability in the interannual time scale over India and investigate mechanisms responsible for this variability. The article is organized as follows. In Section 2, we briefly describe the details of different data sets that are used in the study. Section 3 presents the annual cycle and trends in air-temperature over India. Section 4 demonstrates interannual variability of air-temperature and the possible causes. Section 5 summarizes the result. 2. Data and methods To understand the air-temperature variability over the Indian subcontinent we have used air-temperature data from university of Delaware for the period (Shepard, 1968; Willmott et al., 1985; Legates and Willmott, 1988; Legates and Willmott, 1990; Willmott and Matsuura, 1995). Anomalies are calculated based on climatology of air-temperature for the period of 106 years. Composite analysis is used for understanding the interannual variability. To isolate the prominent pattern of air-temperature variability, EOF analysis has been performed. The air-temperature is detrended before computing the EOFs. In addition to this, we performed the correlation analysis to understand the physical mechanisms responsible for air-temperature changes over India. The correlation of 0.20 is significant at 95% confidence level for 106 years based on two-tailed student s t-test. We have also used the National Oceanic and Atmospheric Administration (NOAA) Extended Reconstructed SST (ERSST) product (Smith and Reynolds, 2004), the 20th century reanalysis (20CR; Compo et al., 2011) sea level pressure (SLP), surface winds, precipitable water, and downward shortwave radiation (SWR) flux for the period To study the interannual variability, all the data is detrended prior to the analysis. A 9-year running mean is removed to suppress the decadal and long-term variations in the data as in Xie et al. (2009). To reduce the effect of pronounced intra-seasonal variability 3-month running average is applied. 3. Annual cycle and trend in air-temperature Annual cycle of air-temperature over India (only land points for the period of ) is shown in Figure 2(a). The air-temperature is maximum in May (29 C) and minimum (<20 C) in January. The warmest season in India is boreal spring (March May; MAM) and coldest is boreal winter (December February; DJF).

3 418 J. S. CHOWDARY et al. Figure 2. (a) Annual cycle of air-temperature ( C) over India, (b) time-series of annual mean air-temperature anomalies and its linear trend (solid line) and (c) de-trended time series of annual mean air-temperature anomalies. Air-temperature trend for 106 ( ) years is 0.33 in (b). It is observed that the trend in air-temperature anomalies over India is increased approximately at a rate of 0.03 C/decade during the period of (Figure 2(b)). Time series of detrended annual mean anomalies of air-temperature over India shows predominant interannual variability with warm and cold years periodically (Figure 2(c)). Figure 3 shows time series of detrended seasonal air-temperature anomalies (normalized) over the Indian land mass for the period of for all four seasons. The warm and cold events/years are apparent in all seasons. The years in which air-temperature is above (below) one standard deviation is considered as warm (cold) events. This classification is used for preparing the respective composites and carrying out detailed analysis. 4. Interannual variability of air-temperature over India 4.1. Composite analysis Figure 4(a) shows the air-temperature composites for warm and cold events over the Indian sub-continent in MAM. During the period of , a total of 14 warm years and 15 cold years are identified (Table 1). It is observed that during the warm episodes strong warming is seen over north and north-western parts of India compared to other regions. On an average airtemperature anomalies exceed 2 C over north India and maintained between 0.2 and 1 C in the south and eastern India. Similarly cold composite of MAM (Figure 4; left) shows strong negative anomalies over the north and north-western parts of India compared to other regions. It is interesting to note that patterns of warm and cold airtemperature (spatial distributions) are mirror images to each other in MAM. The spatial patterns of warming and cooling during summer (June September; JJAS) are similar to that of spring (Figure 4(a) and (b)), but with weaker magnitude. In the warm composite strong warming is observed over the west central India with weak warming over most of the Indian subcontinent. Similarly the cold composites display cooling over most of the Indian subcontinent with maximum cooling over west central India. The lists of warm and cold years are presented in Table-1.

4 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 419 Figure 3. De-trended time-series of seasonal air-temperature anomalies ( C) for (a) MAM (spring), (b) JJAS (summer), (c) ON (fall) and (d) DJF (winter) during period of Warm and cold composites of air-temperature during fall season (October November; ON) shows pattern similar to spring and summer (Figure 4(b) and (c)). The magnitude of warming and cooling over the Indian region during fall is as strong as MAM. The composite of winter air-temperature (Figure 4(d)) shows that warm and cold anomalies are spread evenly throughout the Indian subcontinent unlike in other seasons. Although magnitudes of warming and cooling in winter are weaker, the country-wide signals are apparent. Warm and cold air-temperatures are known to have strong impact on the regional climate and human society. Therefore, it is very important to understand what causes the interannual variability of air-temperature during different seasons. Furthermore, it is essential to know whether this country-wide warming/cooling is the dominant mode of variability in the air-temperature Dominant modes in air-temperature over India and possible causes We have performed EOF analysis of air-temperature separately for all four seasons to examine the dominant modes of variability. Note that only the first two dominant modes are considered for the analysis as they explain most of the variability. Figure 5(a) shows the EOF-1 spatial pattern of air-temperature during spring season and this pattern explains 65% of total variance. The leading mode of air-temperature resembles the composite of warm/cold years, indicating the country-wide warming as the dominant mode of interannual variability. EOF- 2 of air-temperature over India (Figure 5(b)) shows opposite polarity in the north-west and south-east regions. This dipole pattern explains 10% of the interannual variance in the air-temperature. Principal components (PC) corresponding to EOF-1 and EOF-2 are shown in

5 420 J. S. CHOWDARY et al. Figure 4. Composite of air-temperature anomalies ( C; shaded and contours) for warm years (left) and cold years (right) during (a) MAM, (b) JJAS, (c) ON and (d) DJF for the period of Figure 5(c). Warm and cold years are clearly evident in the PC-1 time series from 1900 to The PC-1 and PC-2 are correlated over the global belt with SST and circulation between 50 S and 50 N to understand the processes responsible for these leading modes of variability. Figure 6(a) shows the correlation of MAM airtemperature PC-1 with SST and surface wind anomalies for the period It is observed that EOF-1 airtemperature pattern over India is highly correlated with north Indian Ocean and western Pacific SSTs and circulation. SST anomalies over the eastern Pacific and Atlantic Oceans are weaker. SLP low over the north Indian Ocean and negative precipitable water over most of the Arabian Sea and northern Africa are evident in Figure 6(b) and (c). Low moisture and negative SLP anomalies over India indicate the existence of heat low with strong dry winds convergence there. This local SST and circulation anomalies helps to warm air-temperature over the Indian subcontinent in spring. This is further supported by correlation of air-temperature PC-1 with SWR (Figure 6(d)). The positive SWR is favourable for warming the surface in clear sky conditions over the Indian subcontinent. When correlated the PC-2 with SST, the Arabian

6 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 421 Table 1. Warm and cold years during different seasons based on time-series of seasonal surface air-temperature over India. MAM JJAS ON DJF Warm years Cold years Warm years Cold years Warm years Cold years Warm years Cold years years 15 years 14 years 17 years 16 years 15 years 22 years 20 years Figure 5. (a) The first EOF mode of MAM air-temperature anomalies ( C; shaded and contours), (b) is same as in (a) but for the second EOF mode and (c) corresponding air-temperature principal components (PC). Percentage of variance is shown at the top of (a) and (b).

7 422 J. S. CHOWDARY et al. Figure 6. Correlation of MAM air-temperature PC-1 with MAM anomalies of (a) SST (shaded), surface winds (vectors), (b) SLP, (c) Precipitable water and (d) shortwave radiation, (e) (h) are similar to (a) (d) but for correlation with PC2. The correlation of 0.20 is significant at 95% confidence level. Sea (Bay of Bengal) displayed warm (cold) anomalies (Figure 6(e)). Wind anomalies are southwesterlies in the western Indian Ocean and weak southeasterlies in eastern Indian Ocean. Consistent with SST and circulation, SLP displays low over west and high over east in the Indian Subcontinent (Figure 6(f)). Warm wind intrusion from Arabian Sea to the western India and cold winds from Bay of Bengal to eastern India are responsible for the dipole pattern in EOF-2. In addition to this SWR (precipitable water) is negative (positive) in the east and central India and positive (negative) over the extreme northwestern parts of India (Figure 6(g) and (h)), supporting the evolution of dipole pattern in the spatial distribution of air-temperature. The first EOF (spatial; 50%) mode of JJAS airtemperature variability is similar to that of composite

8 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 423 Figure 7. (a) The first EOF mode of JJAS air-temperature anomalies ( C; shaded and contours), (b) is same as in (a) but for the second EOF mode and (c) corresponding air-temperature principal components (PC). Percentage of variance is shown at the top of (a) and (b). analysis (Figures 7 and 4). It is highly influenced by SST over the tropical oceans (Figure 8(a)). Winds are weaker than normal over the north Indian Ocean. In response to El Niño forcing from eastern Pacific, strong subsidence (high SLP) is seen over the Indian region (Figure 8(b)). This suppresses the mean convection over the Indian land region and enhances incoming SWR (Figure 8(d)). The precipitable water is also reduced over the north Indian Ocean (Figure 8(c)). ENSO influences the Indian monsoon region directly via large-scale circulation changes over the Indo-western Pacific (Mooley and Parthasarathy, 1983; Rasmusson and Carpenter, 1983; Shukla and Paolina, 1983; Webster et al., 1998; Kumar et al., 1999). Severe droughts/floods over India occur in association with ENSO events (Webster et al., 1998). The onset of El Niño reduces strength of monsoon winds and Somali jet in summer and induces warmer SST anomalies in the western Indian Ocean (Webster et al., 1998; Kumar et al., 1999). In addition to SST warming over the Indian Ocean, theses ENSO teleconnections alter the surface air-temperature over the Indian subcontinent. The anomalous central-eastern Pacific SST warming modulates the Walker circulation with local updraft and downdraft over the Indo-western Pacific region. The subsidence over the Indian region resulting from the anomalous Walker circulation in turn warms the air-temperature. Over all EOF-1 spatial pattern of air-temperature is strongly influenced by El Niño during summer monsoon season. EOF-2 (11% of variability) of air-temperature displays cooling in the north and north western parts of India and warming in the south and south eastern parts of India (Figure 7(b)). When SST is correlated with air-temperature PC-2 (Figure 8(e)), it is observed that western Indian Ocean is warmer and western Pacific and southeastern Indian Ocean are cooler. This shows that dipole pattern in air-temperature is strongly influenced by local SST. Circulation pattern over the Indian Ocean is also consistent with air-temperature distribution (second mode). SLP is high in the region north of 15 Nwhen correlated with JJAS air-temperature PC-2 (Figure 8(f)). Reduced moisture availability (negative precipitable water anomalies) and increased SWR (Figure 8(g) and (h)) support the variability. Our result shows that EOF-2 of air-temperature in JJAS is strongly influenced by local air sea interactions from Indian Ocean. The first EOF (55% of variability) mode of ON airtemperature is similar to that of JJAS (Figure 9(a)). The leading mode of air-temperature during fall season is the country-wide warming. EOF-2 (11% of variability) of air-temperature spatial pattern displays the southwest and northeast (south north) oriented positive and negative air-temperature anomalies over India

9 424 J. S. CHOWDARY et al. Figure 8. Correlation of JJAS air-temperature PC with JJAS anomalies of (a) SST (shaded), surface winds (vectors), (b) SLP, (c) Precipitable water and (d) shortwave radiation, (e) (h) are similar to (a) (d) but for correlation with PC2. The correlation of 0.20 is significant at 95% confidence level. (Figure 9(b)). The corresponding PC-1 and PC-2 are displayed in Figure 9(c). Correlation of ON air-temperature PC-1 with SST and surface wind anomalies is shown in Figure 10(a). It is observed that EOF-1 pattern over India is highly correlated with SST over the tropical Oceans. SST correlation is maximum in north Indian Ocean and central Pacific, indicating the influence of local and remote forcing, respectively. Winds are weaker than normal over the north Indian Ocean. In response to central Pacific El Niño, high SLP is noticed in some parts of the Indo-western Pacific region (Figure 10(b)). This accounts for low moisture availability and increased SWR over this region and some parts of India (Figure 10(c) and (d)). It is important to note that spatial pattern of EOF-1 is highly influenced by El Niño during fall season. The strong positive correlation of SST is found over the east-central Pacific and western tropical Indian Ocean when correlated with air-temperature PC-2 during fall

10 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 425 Figure 9. (a) The first EOF mode of ON air-temperature anomalies ( C; shaded and contours), (b) is same as in (a) but for the second EOF mode and (c) corresponding air-temperature principal components (PC). Percentage of variance is shown at the top of (a) and (b). season (Figure 10(e)). This shows that second mode of variability during fall season is closely related to eastern Pacific and western tropical Indian Ocean SSTs. However, SST correlation is strong (negative) in the western Pacific and east equatorial Indian Ocean (Figure 10(e)). TIO SST correlation pattern is similar to that of Indian Ocean dipole (IOD; Saji et al., 1999), indicating that the air-temperature distribution over the Indian subcontinent is also influenced by local air sea interactions (IOD) over the Indian Ocean. Winds are easterlies both over the north Indian Ocean and equatorial Indian Ocean. Strong positive SLP anomalies (Figure 10(f)) over the Indo-western Pacific and Indian subcontinent (especially east) are closely associated with IOD and El Niño. The distribution of precipitable water is consistent with SLP patterns (Figure 10(g)). During positive IOD years strong subsidence (negative precipitable water) associated with negative SST anomalies over the east equatorial Indian Ocean is observed. The Indian Ocean Walker cell shows organized convection and convergence over the west and subsidence over east during IOD events (Figure 10(g)). In conjunction to this, enhanced SWR is observed in the southern parts of India when correlated with airtemperature PC-2 during ON (Figure 10(h)), indicating that southern peninsular India receives positive solar radiation (anomalies) compared to northwestern parts of India (negatively correlated). Over all during fall season first mode of air-temperature variability over the Indian subcontinent is highly influenced by central Pacific El Niño (weak) and north Indian Ocean SSTs, whereas second mode is highly influenced by conventional El Niño and IOD forcing. During winter season, first mode (EOF-1, 44%) of variability in air-temperature (Figure 11(a)) displays a country-wide warming with the maximum anomalies over the north western parts of India. The EOF-2 (18% of variability) displays opposite polarity in air-temperature between northwest and southeast India (Figure 11(b)). The PC-1 during winter is correlated with SST and surface winds (Figure 12(a)) to understand the driving mechanisms. The strong SST anomalies associated with this mode is evident over the Arabian Sea and some parts of eastern Pacific and western Atlantic. The winds are weaker over the north Indian Ocean when correlated with DJF PC-1. It is important to note that even though El Niño peaks during winter it has less impact on the air-temperature over the Indian subcontinent. The airtemperature in winter is highly influenced by north Indian Ocean SSTs. SLP and precipitable water shows weak signals over north Indian Ocean (Figure 12(b) and (c)). SWR is strong in the north and north western parts of India compared to south when correlated with air-temperature

11 426 J. S. CHOWDARY et al. Figure 10. Correlation of ON air-temperature PC with ON anomalies of (a) SST (shaded), surface winds (vectors), (b) SLP, (c) Precipitable water and (d) shortwave radiation, (e) (h) are similar to (a) (d) but for correlation with PC2. The correlation of 0.20 is significant at 95% confidence level. PC-1 (Figure 12(d)). This explains the leading pattern of air-temperature during winter over India. PC-2 correlation with SST anomalies over the tropical oceans displays maximum warming over the entire tropical Indian Ocean (basin-wide warming), eastern Pacific and equatorial Atlantic Oceans (Figure 12(e)). This indicates that the EOF-2 of winter is highly influenced by SST over the tropical oceans. These SST anomalies in the Indian Ocean and Atlantic Ocean are response to El Niño in the Pacific (Chowdary and Gnanaseelan, 2007). Therefore the EOF-2 of air-temperature is highly influenced by El Niño in winter. This is also reflected in wind pattern (Figure 12(e)). SLP and precipitable water distributions are consistent with SSTs in the tropical oceans (Figure 12(f) and (g)). SWR is strong over the maritime continent and low over some parts of India (Figure 12(h)). Over all winter air-temperature is influenced by both local (north Indian Ocean SST) and remotely from Pacific via

12 INTERANNUAL VARIABILITY OF SURFACE AIR-TEMPERATURE OVER INDIA 427 Figure 11. (a) The first EOF mode of DJF air-temperature anomalies ( C; shaded and contours), (b) is same as in (a) but for the second EOF mode and (c) corresponding air-temperature principal components (PC). Percentage of variance is shown at the top of (a) and (b). the atmospheric bridge. The first mode of variability is controlled by north Indian Ocean SSTs, whereas the second mode of variability is dominated by SST anomalies over the equatorial eastern Pacific. 5. Summary The characteristics of interannual variability of the surface air-temperature over India are investigated during the 20th century (1900 through 2005) in all four seasons. A large part of the interannual variability of airtemperature is attributed to the ENSO and Indian Ocean SSTs. The spatial patterns of leading mode (EOF-1) display a country-wide warming in all seasons. These EOF-1 spatial patterns in air-temperature are similar to that of composite of warm years. Above-normal air-temperature over India (country-wide warming) is related to a simultaneous El Niño in the eastern Pacific during boreal summer. Strong subsidence, weaker low-level winds, less moisture availability and enhanced incoming SWR associated with El Niño in summer are responsible for surface warming. It is observed that leading mode of variability in fall air-temperature pattern over India is driven by SST over the tropical oceans. SST correlation is maximum in central Pacific, indicating that central Pacific has strong impact on air-temperature over Indian subcontinent. The leading mode of air-temperature warming (EOF-1) during boreal spring and winter is influenced by Indian Ocean SST anomalies. The low moisture and negative SLP anomalies indicate the existence of heat low with strong dry winds converging in to Indian subcontinent and assist surface warming in MAM. Even though El Niño peaks during winter, its impact on the winter airtemperature over the Indian subcontinent is weak. The second EOF mode shows dipole-like airtemperature pattern with warming over the south-east and cooling in the north-western India during JJAS and DJF, whereas MAM shows opposite polarity. During MAM, warm winds from Arabian Sea (blows to the western India) and cold winds from Bay of Bengal (to eastern India) are responsible for EOF-2 air-temperature patterns over India. During JJAS, EOF-2 is strongly influenced by local air sea interactions from Indian Ocean and western Pacific Ocean. In case of boreal fall, EOF-2 of air-temperature displays a south-west and north-east orientation, which is highly influenced by El Niño and IOD forcing. During DJF EOF-2 spatial pattern is influenced by SST anomalies over the equatorial eastern Pacific. There is a high level of consistency between changes in the Indian/Pacific Ocean SSTs and air-temperatures over India during the 20th century in the interannual time scale. Therefore, our results conclude

13 428 J. S. CHOWDARY et al. Figure 12. Correlation of DJF air-temperature PC with DJF anomalies of (a) SST (shaded), surface winds (vectors), (b) SLP, (c) Precipitable water and (d) shortwave radiation, (e) (h) are similar to (a) (d) but for correlation with PC2. The correlation of 0.20 is significant at 95% confidence level. that the ENSO and Indian Ocean warming/cooling are dominant factors that are responsible for interannual air-temperature over India. Acknowledgements We thank Prof. B. N. Goswami, Director IITM for support. We acknowledge S. Rahul for scientific discussions. Figures are prepared using GrADS. References Chowdary JS, Gnanaseelan C Basin-wide warming of the Indian Ocean during El Niño and Indian Ocean dipole years. International Journal of Climatology 27: Compo GP, Whitaker JS, Sardeshmukh PD, Matsui N, Allan RJ, Yin X, Gleason BE Jr, Vose RS, Rutledge G, Bessemoulin P, Brönnimann S, Brunet M, Crouthamel RI, Grant AN, Groisman PY, Jones PD, Kruk MC, Kruger AC, Marshall GJ, Maugeri M, Mok HY, Nordli Ø, Ross TF, Trigo RM, Wang XL, Woodruff SD, Worley SJ The twentieth century reanalysis project. Quarterly Journal of the Royal Meteorological Society 137: 1 28.

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