Australian Rainfall and Surface Temperature Variations Associated with the Southern Hemisphere Annular Mode

2452 JOURNAL OF CLIMATE VOLUME 20

HARRY H. HENDON Bureau of Meteorology Research Centre, Melbourne, Australia

DAVID W. J. THOMPSON Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

MATTHEW C. WHEELER Bureau of Meteorology Research Centre, Melbourne, Australia

(Manuscript received 27 April 2006, in final form 6 September 2006)

ABSTRACT

Daily variations in Australian rainfall and surface temperature associated with the Southern Hemisphere annular mode (SAM) are documented using observations for the period 1979–2005. The high index polarity of the SAM is characterized by a poleward contraction of the midlatitude westerlies. During winter, the high index polarity of the SAM is associated with decreased daily rainfall over southeast and southwest Aus- tralia, but during summer it is associated with increased daily rainfall on the southern east coast of Australia and decreased rainfall in western Tasmania. Variations in the SAM explain up to ϳ15% of the weekly rainfall variance in these regions, which is comparable to the variance accounted for by the El Niño– Southern Oscillation, especially during winter. The most widespread temperature anomalies associated with the SAM occur during the spring and summer seasons, when the high index polarity of the SAM is associated with anomalously low maximum temperature over most of central/eastern subtropical Australia. The regions of decreased maximum temperature are also associated with increased rainfall. Implications for recent trends in Australian rainfall and temperature are discussed.

1. Introduction SAM and the Northern Hemisphere annular mode (NAM) is documented in Thompson and Wallace The Northern and Southern Hemisphere annular (2000). modes play a prominent role in the climate of their The annular modes are naturally occurring patterns respective hemispheres. Both modes are characterized of variability in the climate system and have a typical by approximately zonally symmetric, equivalent baro- decorrelation time scale of ϳ2 weeks (Lorenz and tropic seesaws in the strength of the zonal flow between Hartmann 2001, 2003). However, the annular modes ϳ ϳ 55°–60° and 35°–40° latitude. The structure of the also appear to be sensitive to increasing greenhouse Southern Hemisphere annular mode (SAM; also re- gases in model simulations (e.g., Shindell et al. 1999; ferred to as the Antarctic Oscillation or High Latitude Fyfe et al. 1999; Kushner et al. 2001; Cai et al. 2003; Mode) is documented in, for example, Trenberth Miller et al. 2006; Arblaster and Meehl 2006), and over (1979), Rogers and van Loon (1982), Mo and White the past few decades, the SAM has exhibited trends (1985), Kidson (1988), Karoly (1990) and Thompson during austral summer that are consistent with forcing and Wallace (2000). The strong similarity between the by the Antarctic ozone hole (Thompson and Solomon 2002; Gillett and Thompson 2003; Shindell and Schmidt 2004). As such, the climate impacts of the annular Corresponding author address: Harry Hendon, Bureau of Me- teorology Research Centre, GPO Box 1289, Melbourne 3001, modes have implications not only for the current cli- Australia. mate, but for the interpretation of climate change as E-mail: [email protected] well.

DOI: 10.1175/JCLI4134.1

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC

JCLI4134 1JUNE 2007 HENDON ET AL. 2453

The climate impacts of the NAM have been exten- tion–National Center for Atmospheric Research sively examined in numerous studies. However, rela- (NCEP–NCAR) reanalysis (Kalnay et al. 1996). The tively little work has been done on documenting re- EOF analysis was conducted on the base period 1979 to gional climate variations associated with the SAM. This 2000. Before computing the EOFs, the seasonal cycle is partly explained because much of the inhabitable was removed from the data, and grid points were landmasses in the Southern Hemisphere are equator- weighted by the square root of the cosine of latitude. ward of the region where the SAM produces its largest The EOFs are based on the covariance matrix. We use changes in circulation. Nonetheless, rainfall variations daily values of the SAM index for the period January associated with the SAM have been suggested, for in- 1979–February 2005. By convention, the high index po- stance, in southern South America (Silvestri and Vera larity of the SAM (positive index) is associated with 2003; Haylock et al. 2006), western South Africa (Rea- anomalous westerly flow along ϳ60°S juxtaposed son and Rouault 2005) and southwestern Australia against anomalous easterly flow along ϳ40°S. (Meneghini et al. 2007). Recent and projected climate Daily Australian rainfall variations are assessed using change in southwestern Australia (decreased winter- an objective analysis (Mills et al. 1997) of daily gauge time rainfall) has been attributed to a positive trend in reports (Lavery et al. 1997) that span the entire coun- the SAM (e.g., Ansell et al. 2000; Cai et al. 2003; Li et try. The daily analyses are available on a 1° grid for the al. 2005). In many of these studies, decreased winter- same period as the SAM index (January 1979–February time rainfall during the high polarity of the SAM has 2005). Daily maximum and minimum surface tempera- been attributed to a poleward shift of the midlatitude ture variations are assessed using approximately 100 storm track. high-quality stations that have nearly continuous The purpose of the present study is to comprehen- records for the period 1979–2005 (Trewin and Trevitt sively document the impact of the SAM on daily rain- 1996; Torok and Nicholls 1996). Circulation variations fall and surface temperature variations in station-based in the Australian region associated with the SAM are data throughout Australia. The results clarify the role assessed with daily mean analyses of sea level pressure of the SAM for variations of Australian climate and and winds at 850 hPa from the NCEP–NCAR reanaly- also provide a sounder basis for attribution of recent sis (Kalnay et al. 1996). Australian climate change to observed trends in the Composite anomalies are formed for each season: SAM. December–February (DJF), March–May (MAM), June–August (JJA), and September–November (SON). 2. Data and analysis method During all seasons, high and low index days are defined Our primary approach is to composite daily varia- as days on which anomalies in the daily SAM index tions in rainfall and temperature during days corre- exceed one standard deviation in absolute value based sponding to the high and low index polarities of the on the full 1979–2005 daily record. The magnitude of SAM. Daily data are used throughout the study in or- the daily SAM index exceeds one standard deviation in der to exploit the fact that the typical decorrelation absolute value about one-third of the time, hence for ϳ time for the SAM is 1–2 weeks. Thus, use of daily data each season roughly 400 days (out of a total of 2400 increases the sample sizes used in the analyses relative days) correspond to the high and low index polarity, to composites based on, say, monthly mean data. The respectively. We examine all four seasons separately analyses are restricted to the period post-1979, for because 1) southwestern Australia receives the bulk of which assimilation of satellite data provides a reliable its rainfall during winter, but much of the rest of Aus- estimate of daily variations in the SAM in global re- tralia receives significant rainfall in spring, summer, and analyses (e.g., Marshall 2003). autumn; and 2) the mechanisms for rainfall in southeast The SAM is defined using daily index values pro- Australia vary from winter (primarily midlatitude fron- vided by the U.S. National Weather Service Climate tal systems) to summer (e.g., moist northeasterly tropi- Prediction Center (CPC; http://www.cpc.ncep.noaa. cal intrusions associated with a poleward shift of the gov/products/precip/CWlink/daily_ao_index/aao/ subtropical ridge and the development of the monsoon aao_index.html). trough). Hence, the regional impacts of the SAM are The CPC daily SAM index was constructed by pro- expected to vary with season. jecting daily 700-hPa height anomalies onto the leading The significance of the composited anomalies is empirical orthogonal function (EOF) of monthly mean judged in two ways. For temperature and winds, which 700-hPa height poleward of 20°S. The height data are are more normally distributed than rainfall, the com- from the National Centers for Environmental Predic- posite differences are estimated to be significantly dif-

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 2454 JOURNAL OF CLIMATE VOLUME 20 ferent from zero at the 95% (90%) level using a t test in Fig. 1 for summer (DJF) and in Fig. 2 for winter applied to the difference of two means: (JJA). The total composites for the high and low index | Ϫ | polarities are provided so that the differences (e.g., the X1 X2 t ϭ Ͼ 1.98 ͑1.66͒. high-minus-low index maps) can be interpreted within ͌ ր ϩ ր s 1 Neff1 1 Neff2 the context of the mean state. To first order, the high and low index polarities of the Here, X1 and X2 are the sample means for the high and low phases and SAM have opposite signed but otherwise identical climate impacts. Thus in the discussion that follows we ͑N s2 ϩ N s2͒ will refer to the high-minus-low index composite differ- ϭ ͱ 1 1 2 2 s ͑ ϩ ͒ , ences as anomalous conditions during the high index N1 N2 polarity of the SAM (similarly, anomalous conditions where s1 and s2 are the standard deviations of daily associated with the low index polarity of the SAM can winds or temperatures for the high and low phases, and be approximated as the opposite of the high-minus-low N1 and N2 are the sample sizes for each phase. Here, index composite maps). The high-minus-low index Neff1 and Neff2 are the effective sample sizes taking into composite maps correspond to conditions associated account the autocorrelation of the daily SAM index. with a roughly 3 standard deviation change in the daily For temperature and wind data, N1 and N2 typically SAM index (i.e., the mean of the SAM index averaged ϳ range 350–400 days, and Neff N/3. over the high and low index composites is ϳϩ1.5 and For the composite rainfall differences, we adopt a ϳϪ1.5 standard deviations, respectively). Monte Carlo resampling technique whereby 500 syn- In both summer and winter, the high index polarity of thetic realizations of the composite high-minus-low dif- the SAM is associated with anomalously high surface ference are generated from daily data that have been pressure centered at about 45°S and enhanced circum- randomized while retaining the original redness of the polar westerlies poleward of 55°S (Figs. 1 and 2, bot- time series. The randomization is done by successively tom). At Australian latitudes (15°–40°S) the anomalous shifting the start date of the SAM index and reversing flow is predominantly easterly with a magnitude of its time sequence relative to the rainfall time series, and ϳ3–5msϪ1. The lower-tropospheric zonal wind then recomputing the composites. The shifting is done anomalies extend and strengthen upward through the 500 times in 4-day increments, and the composites are troposphere (not shown), indicative of the equivalent recalculated using data only from the desired seasons. barotropic nature of the SAM. The composite analysis The technique maintains the autocorrelation (redness) also captures zonal asymmetries in the pressure and of both the daily SAM index and the rainfall data. We wind fields associated with the SAM, with centers of then sort the 500 samples from lowest to highest, based maximum surface pressure occurring near 90°E and on the magnitude of the composite difference. The 50th east of 180°. The midlatitude asymmetries inherent in highest composite magnitude is the threshold for the the SAM are much less prominent than the asymme- highest decile in this randomized sample. This thresh- tries associated with the NAM (e.g., Thompson and old is then used as the baseline for the 90% significance Wallace 2000), but nevertheless contribute to longitu- level in the original composite. Note that we sort based dinal variations in the climate impacts of the SAM. on the magnitude of the composite anomaly and use the In winter (JJA; Fig. 2), when the climatological mean same threshold for determining the significance of a westerlies and subtropical ridge extend equatorward positive or negative anomaly. Thus our significance test into subtropical central Australia, the anomalous east- makes no assumption about the sign of the expected erlies associated with the high index polarity of the anomaly, which is equivalent to applying a two-tailed SAM cover most of the continent (Fig. 2, bottom). In test. contrast, during summer (DJF; Fig. 1), when the climatological mean subtropical ridge is contracted poleward 3. Rainfall and temperature variations and the monsoon trough is developed over central and northern Australia (e.g., Hendon and Liebmann 1990), a. Composite circulation anomalies the anomalous easterlies associated with the high index To provide context for the rainfall and surface tem- polarity of the SAM are confined to southern Australia perature variations associated with the SAM, we first (Fig. 1, bottom). Wind anomalies associated with the examine the associated changes in the lower-tropo- high index polarity of the SAM during spring (high- spheric flow in the Australian region. Composite maps lighted for the Australian region in Fig. 3, bottom left) of winds at 850 hPa and sea level pressure for low index are similar to summer, though the easterly anomalies days, high index days, and their differences are shown across southern Australia have a weaker meridional

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 1JUNE 2007 HENDON ET AL. 2455

Ϫ FIG. 1. Composite daily 850-hPa winds [maximum vector (m s 1) shown to right of each panel] and sea level pressure for the (top) low, (middle) high, and (bottom) high-minus-low polarity of the daily SAM index in the December–February season, 1979–2005. The contour interval (CI) in the top two panels is 3 hPa, and in the bottom panel is 2 hPa. The number of days in each index polarity is indicated in the upper right of the top two panels. Vector winds are plotted heavy where they are deemed to significantly differ from 0 at the 90% level based on a t test. Positive (negative) contours of sea level pressure differences are solid (dashed) and the zero contour is heavy in bottom panel. The vector wind scale in the bottom panel is 1⁄2 that in the top two panels, but the maximum plotted vector is different as indicated.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 2456 JOURNAL OF CLIMATE VOLUME 20

FIG. 2. Same as in Fig. 1, but for the June–August season. component. The easterly anomalies during the high in- seasons superposed on the attendant differences in the dex polarity of the SAM in autumn (highlighted for the 850-hPa flow (i.e., the wind anomalies for DJF and JJA Australian region in Fig. 3, top left) exhibit a pro- in Fig. 3 are reproduced from Figs. 1 and 2, respec- nounced southerly component over the western half of tively). In all seasons, significant anomalies are mainly the continent. confined to the southern half of the continent, but the contrast between the pattern of rainfall anomalies in b. Rainfall anomalies autumn/winter (MAM/JJA) and spring/summer (SON/ Figure 3 shows composites maps of rainfall for the DJF) is striking. In autumn/winter (Fig. 3, top), the high high-minus-low index polarities of the SAM for all four polarity index of the SAM is associated with decreased

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 1JUNE 2007 HENDON ET AL. 2457

FIG. 3. Composite daily rainfall (contours and shading) and 850-hPa winds (maximum vector shown in lower left of each panel) for high–low polarity of the SAM index for March– May, June–August, September–November, and December–February. CI for rainfall differences is 0.5 mm dayϪ1 with negative difference dashed. Differences that are deemed to be significantly different from zero based on a resampled Monte Carlo test are shaded. The number of days in the high and low index polarities of the SAM is listed in the upper right of each panel. The vector wind scale is the same in all panels, but the maximum plotted vector is different as indicated. rainfall in the extreme southwest, which has been al- upslope flow (weakened westerlies) on the western luded to in previous studies (e.g., Ansell et al. 2000; slopes of the generally north–south-oriented orogra- Meneghini et al. 2007). Decreased rainfall also occurs in phy. the southeast to the west of the Australian Alps during The increased rainfall on the southern third of the winter. In contrast, during spring/summer (Fig. 3, bot- east coast of the mainland in spring and summer (Fig. 3, tom), the high index polarity of the SAM is associated bottom) is consistent with an anomalous upslope source with increased rainfall on the southern third of the east of moisture from the Tasman Sea. However, the mean coast of the mainland and on the east coast of Tasma- winds are westerly along the southeast cost, even dur- nia. Decreased rainfall is also apparent on the west ing high polarity of the SAM (e.g., Fig. 1). Thus, it coast of Tasmania, especially during spring. remains to be demonstrated that the high polarity of The negative rainfall anomalies in the southwest and the SAM is associated with an actual increase in ups- in the southeast to the west of the Australian Alps in lope (easterly) conditions. We demonstrate this by autumn–winter during high index polarity of the SAM computing the rate of occurrence of easterlies at 850 are consistent with the accompanying anomalous east- hPa in the low index polarity (Fig. 4, top), high index erly winds. The easterly anomalies correspond to a polarity (Fig. 4, middle), and high-minus-low difference weakening of the climatological mean westerlies, and (Fig. 4, bottom). Upslope easterlies occur about 10% of presumably act to reduce or weaken the westward pro- the time on the southeast coast during the low index gression of rain-producing synoptic weather systems polarity of the SAM, increasing to 30% of the time that develop in the midlatitude westerlies. Similarly, the during the high index polarity of the SAM. Hence, wet negative rainfall anomalies on the west coast of Tasma- conditions on the southeast coast during the high index nia in spring–summer, which are also accompanied by polarity of the SAM are consistent with a twofold in- anomalous easterly winds, appear to stem from reduced crease in the occurrence of upslope easterly conditions

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC

Fig 3 live 4/C 2458 JOURNAL OF CLIMATE VOLUME 20

of these SAM-related rainfall anomalies can be assessed by comparing their amplitudes to the standard deviation of daily rainfall that has been low-pass filtered with application of a 7-day running mean (Fig. 5). The standard deviation of 7-day running mean, as opposed to raw daily data, is considered to account for the persistence of the SAM, (i.e., the daily rainfall anomalies shown in Fig. 3 are representative of conditions that persist for ϳ1 week). Figure 5 indicates that the greatest rainfall variability occurs in northern Australia during the summer monsoon, but this is a region that experiences little significant impact from the SAM. The southeast experiences near-constant rainfall variability year-round of ϳ2–3mmdayϪ1, while the southwest experiences a wintertime maximum in variability of ϳ3 mm dayϪ1. Comparison of Figs. 3 and 5 indicates that the SAM anomalies along the southeastern coast in spring–summer and in the southwest and southeast during autumn–winter approach 1 standard deviation of the 7-day running mean rainfall. Thus, in regions where the SAM has its greatest impact, a ϳ3 standard deviation anomaly of the SAM (as implied by the high-minus-low composites) is associated with a ϳ1 standard deviation change in weekly rainfall. In terms of variance, the SAM accounts for up to ϳ15% of the week-to-week rainfall variance in these regions. Another way to quantify the impact of the SAM on precipitation is to determine its impact on the occurrence of significant rainfall events, defined here as an accumulation above a specified threshold. We consider weekly rainfall accumulation in the highest quintile, which we define based on observed daily rainfall for 1950–2005. Because of the relatively short record with which to form composites (1979–2005), we use weekly as opposed to daily accumulation and we consider the upper quintile as opposed to a more extreme threshold such as the upper decile in order to reduce noise and thus produce more reliable estimates of the changes in FIG. 4. Rate of the daily occurrence of easterly flow at 850 hPa probabilities. for the (top) low, (middle) high, and (bottom) high-minus-low At every continental grid point an upper quintile for polarity of the daily SAM index in the December–February sea- the weekly rainfall rate is established, which by defini- son 1979–2005. CI is 4%. tion is exceeded 20% of the time. The climatology of the upper quintile threshold (not shown) varies spa- over that during the low index polarity. However, a tially and with season in a similar fashion as the weekly more thorough analysis of the relationship between standard deviation (Fig. 5). As for the weekly standard rain episodes and upslope flow on the east coast is war- deviation, the upper quintile threshold shows a general ranted in order to fully understand the impact of the lack of seasonality in southeast Australia, maximum in SAM. the southwest during winter, and overall highest values The rainfall anomalies associated with variations of in the north during summer. Threshold upper quintile the SAM approach 2 mm dayϪ1 in magnitude along the weekly rainfall accumulations range from in excess of southeast coast in spring–summer and in the southwest 100 mm in the north during summer to 25–55 mm in the and southeast during autumn–winter. The importance southeast and southwest during winter (with maximum

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 1JUNE 2007 HENDON ET AL. 2459

Ϫ FIG. 5. Std dev of low-pass-filtered (7-day running mean) daily rainfall (mm day 1) for MAM, JJA, SON, and DJF for the period 1979–2005. Data-void regions are unshaded. exceeding 70 mm on the west coast of Tasmania in up to 2 times larger during the low index polarity in winter). southwest Australia. These regions coincide with loca- The frequency of occurrence of days that exceed the tions where the mean rainfall is increased (reduced) weekly quintile rainfall rate for periods when the SAM during the low (high) index polarity of the SAM (Fig. 3, is in the high-versus-low index polarities is shown in top right). A region of modest increase in the incidence Fig. 6. Ratios greater (less) than one indicate an in- of an upper quintile event during the high index polar- creased (decreased) likelihood of a significant weekly ity is evident in southern Queensland/northern New rainfall event when the SAM is in its high index polar- South Wales. ity. The ratio is shaded only when it is significantly During spring/summer (Fig. 6, bottom), the likeli- different from 1 at the 90% level. Significance is as- hood of an upper quintile event is up to 2 times greater sessed using a resampled Monte Carlo test similar to in the high index polarity throughout much of southern that for the mean rainfall anomalies (Fig. 3). Here, we Australia, with the largest difference of ϳ3 observed on compute and sort 500 synthetic realizations of the ratio the southeast coast during summer. Interestingly, the of the frequency of occurrence of the weekly rainfall region of increased probability extends into south- accumulation in the upper quintile in the high-to-low central Australia during spring, which is a region where polarity index of the SAM. The 25th highest and 25th the difference in mean rainfall is not as pronounced lowest composite ratios are used as the thresholds for (Fig. 3, bottom). The mechanism for this increased oc- statistical significance of the high and low values of the currence of significant rainfall in south-central Austra- actual composite ratios, respectively. This is equivalent lia is not known but is possibly related to an elevated to 90% statistical significance with a two-sided test. occurrence of cutoff lows on the equatorward side of For the most part, the impact of the SAM on the the enhanced ridge along ϳ45°S (cf. Figs. 2 and 3) dur- incidence of an upper quintile rainfall event is consis- ing the high phase of the SAM. During spring and sum- tent with its impact on mean precipitation. During win- mer, an upper quintile event is also twice as likely dur- ter (Fig. 6, top right), the likelihood of a rainfall accu- ing the low index polarity of the SAM in western Tas- mulation in the upper quintile is ϳ1.5 times larger dur- mania, but more likely during the high index polarity in ing the low index polarity in southeast Australia, and eastern Tasmania.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 2460 JOURNAL OF CLIMATE VOLUME 20

FIG. 6. Ratio of the frequency of occurrence of exceeding the highest weekly quintile rainfall accumulation in the high index polarity to the low index polarity of the SAM. Solid contours are for ratios 1.5:1, 2:1, 2.5:1, 3:1, and 3.5:1. Dashed contours are ratios 1:1.5, 1:2, 1:2.5, 1:3, and 1:3.5. Shading indicates regions where the ratio is significantly different than 1 based on a resampled Monte Carlo test. The number of days in the high and low index polarities of the SAM is indicated in the upper right of each panel. c. Temperature anomalies rience increased rainfall and reduced maximum temperatures (Fig. 7) during the high index polarity of the Composites of daily maximum (Fig. 7) and minimum SAM. Presumably, these reduced minimum tempera- (Fig. 8) temperature for the high-minus-low index po- tures follow from reduced maximums as a result of re- larities of the SAM are made in a similar fashion as for duced daytime warming in regions of increased rainfall, rainfall. The greatest temperature anomalies occur dur- which is associated with increased cloudiness (reduced ing spring and summer, when much of the south-central insolation) and enhanced surface evaporation from and -eastern portions of the continent experience re- moist soil (e.g., Power et al. 1998). During winter in the duced maximum temperature during the high phase of southeast and southwest, where rainfall is reduced dur- the SAM (Fig. 7, bottom). These are regions that ex- ing the high phase of the SAM, minimum temperatures perience increased rainfall during the high phase of the are reduced (Fig. 8, top). If, as in summer, minimum SAM. In autumn (MAM; Fig. 7, top left) reduced temperatures are largely controlled by the follow-on maxima are confined to the western portion of the con- effect from changes in the daytime maximum tempera- tinent, where the flow anomalies associated with the ture as a result of variations in rainfall, then in these SAM have a pronounced southerly component (i.e., im- regions of reduced rainfall in winter we would expect plying cold advection) in this season (Fig. 3). increased minimum temperatures. But the regions in In general, the results for minimum temperature are the southeast and southwest during winter show little weaker than their maximum temperature counterparts, signal in maximum temperature (Fig. 7, top), so the but consistent with the distribution of rainfall anoma- reduced minimum is not a result of reduced daytime lies. For instance, in spring and summer minimum tem- warming. Rather, the reduced minimums presumably perature (Fig. 8, bottom) is reduced in the south-central stem from enhanced clear-sky cooling in regions of re- portions of the continent, which are regions that expe- duced cloud cover associated with reduced rainfall.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC

Fig 6 live 4/C 1JUNE 2007 HENDON ET AL. 2461

FIG. 7. Composite daily maximum temperature differences (°C) between the high and low index polarities of the SAM. Differences are plotted solid (open) where they are deemed to be significantly different from 0 at the 95% (90%) level based on a t test. Positive (negative) differences are indicated by circles (triangles).

This clear-sky cooling effect on minimum temperature of the SAM. Thus, an extreme maximum tempera- is only prominent if the effect of rainfall on daytime ture occurs about twice as often in the low phase as maximums is absent or removed (e.g., Power et al. during the high phase of the SAM. Note that the de- 1998). cile threshold (39.5°C) is about 1.5 standard devia- The changes in mean maximum and minimum tem- tions greater than the mean (32.6°C), which is an perature associated with the SAM are also accompa- equivalent method of defining extremes. Similarly, at nied by changes in the incidence of extreme tempera- Sydney on the southeast coast, the summertime maxi- ture events. Here, we define an extreme event as a mum decile threshold of 30.0°C is exceeded twice as temperature exceeding or dropping below the climato- often during the low index (53 out of 348 days) as dur- logical threshold for the highest or lowest decile. We ing the high index (22 out of 333 days) polarity of the focus on maximum temperature exceeding the upper SAM. decile in summer and minimum temperature dropping In winter, stations in the southwest and southeast below the lower decile in winter. Selective stations that exhibit a reduction in minimum temperature in the across south-central Australia (from west to east) are high index polarity of the SAM (Fig. 8) also exhibit a summarized in Table 1 for summer, when this region higher rate of occurrence of extreme minimum tem- experiences reduced maximum temperature during perature (Table 2). For instance at Wandering, which is the high index polarity of the SAM. For instance, at in the important wheat belt of Western Australia, win- Kalgoorlie in south-central Western Australia where tertime frost is almost 3 times less likely during the low the high-minus-low maximum temperature anomaly is index (17 out of 373 days) as during the high index (44 –2.9°C, an extreme maximum temperature (Ͼ39.5°C) out of 410 days) polarity of the SAM. Similarly, in occurs in 45 out of 348 days in the low phase of the southeastern Australia, hard frost at Rutherglen (mini- SAM but only in 23 out of 332 days in the high phase mum temperatures less than –2.5°C) is almost twice as

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 2462 JOURNAL OF CLIMATE VOLUME 20

FIG. 8. Same as in Fig. 7, but for daily minimum temperature. likely in the high index as compared to the low index of 4. Discussion the SAM. a. Relationship with ENSO Note that the impact of the SAM on the incidence of extreme temperatures is consistent with the changes in Two issues regarding the regional impacts of the the mean temperature (as indicated in Figs. 7 and 8) but SAM in Australia need further consideration. The first may also reflect changes in the shape (e.g., variance and is the impact of the El Niño–Southern Oscillation skewness) of the temperature frequency distribution at (ENSO) phenomenon on the composite anomalies de- individual stations. veloped in the previous section. The SAM is uncorre-

TABLE 1. Representative stations (from west to east) that exhibit significant changes in maximum temperature (TMax) associated with swings in the SAM for the summer season (DJF). Columns are station name and location, mean summer maximum T and its daily std dev, difference in maximum T for high polarity and low polarity composites of the SAM, climatological threshold for highest decile of maximum T, and rates of occurrence of highest decile in the high and low polarity composites of the SAM (days exceeding threshold in each phase and total number of days in each phase indicated in parentheses). Bold indicates differences significant at the 95% level.

⌬ Ϫ Mean TMax daily T (°C) (High low TMax decile High polarity Low polarity

Station std dev (°C) SAM TMax) threshold (°C) rate TMax (%) rate TMax (%) (348/45) 13 (332/23) 7 39.5 2.9؁ (Kalgoorlie (30.8°S, 121.4°E) 32.6 (5.3 (347/43) 12 (329/21) 6 40.0 2.7؁ (Forrest (30.8°S, 128.1°E) 31.8 (5.7 (339/41) 12 (330/15) 6 43.5 2.7؁ (Marree (29.6°S, 138.1°E) 37.4 (4.9 (346/54) 16 (324/18) 5 43.5 2.4؁ (Birdsville (25.90°S, 139.33°E) 38.6 (4.1 (347/43) 12 (333/17) 5 39.5 2.3؁ (Cobar (31.5°S, 145.8°E) 33.5 (4.6 (347/53) 15 (332/17) 5 36.5 2.3؁ (Gunnedah (31.0°S, 150.3°E) 31.7 (3.9 (347/53) 15 (331/21) 6 35.5 2.4؁ (Richmond (33.6°S, 150.8°E) 29.1 (4.8 (348/53) 15 (333/22) 7 30.0 1.5؁ (Sydney (33.87°S, 151.20°E) 26.1 (3.4

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 1JUNE 2007 HENDON ET AL. 2463

TABLE 2. Representative stations (from west to east) that exhibit significant changes in minimum temperature associated with swings in the SAM for the winter season (JJA). Columns are station name and location, mean winter minimum T and its daily std dev, minimum T difference for the high polarity and low polarity composites of the SAM, climatological threshold for lowest decile of minimum T, and rates of occurrence of lowest decile in the high and low polarity composites of the SAM (days exceeding threshold in each phase and total number of days in each phase indicated in parentheses). Bold indicates differences significant at the 95% level.

⌬ Ϫ Mean TMin T (high low Decile High polarity Low polarity Station (daily std dev) (°C) SAM; °C) threshold (°C) rate (%) rate (%) (395/12) 3 (465/55) 12 4.0 1.2؁ (Perth (31.93°S, 115.93°E) 8.5 (3.1 (373/17) 4 (410/44) 11 0 1.2؁ (Wandering (32.67°S, 116.67°E) 5.0 (3.8 (395/33) 8 (465/60) 13 0.5؁ 1.4؁ (Alice Springs (34.93°S, 138.58°E) 4.8 (4.7 (399/27) 7 (465/69) 15 1.5 1.0؁ (Laverton (37.87°S, 144.26°E) 5.5 (3.0 (391/37) 9 (464/76) 16 2.5؁ 1.1؁ (Rutherglen (36.10°S, 146.5°E) 2.5 (3.9 (389/39) 10 (461/67) 15 0 1.0؁ (East Sale (38.10°S, 147.13°E) 4.0 (3.2 (395/33) 8 (465/60) 13 1.5؁ 1.0؁ (Wagga Wagga (35.17°S, 147.15°E) 3.4 (3.5 lated with ENSO (as measured by popular indices of Smith 2004) and temperature (e.g., Nicholls 2003). The eastern equatorial Pacific sea surface temperature such SAM has exhibited a trend toward its high index po- as the Niño-3.4 SST index) in autumn through spring larity over the period 1979–2005, but the trend is re- (Table 3). However, during summer (DJF), the warm stricted primarily to the summer and, to a lesser extent, phase of the ENSO cycle is significantly associated with autumn months (Thompson and Solomon 2002; Mar- the low index polarity of the SAM (e.g., L’Heureux and shall 2003; Table 4). The positive trend in the SAM Thompson 2006). To ensure that we have extracted the corresponds to an increase of about ϳ1⁄2 of the daily SAM signal in rainfall in summer and not just a residual standard deviation of the SAM index during summer of the ENSO signal, we recomputed the high–low rain- for the period 1979–2005. The trend during autumn is a fall composite by excluding the summers during El more modest increase of ϳ1⁄3 of the daily standard de- Niño (1982/83, 1986/87, 1991/92, 1997/98, and 2002/03) viation. As there has been no significant trend in the and La Niña [1988/89, 1994/95, and 2000/01; the dates SAM during winter for this period, it is difficult to as- are identified by Smith and Sardeshmukh (2000) and cribe any observed wintertime rainfall or temperature are updated online at http://www.cdc.noaa.gov/people/ trends to a trend in the SAM. This does not preclude, cathy.smith/best/#years]. The high–low rainfall and however, the possible contribution of the SAM to the wind composite differences for summer in the non- wintertime rainfall decline in the southwest prior to ENSO years are remarkably similar to that when the ENSO years are included (i.e., compare Fig. 9 with the bottom-right panel in Fig. 3). This suggests that the results in this study are dominated by variations in the SAM and are not heavily contaminated by the impact of ENSO. However, this does not necessarily imply that we can separate the contributions of ENSO and the SAM to the summertime rainfall variations in the southeast. b. Trends The other issue that warrants attention is the role of the SAM in recent trends in Australian rainfall (e.g.,

TABLE 3. Correlation of SAM index with Niño-3.4 SST index (average SST for 5°S–5°N, 120°–170°W) for the period 1979–2005 (bold indicates significant correlation at the 95% level).

Monthly data Seasonal data SON Ϫ0.21 Ϫ0.25 FIG. 9. Composite daily rainfall and 850-hPa wind differences 0.48؁ 0.34؁ DJF between high and low index polarities of the SAM index during 0.16؁ 0.10؁ MAM DJF in non-ENSO years. Plotting convention is same as in JJA 0.00 0.00 Fig. 3.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 2464 JOURNAL OF CLIMATE VOLUME 20

TABLE 4. Trend in SAM index for the period 1979–2005. Units are daily std devs.

SON Ϫ0.15 DJF ϩ0.54 MAM ϩ0.35 JJA Ϫ0.06

1979 (e.g., Smith 2004), which extends prior to the start of the analysis presented here. On the other hand, the SAM has likely contributed to the observed summertime rainfall and temperature trend in the period 1979–2005, at least in the southern and central part of the country where the impacts of the SAM are most pronounced. The top panel in Fig. 10 shows the observed trend in rainfall during DJF for the period 1979–2005. The trend is dominated by wetter conditions in the tropical northwest, drier conditions in the northeastern coastal region, and increased rainfall extending into the southwest and southeast. Note that while the trend in the southern part of the country is small relative to that in the north, it nevertheless accounts for a comparable fraction of the total variance in their respective regions (i.e., cf. Fig. 10 to Fig. 5). The bottom panel in Fig. 10 shows the contribution of the SAM to the observed trends. The contribution of the SAM to the summertime trends is found by first recomputing the high–low summertime composite using detrended data. We use detrended data in order to obtain an unbiased estimate of contribution of the SAM to rainfall variability, but the high–low summertime rainfall composite based on detrended data is nearly identical to that based on raw data (Fig. 3, bottom right). The SAM contribution to the trend (Fig. 10, bottom) is then estimated by 1) normalizing the de- FIG. 10. (top) Observed rainfall trend for the DJF season 1979– trended high–low composite by the composite high–low 2005 based. (bottom) Rainfall trend that can be attributed to the SAM. CI is 0.2 mm dayϪ1 (27 yr)Ϫ1. amplitude of the SAM index (ϭϳ3), and then 2) scaling this normalized high–low detrended composite by the observed trend in SAM for the period 1979–2005. Only temperature is assessed in a similar fashion. We con- those locations where the SAM signal in daily rainfall is centrate on maximum temperature just in summer be- determined to be statistically significant at the 90% cause the SAM signature in maximum temperature in level, as in Fig. 3, are shaded. As expected, the SAM autumn and in minimum temperature in both summer does not account for the large positive rainfall trend in and autumn is small. Australia as a whole has experi- the northern and central portions of the continent enced a warming trend since the middle of the last cen- where there is little signal of the SAM in rainfall. How- tury that has been attributed to greenhouse gas warm- ever, the SAM does account for 50%–75% of the more ing (e.g., Karoly and Braganza 2005). During summer, modest positive trends in southeast Australia, and the this warming is most pronounced in the eastern portion east–west dipole in precipitation trends across Tasma- of the continent, where maximum temperature has in- nia. A similar analysis for the autumn season suggests creased at a rate of ϳ1°C (25 yr)Ϫ1 for the period 1960– that the modest positive trend in the SAM accounts for 2005 (Fig. 11, top). During the more recent period con- a portion of the observed drying trend in southwest sidered in this study (1979–2005), much of north-central Australia (not shown). Australia has cooled (consistent with this being a region The contribution of the SAM to trends in surface of increased rainfall but one that is unrelated to the

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC

Fig 10 live 4/C 1JUNE 2007 HENDON ET AL. 2465

SAM; Fig. 10) and the long-term warming in the southeast has largely been mitigated. This region of mitigated warming in the south and east coincides with where the SAM contribution to the trend (1979–2005) has a cooling of up to 0.5°C (25 yr)Ϫ1 (Fig. 11, bottom). Thus, it is tempting to infer that the recent upward trend in the SAM during summer has acted to mitigate some of the longer-term greenhouse gas warming across central-east Australia.

5. Conclusions The high index polarity of the SAM is associated with a poleward contraction of the midlatitude storm track and thus easterly anomalies across much of southern and central Australia. During winter, the easterly anomalies across southern Australia are associated with decreased daily rainfall in the southwest and in the southeast to the west of the Australian Alps, which are regions that receive much of their wintertime rainfall from synoptic-scale disturbances in the midlatitude westerlies. During spring and summer, the easterly anomalies during the high index polarity of the SAM are associated with increased daily rainfall on the southeast coast of the mainland, which appears to result from an increased occurrence of moist upslope flow from the Tasman Sea. The SAM explains 10%–15% of the weekly rainfall variability in the southwest and southeast during winter and on the southeast coast during spring–summer, which is comparable to or larger than the variability in these regions associated with ENSO (e.g., McBride and Nicholls 1983). Thus, the SAM is an important contributor to rainfall variability even in regions where the ENSO signal is prominent. Variations in the SAM also impact Australian surface temperatures. Maximum surface temperatures tend to be decreased (increased) in the regions of enhanced (decreased) rainfall. The strongest signals are in spring and summer across much of southern and eastern Australia, where maximum temperatures are reduced in regions of increased rainfall during the high index polarity of the SAM. The relationships between the SAM and daily minimum temperatures are weaker than their maximum temperature counterparts, but wintertime minimums tend to be decreased in regions of reduced rainfall, indicative of increased clear-sky cooling. The cooling of much of Australia during the high index polarity of the SAM is consistent with new calculations by Gillett et al. (2006) based on year-round Ϫ FIG. 11. Maximum temperature trend [°C (25 yr) 1] in DJF for station-based data. (top) 1960–2005 and (middle) 1979–2005. (bottom) Maximum The usefulness of the present results for deterministic temperature trend that can be attributed to the SAM in the 1979– prediction of rainfall and temperature is limited by both 2005 period. the signal strength of the climate impacts of the SAM

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC

Fig 11 live 4/C 2466 JOURNAL OF CLIMATE VOLUME 20 and by the ability to predict the SAM in the first place. in 2004. DT is grateful for support provided by BMRC Skillful prediction of the SAM beyond ϳ10 days has for that visit and for funding provided by the National not yet been demonstrated. However, it is likely that Science Foundation Climate Dynamics Program. the SAM is predictable on seasonal time scales via its apparent relationship to ENSO (L’Heureux and REFERENCES Thompson 2006). Additionally, there is growing evidence that low-frequency variations in the Southern Ansell, T. J., C. J. C. Reason, I. N. Smith, and K. Keay, 2000: Evidence for decadal variability in southern Australian rain- Hemisphere stratosphere—driven either by internal at- fall and relationships with regional pressure and sea surface mospheric dynamics or polar ozone depletion—are dy- temperature. Int. J. Climatol., 20, 1113–1129. namically linked to changes in the tropospheric flow Arblaster, J. M., and G. A. Meehl, 2006: Contributions of external that resemble the SAM (Thompson et al. 2005). Al- forcings to southern annular mode trends. J. Climate, 19, though the SAM is thought to interact with the South- 2896–2905. ern Ocean (e.g., Hall and Visbeck 2002) and that this Cai, W. J., P. H. Whetton, and D. J. Karoly, 2003: The response of the Antarctic Oscillation to increasing and stabilized atmo- interaction may increase the persistence of the SAM spheric CO2. J. Climate, 16, 1525–1538. (Watterson 2001), useful enhancement of predictability Fyfe, J. C., G. J. Boer, and G. M. Flato, 1999: The Arctic and arising from the interaction with the Southern Ocean Antarctic Oscillations and their projected changes under glo- has yet to be demonstrated. bal warming. Geophys. Res. Lett., 26, 1601–1604. The SAM has contributed to much of the observed Gillett, N. P., and D. W. J. Thompson, 2003: Simulation of recent Southern Hemisphere climate change. Science, 302, 273–275. increases in rainfall over southeastern Australia and ——, T. D. Kell, and P. D. Jones, 2006: Regional climate impacts eastern Tasmania and the decreases in rainfall over of the Southern Annular Mode. Geophys. Res. Lett., 33, western Tasmania during the austral summer season for L23704, doi:10.1029/2006GL027721. the period 1979–2005. However, there is little evidence Hall, A., and M. Visbeck, 2002: Synchronous variability in the that the SAM has contributed to seasonal precipitation Southern Hemisphere atmosphere, sea ice, and ocean result- changes over Australia during other seasons in the past ing from the annular mode. J. Climate, 15, 3043–3057. 25 yr. It would be interesting to examine the possible Haylock, M. R., and Coauthors, 2006: Trends in total and extreme South American rainfall in 1960–2000 and links with sea sur- impacts of the SAM on Australian climate changes that face temperature. J. Climate, 19, 1490–1512. occurred prior to the start of our analysis in 1979, but Hendon, H. H., and B. Liebmann, 1990: A composite study of such an analysis is hampered by the availability of re- onset of the Australian summer monsoon. J. Atmos. Sci., 47, liable indices of the SAM in the presatellite era (e.g., 2227–2240. Marshall 2003). Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Re- analysis Project. Bull. Amer. Meteor. Soc., 77, 437–471. The SAM also appears to have mitigated some of the Karoly, D. J., 1990: The role of transient eddies in the low-fre- longer-term increase in temperature across Australia, quency zonal variations in the Southern Hemisphere circula- which has been attributed to increasing greenhouse tion. Tellus, 42A, 41–50. gases and other anthropogenic forcing (Karoly and ——, and K. Braganza, 2005: Attribution of recent temperature Braganza 2005). In conjunction with the recent upward changes in the Australian region. J. Climate, 18, 457–464. trend of the SAM during summer, maximum summer- Kidson, J. W., 1988: Indices of the Southern Hemisphere zonal wind. J. Climate, 1, 183–194. time temperatures across southern and eastern Austra- Kushner, P. J., I. M. Held, and T. L. Delworth, 2001: Southern lia have warmed less or even leveled relative to the Hemisphere atmospheric circulation response to global longer-term upward trend. As much of the positive warming. J. Climate, 14, 2238–2249. summertime trend in the SAM has been attributed to Lavery, B., G. Joung, and N. Nicholls, 1997: An extended high- the Antarctic ozone hole (Thompson and Solomon quality historical rainfall dataset for Australia. Aust. Meteor. 2002; Gillett and Thompson 2003), it would be interest- Mag., 46, 27–38. ing to see if 1) climate model simulations of recent L’Heureux, M. L., and D. W. J. Thompson, 2006: Observed relationships between the El Niño–Southern Oscillation and the climate change exhibit a mitigating effect of strato- extratropical zonal-mean circulation. J. Climate, 19, 276–287. spheric ozone depletion on greenhouse gas warming in Li, Y., W. Cai, and E. P. Campbell, 2005: Statistical modeling of southern and eastern Australia during summer, and 2) extreme rainfall in southwest Western Australia. J. Climate, the predicted future recovery of the Antarctic ozone 18, 852–863. hole minimizes the effect of the SAM on Australian Lorenz, D. J., and D. L. Hartmann, 2001: Eddy–zonal flow feed- temperature trends. back in the Southern Hemisphere. J. Atmos. Sci., 58, 3312– 3327. ——, and ——, 2003: Eddy–zonal flow feedback in the Northern Acknowledgments. Comments on an earlier version Hemisphere winter. J. Climate, 16, 1212–1227. of the manuscript by B. Timbal and P. Hope are appre- Marshall, G. J., 2003: Trends in the Southern annular mode from ciated. This work was initiated when DT visited BMRC observations and reanalyses. J. Climate, 16, 4134–4143.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC 1JUNE 2007 HENDON ET AL. 2467

McBride, J. L., and N. Nicholls, 1983: Seasonal relationships be- ——, R. L. Miller, G. Schmidt, and L. Pandolfo, 1999: Simulation tween Australian rainfall and the Southern Oscillation. Mon. of recent northern winter climate trends by greenhouse-gas Wea. Rev., 111, 1998–2004. forcing. Nature, 399, 452–455. Meneghini, B., I. Simmonds, and I. N. Smith, 2007: Association Silvestri, G. E., and C. S. Vera, 2003: Antarctic Oscillation signal between Australian rainfall and the Southern Annular Mode. on precipitation anomalies over southeastern South America. Int. J. Climatol., 27, 109–121. Geophys. Res. Lett., 30, 2115, doi:10.1029/2003GL018277. Miller, R. L., G. A. Schmidt, and D. T. Shindell, 2006: Forced Smith, C. A., and P. Sardeshmukh, 2000: The effect of ENSO on annular variations in the 20th century Intergovernmental the intraseasonal variance of surface temperature in winter. Panel on Climate Change Fourth Assessment Report models. Int. J. Climatol., 20, 1543–1557. J. Geophys. Res., 111, D18101, doi:10.1029/2005JD006323. Mills, G. A., G. Weymouth, J. Lorkin, M. Manton, E. Ebert, J. Smith, I. N., 2004: An assessment of recent trends in Australian Aust. Meteor. Mag., Kelly, D. Jones, and G. deHoedt, 1997: A national objective rainfall. 53, 163–173. rainfall analysis system. BMRC Techniques Development Thompson, D. W. J., and J. M. Wallace, 2000: Annular modes in Rep. 1, Bureau of Meteorology, Melbourne, Australia, 30 pp. the extratropical circulation. Part I: Month-to-month vari- Mo, K. C., and G. H. White, 1985: Teleconnections in the South- ability. J. Climate, 13, 1000–1016. ern Hemisphere. Mon. Wea. Rev., 113, 22–37. ——, and S. Solomon, 2002: Interpretation of recent Southern Nicholls, N., 2003: Continued anomalous warming in Australia. Hemisphere climate change. Science, 296, 895–899. Geophys. Res. Lett., 30, 1370, doi:10.1029/2003GL017037. ——, M. P. Baldwin, and S. Solomon, 2005: Stratosphere– Power, S., F. Tseitkin, S. Torok, B. Lavery, R. Dahni, and B. troposphere coupling in the Southern Hemisphere. J. Atmos. McAvaney, 1998: Australian temperature, Australian rainfall Sci., 62, 708–715. and the Southern Oscillation, 1910–1992: Coherent variabil- Torok, S. J., and N. Nicholls, 1996: A historical annual tempera- ity and recent changes. Aust. Meteor. Mag., 85–101. 47, ture data set for Australia. Aust. Meteor. Mag., 45, 251–260. Reason, C. J. C., and M. Rouault, 2005: Links between Antarctic Oscillation and winter rainfall over western South Africa. Trenberth, K. E., 1979: Interannual variability of the 500 mb zonal-mean flow in the Southern Hemisphere. Mon. Wea. Geophys. Res. Lett., 32, L07705, doi:10.1029/2005GL022419. Rev., 1515–1524. Rogers, J. C., and H. van Loon, 1982: Spatial variability of sea 107, level pressure and 500 mb height anomalies over the South- Trewin, B. C., and A. C. F. Trevitt, 1996: The development of ern Hemisphere. Mon. Wea. Rev., 110, 1375–1392. composite temperature records. Int. J. Climatol., 16, 1227– Shindell, D. T., and G. A. Schmidt, 2004: Southern Hemisphere 1242. climate response to ozone changes and greenhouse gas in- Watterson, I. G., 2001: Zonal wind vacillation and its interaction creases. Geophys. Res. Lett., 31, L18209, doi:10.1029/ with the ocean: Implications for interannual variability and 2004GL020724. predictability. J. Geophys. Res., 106, 23 965–23 976.

Unauthenticated | Downloaded 10/04/21 10:07 AM UTC