Regional climate response to late twentieth century warming over the ...

GEOPHYSICAL RESEARCH LETTERS, VOL. ???, XXXX, DOI:10.1029/,

Regional climate response to late twentieth century warming over the Indian Ocean J. J. Luffman Climate Change Research Centre, University of New South Wales, Australia

1989; Ansell and Reason 2000). A gradient of SST anomalies between the Indonesian region and the central Indian Ocean identified by Nicholls (1989) was found to be associated with the leading rotated principal component of Australian winter rainfall, accounting for 30% of the total variance in district average rainfall. The air-sea processes by which this SST anomaly pattern controls northwest cloudband activity were described by Ansell and Reason (2000), whereby southeasterly wind anomalies off the Sumatran coast drive enhanced upwelling and a resultant localised cooling of SST, reducing the SST gradient described by Nicholls (1989) and hence the number of rainfall producing cloudbands reaching southeastern Australia. Modes of variability unique to the Indian Ocean have recently been identified, and are now understood as important drivers of Australian climate variability. The Indian Ocean Dipole (IOD) was described by Saji et al. (1999) as a temporary modification to the east-west structure of the tropical wind field, which can be measured as the difference between SST in the western and eastern tropical Indian Ocean. The IOD exhibits significant negative correlations with rainfall over western and southern Australia, including the southeast of the continent (Ashok et al. 2003). Positive IOD events enhance the subtropical jet (Ashok et al. 2006), causing the midlatitude storm track over southern Australia and New Zealand to shift southward, leading to lower precipitation rates. Another dipole mode in Indian Ocean SST has been proposed by England et al. (2006) to explain interannual variability of southwest Western Australian (SWWA) rainfall. The SST anomalies are linked to the wind field through Ekman transport and air-sea heat fluxes, and the associated dipole mode index has a higher correlation with rainfall over SWWA than the corresponding time series for the IOD. Despite these studies of Indian Ocean climate variability, no analysis of the impact of Indian Ocean warming upon regional climate has been conducted. In this study, we investigate the regional climate response to a warming Indian Ocean, using an ensemble set of experiments with an Atmospheric General Circulation Model (AGCM) forced with the linear trend component of observed SST during the late 20th Century. The remainder of this thesis is structured as follows: in Chapter 2 the observed late 20th Century changes to the Indian Ocean and to Australian climate are described. The configuration and forcing of the model experiments are outlined in Chapter 3. The forced changes to the atmospheric circulation are detailed in Chapter 4, and the resultant model rainfall trends are analysed in Chapter 5. Finally, a discussion and conclusions are given in Chapter 6.

The regional climate response to a warming of the Indian Ocean is examined in an ensemble of atmospheric general circulation model experiments. The warming trend of the Indian Ocean was found to reorganise horizontal and vertical atmospheric circulation patterns across the globe, with the most marked changes over the Indian Ocean region also extending over the surrounding continents of Asia and Australia. The increase in tropical SST across the basin was found to drive an enhanced deep convection throughout the depth of the troposphere, with convective outflow in the upper levels leading to a subsiding trend in the Southern Hemisphere tropics, taking a maximum at 130-160◦ E to the north and northeast of Australia. The drying induced by this anomalous zone of subsidence is exacerbated over the northeast of the Australian continent by the anomalous anticyclonic circulation, which leads to an offshore trend in near-surface winds. The confluence of these two factors leads to a strong drying signal over northeastern Australia, with significant modeled rainfall decreases as large as 800 mm per century in some areas, quantitatively similar to the observed trends. We thus conclude that the rapid late 20th Century warming of the Indian Ocean may have contributed to the observed drying trend of northeastern Australia, via modifications to the vertical structure of the tropical wind field.

1. Introduction The Indian Ocean plays a fundamental role in determining Australian climate. Changes in sea surface temperature (SST) in the Indian Ocean can be linked to a significant proportion of rainfall variability across the continent (e.g., Nicholls 1989; Drosdowsky and Chambers 2001; England et al. 2006). Apart from varying seasonally and interannually, the basin-averaged Indian Ocean SST has increased since 1970 at a rate of 0.93◦ C per century, with local rates as high as 2.92◦ C per century (using SST from Smith and Reynolds 2004). Significant trends in Australian rainfall patterns have also been observed over this period (e.g., Smith 2004; Rotstayn et al. 2007). At present, the extent to which the Indian Ocean warming trend is driving changes to Australian climate remains unknown. One of the aims of this study is to determine to what extent the warming of the Indian Ocean can account for observed climate trends over Australia. Seasonal and interannual variability of Australian rainfall has been explored extensively in previous studies (e.g., O’Mahony 1961; Pittock 1975; Drosdowsky 1993; Power et al. 1998). Such studies are generally motivated by the ultimate goal of improving seasonal rainfall predictions, and some have led to the development of predictive indices using lagged relationships with SST in the Pacific and Indian Oceans (e.g., Drosdowsky and Chambers 2001; Watterson 2001). SST patterns in the Indian Ocean can account for a significant proportion of interannual variations in Australian rainfall (Nicholls

2. Observed Regional Climate Trends 2.1. Warming of the Indian Ocean . The Indian Ocean has experienced a marked upward trend in SST over recent decades. Whilst the trend in Indian Ocean SST has become more apparent in recent years, it was already noted in earlier studies in the context of trends in Australian rainfall (e.g., Allan and Haylock 1993). The warming trend has been significant across most of the basin, with only a small area east of Madagascar showing a decreasing trend (Figure 1). Based on NOAA extended reconstructed SST data (Smith and Reynolds 2004), the basin-average warming since 1970 has been 0.93◦ C per century, with values as high as 2.92◦ C per century in southern equatorial regions. The spatial pattern of the trend during 1900-1970 and 1970-1999 is shown in Figure 1.

Copyright 2007 by the American Geophysical Union. 0094-8276/07/$5.00

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Figure 1. Estimated linear trends in Indian Ocean SST (◦ C per century) 1900-1970 (left), 1970-1999 (right) after Rayner et al. (2003). Taken from IPCC Fourth Assessment Report (IPCC 2007).

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Figure 2. Linear trends in seasonal SST (◦ C per century) in the Indian Ocean over the period 1970-2005. Data used to compute seasonal trends was taken from the NOAA ExtendedReconstructed SST dataset (Smith and Reynolds 2004). The trend in SST over the Indian Ocean exhibits only minimal seasonal variation (Figure 2), perhaps unsurprising given the high persistence of SST on monthly time scales. This uniformity between seasons in both spatial pattern and magnitude also suggests that forcing mechanisms for the trend are likely to operate over significant temporal and spatial scales, such as anthropogenic climate change. Another characteristic of the SST increase is a marked variability over interannual and decadal time scales, seen in the time series of basin-averaged SST (Figure 3). Despite these variations, the most notable feature of the temperature record is the long-term trend seen during 1970-2005. The most likely cause for the warming in global SST is increasing greenhouse gas (GHG) concentrations, with a positive net radiative forcing causing a heating of the sea surface (Levitus 2005). Under increasing GHG scenarios, climate models also project a poleward shift in the position of zero mean zonal wind stress in the Southern Hemisphere, as the subpolar westerly winds increase and shift southward (Saenko et al. 2005). Using output from 10 different GCM’s, Alory et al. (2007) argue that a 0.5◦ poleward expansion of the Indian Ocean subtropical gyre can account for much

Figure 3. Time series of annual Indian Ocean basin-averaged SST (◦ C) between 20◦ S-20◦ N and 40◦ E-110◦ E. Anomalies are relative to the 1970-2005 climatology. Data used to compute the time series was taken from the NOAA Extended-Reconstructed SST dataset (Smith and Reynolds 2004). of the observed subtropical warming of the Indian Ocean over the same period. The authors base this argument on the premise that a southward shift of the gyre circulation results in a southward shift of the gyre’s thermal structure, causing an increase in subtropical SST. Despite this mechanism for the subtropics, it is almost certain that the Indian Ocean warming of the past 30 years is forced, to a large extent, by radiative flux changes controlled by increasing GHG’s. Whilst the subject of Indian Ocean variability and teleconnections with Australian climate has been studied extensively, the role of this emerging SST trend has received far less attention. The sustained SST trend in the Indian Ocean will almost certainly modulate the historic teleconnections from this region, via for example the IOD, to Australian rainfall. The observed warming in Indian Ocean SST adjacent to Africa has been suggested to force a net shift of convection from land towards the ocean, reducing rainfall in the Sahel region (Giannini et al. 2003). An ensemble set of GCM experiments forced only with observed SST over the period 1930-2000 exhibits a low frequency trend in precipitation over the Sahel similar to observations, with a marked drying from the 1960’s to the 1980’s. Whilst correlations between Sahel rainfall and SST are highest in the western and

LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING northern Indian Ocean (Giannini et al. 2003), some distance from Australia, this study shows that low frequency trends in precipitation can be accounted for by corresponding trends in Indian Ocean SST. It has also been argued that the warming of the tropical Indian Ocean might have contributed to unusually dry and warm conditions over North America and western Europe over 1998-2002 (Hoerling and Kumar 2003), using observational data and GCM experiments. The authors considered both warm Indian and Pacific tropical SST anomalies simultaneously, and hence it is unclear whether the Indian Ocean warming alone was driving the teleconnection, or indeed the Pacific Ocean warming, or a combination of the two. A subsequent study considered tropical Indian Ocean SST’s as a separate case, and found that a large proportion of the observed Northern Hemisphere circulation changes over the late 20th Century could be forced simply by the linear trend in Indian Ocean SST’s (Hoerling et al. 2004). The authors also found that in 80% of model realisations forced only with warm Indian Ocean SST, the North Atlantic Oscillation (NAO) index exhibited a positive trend, leading to a decrease in precipitation over the Mediterranean region and an increase over northern continental Europe.

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Figure 5. Linear trends in seasonal mean precipitation over the period 1971-2005 (mm per century) estimated from a monthly gridded rainfall dataset interpolated from high quality station data (Lavery et al. 1997).

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More recently, the observed warming of Indian Ocean SST was found to project onto observed trends in the Arctic Oscillation in the Northern Hemisphere midlatitudes (Minvielle et al., submitted 2006). The warming of tropical Indian Ocean surface waters was suggested to lead to an intensified deep convection in the atmosphere, and subsequent modification of the Hadley cell and subtropical jet. It is as yet unknown whether such a mechanism exists in the Southern Hemisphere, and indeed what the impacts on Australian climate might be. In Chapter 3 we outline the design of model experiments used to isolate the nature of atmospheric modifications arising from a warming of the Indian Ocean. 2.2. Recent Trends in Australian Rainfall On decadal and longer time scales, a number of trends have emerged in Australian rainfall patterns. The trends are significant across a large area of the continental landmass, and broad spatial patterns have been observed (Figure 4). A decrease in rainfall over SWWA during much of the 20th Century has been extensively documented (e.g., Wright 1971; Pittock 1975; Sadler et al.1988; Allan and Haylock 1993). Explanations for this trend have included a low frequency modulation of the long wave trough southwest of the continent (Allan and Haylock 1993), a reduction in land surface roughness due to land clearing (Pitman et al. 2004) and anthropogenic forcing by GHG, ozone and aerosols (Timbal et al. 2006). It has been suggested by Nicholls (2006) that a combination of these factors is likely to have produced the observed decrease. A positive trend in rainfall over central western and northwestern Australia over the 20th Century is described by Smith (2004), significant at the 95% confidence level across a broad spatial domain. In the central west of the continent the increase in annual rainfall was found to be 109% per century, over a spatial pattern similar to that identified by Nicholls (1989), which he found to be strongly correlated to SST patterns in the Indian Ocean. Rainfall over eastern Australia has exhibited a general decline during the second half of the 20th Century, with no detailed studies to date on the subject. The negative trend has been particularly pronounced over the northeast, where decreases in mean annual rainfall have been as large as 200mm per decade since 1971 (estimated from Bureau of Meteorology gridded rainfall data). There is some speculation that the decrease along the east coast could be due to an increased frequency of El Ni˜no events in the late 20th Century, driven by increasing GHG concentrations (Rotstayn et al. 2007). However, to date no significant linear trend has been observed in the Southern Oscillation Index (SOI), and it is unclear whether changes in El Ni˜no activity over the late 20th Century could have forced the observed East Coast drying trend. Trends in Australian rainfall also exhibit a seasonality component as the underlying mechanisms are superimposed upon the annual cycle of rainfall bearing flow regimes. The seasonal trends over 1971-2005 are shown in Figure 5. The strongest trends are present at the height of the northern wet season (DJF) when a substantial increase has occurred in the northwest, with a drying of even greater magnitude observed over the northeast. During autumn (MAM) weaker trends exist, with the signature being a decrease in both the far northeast and the far southeast. The austral winter (JJA) sees a moderate drying over much of the continent, except over western Tasmania and along the east coast poleward of 30◦ S where moderate increases have occurred. During spring (SON), a strong band of increasing rainfall extends from the northwest to the east, also covering a large area of the western interior. These trends in rainfall warrant further investigation, especially considering their continuation into the early part of the 21st Century. Given the extensive linkages between Australian climate and the Indian Ocean on seasonal to interannual time scales, the role of lower frequency variability and trends in the Indian Ocean need to be examined further.

3. Climate Model and Experimental Design 3.1. Atmospheric Model The atmospheric model used in this study is the Community Atmosphere Model version 3 (CAM3), developed by the National Centre for Atmospheric Research (NCAR). The CAM3 is

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the AGCM component of the Community Climate System Model (CCSM), a coupled climate model consisting of ocean, ice, land and atmosphere models. In this study, the CAM3 is coupled only with the Community Land Model, which is described in section 3.2. The configuration of CAM3 chosen for this study uses Eulerian spectral dynamics with a triangular truncation at wavenumber 42. The resulting T42 horizontal resolution is approximately 2.8◦ in both latitude and longitude. In the vertical, the model consists of 26 levels in a hybrid sigma-pressure system. Vertical levels above 85hPa are discretised as pressure surfaces only, while the lower levels are pure sigma. Deep convection in the model is parameterised using the the simplified cumulus scheme proposed by Zhang and McFarlane (1995), whereby convective-scale updrafts can occur when the lower troposphere is conditionally unstable. The treatment of shallow convection in CAM3 incorporates the scheme of Hack (1994) using a three-level cloud model with stability dependant mass flux. Non-convective cloud processes are treated in CAM3 by the formulation introduced by Rasch and Kristjansson (1998). Proportions of liquid and ice phase condensate are determined using the temperature of the surrounding air-mass. The condensate can then be evaporated or converted to precipitation depending on both resolved and unresolved atmospheric processes. This parameterisation consists of a macroscale component controlling exchange between vapour and condensate phase, and a microphysics component that determines evaporation and precipitation of condensate. Precipitation may be in the form of rain or snow, or a mixture of both. The atmospheric boundary layer is treated in CAM3 with an explicit non-local boundary layer scheme as described by Holtslag and Boville (1993). This scheme accounts for conditions when eddies within the boundary layer reach a similar size to the boundary layer depth itself, allowing a more realistic treatment of transport by such eddies. The AGCM is forced by prescribed global monthly SST values, as well as sea-ice fraction, linearly interpolated at each time step to form the bottom boundary conditions for the atmosphere. The model forcing by a set of SST values allows for a direct examination of dynamical processes operating between the ocean surface and atmosphere, and is also computationally inexpensive compared with a complete coupled ocean-atmosphere model. A more thorough description of CAM3 is given by Collins et al. (2006).

is designed to provide surface albedos, upward longwave radiation, sensible and latent heat fluxes, water vapour flux and zonal and meridional surface stresses for the atmospheric model. These exchanges with the atmosphere are modified by a number of hydrological and ecological processes. The structure, composition and phenology of vegetation is treated, as well as stomatol physiology and photosynthesis. Modelled hydrology components include treatments of forest canopy, snow, soil, lakes and river runoff into the ocean. Also included in CLM3 are parameterisations of subgrid surface composition, based on satellite observations of lakes, wetlands, glaciers and vegetation types. Energy and moisture fluxes are treated separately for each of these surface types. By allowing for the treatment of these basic land-atmosphere interactions, the implementation of a land model produces a more realistic simulation of the climate system response to the imposed SST forcing. A more detailed description of CLM3 is given by Bonan et al. (2002) and Oleson et al. (2004). 3.3. Model Simulation of Australian Climate This section is intended to give an overview of the model’s performance in simulating Australian climate, and Australian rainfall in particular. Precipitation is typically one of the most difficult climatological variables to capture, due to the largely subgrid nature

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Figure 6. Comparison of observed (left) and modeled (right) annual mean precipitation (mm) over Australia. The modeled mean values are taken from a CAM3 control run forced by a monthly varying SST climatology computed over 1970-1999. Observed values are annual averages over the same period computed from a monthly gridded rainfall dataset interpolated from high quality station data (Lavery et al. 1997).

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Figure 7. Comparison of observed (left) and modeled (right) seasonal mean precipitation (mm) over Australia. The modeled mean values are taken from a CAM3 control run forced by an SST climatology computed over 1970-1999. Observed values are seasonal averages over the same period computed from a monthly gridded rainfall dataset interpolated from high quality station data (Lavery et al. 1997).

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING of convective processes and cloud physics. Despite this challenge, CAM3 is able to reproduce the continental-scale features of Australian rainfall. A comparison of the model’s climatological annual mean rainfall and observed values over Australia is given in Figure 6. The model is able to simulate the area of higher precipitation across the north of Australia due to the summer monsoon, and also the relatively wet east coast where prevailing winds are onshore. The large area of low precipitation over the inland of the continent is also well captured by the model, although rainfall over inland Queensland is too high. The small area of higher precipitation in the far southwest corner of the continent is poorly reproduced, as is the marked east-west gradient across the island of Tasmania. These deficiencies may be attributed to the model’s relatively coarse horizontal resolution, especially over Tasmania where fine-scale orographic features will be smoothed. The simulation of seasonal climate features over the Australian region is also of importance when analysing the dynamic nature of imposed modifications to the atmospheric circulation. The model’s reproduction of temporal patterns in rainfall across the Australian continent is evaluated in Figure 7 in a comparison between seasonal mean rainfall from the model climatology and the corresponding observed values. In the model, the monsoon begins too early in the austral summer and is more intense than in reality, particularly over the Pilbara and Kimberley regions in the northwest of the continent. This disparity is in line with the global overestimation by CAM3 of tropical precipitation, as shown by Hack et al. (2005). The model precipitation climatology does exhibit a wintertime increase over the southwest and southeast of the continent, but of smaller magnitude than the observed increase. This may be due to the relatively low resolution of the model, and also its tendency to place the subtropical ridge too far to the south (Hack et al. 2005). Rainfall along the east coast of Australia is well captured across all seasons, especially when considering the relatively low resolution of the model, which limits the representation of orographic effects for moist onshore air-streams. 3.4. Experimental Forcing and Configuration The premise of our experimental design is to analyse the modifications to regional climate forced by the observed warming of the Indian Ocean. We are interested only in the regional climate modifications arising from the lowest frequency aspects of the observed SST changes; i.e. the linear trend component. By conducting experiments forced only by the changes to Indian Ocean SST, we

can elucidate the response of the regional climate in isolation from other potential forcing agents. Outside the Indian Ocean, the model is forced by monthly varying global climatological SST and sea-ice fraction data. The climatological values for each month are computed from the HadISST1 dataset (Rayner et al. 2003) about the initial year 1970 and interpolated onto the model grid. The Indian Ocean region is defined as the ocean basin north of 25◦ S, bordered to the west by the African continent, to the east by the Indonesian archipelago and to the north by the Asian continent. Within this Indian Ocean region, a linear trend over the period 1970-2005 is fitted to the historical SST time series at each model gridpoint, using the HadISST1 dataset, with a mean 1970-2005 SST change of +0.93◦ C per century over the basin. The linear trend in SST at each gridpoint is added to the monthly climatological values over the period 1970-2005, so that the only variability in SST is the seasonal cycle superimposed upon the observed linear trend (Figure 8). At 15◦ S , a ramp of width 10◦ in latitude is used to border the forced region to minimise edge effects, and across this ramp the imposed trend is damped linearly to a value of zero at the outside boundary. The forcing region and magnitude of imposed linear SST trends is shown in Figure 9. In addition, we examined an ensemble set of four experiments with the same Indian Ocean trend, but additionally a trend in SST extending east of the Indonesian archipelago into the Pacific Ocean to 130◦ E. Our main findings are robust across both experiments, indicating that the climate response in the Indian Ocean experiments is not a consequence of the particular forcing region geometry used, but the result of gradual sea temperature warming across the Indian Ocean. In order to filter out the internal variability generated by the atmosphere, including the weather transients, an ensemble of experiments was carried out with identical SST forcing as described above, but each with slightly varied atmospheric initial conditions. The number of ensemble members was 5, yielding a total of 175 years of integration time. Whilst there is no upper bound on the number of integrations desired, the computational load of this ensemble size is already substantial. In addition, we employ a bootstrap statistical analysis to quantify which aspects of the climate trends are significant. In Chapters 4 and 5 we find a number of major features in the atmospheric circulation common to the output of all five ensemble members, suggesting that this modest ensemble size is more than sufficient for our purposes. Each of the five ensemble members is spun up from September 1970. The atmospheric initial conditions for each member were

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Figure 8. Schematic time series of anomalous model SST (◦ C) forcing at gridpoints inside (red) and outside (black) the Indian Ocean. Indicated SST anomalies are relative to their annual averages based on a climatology centered about the initial year 1970. The SST forcing varies geographically over the Indian Ocean as shown in Figure 3.4. Temperature axis is not drawn to scale.

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

taken from an independent simulation at two day intervals. We then allow a spin up period of 4 months for each member, with 1st January 1971 the first day included in our analysis. This period of spinup time is well beyond the time scale of dynamical predictability, and given the chaotic nature of the atmosphere, we expect the differentiated initial conditions to be sufficient to ensure independence between ensemble members (Graham and Mason 2005). Our version of the HadISST1 dataset used to force the model is complete to December 2005, yielding a total integration time of 35 years for each ensemble member.

4. Atmospheric Circulation Response Here we analyse the circulation changes imposed by the linear trend component of Indian Ocean SST and the mechanisms by which they are projected onto regional climate. In particular, we examine the zonal strucure of the global response, the circulation changes in the Australian region and their impact upon the advection of moisture. Because our ensemble experiment set is forced only by the seasonal cycle of SST plus the linear trend over the Indian Ocean, the atmospheric response we obtain can be interpreted as a linear approximation to the signal of a warming Indian Ocean. The significance of modeled trends is determined using the bootstrapping method described by Efron (1982; see also Appendix A). This technique can be particularly effective in dealing with climate data from non-Gaussian fields, as other hypothesis tests often make invalid assumptions about the normality of the sampling distribution (Kiktev et al. 2003). Our approach determines whether the mean of the bootstrap distribution of ensemble members at each model gridpoint is significantly different from zero at the 90% confidence level using a bootstrap-t test, the details of which are given in Appendix A. 4.1. Global Response to Indian Ocean Warming A global response to the warming Indian Ocean can be seen in zonally-averaged zonal winds (Figure 10) throughout the depth of the troposphere, suggesting a large-scale reorganisation of the wind field at multiple levels in response to the imposed surface heating. The trends in the Northern Hemisphere extratropics resemble the zonal wind anomaly structure of the positive phase of the Northern Annular Mode (NAM) shown by Thompson et al. (2003), with an increase in westerlies north of about 45◦ N and a weakening to the south. To investigate this modification further we conduct an Emperical Orthoganal Function (EOF) analysis of modeled sea level pressure (SLP) poleward of 20◦ latitude. This EOF analysis adopts the method of North et al. (1982) to elucidate the spatial pattern and principal component time series of the NAM and SAM indices under the condition of a warming Indian Ocean, the results of which are shown in Figures 11 and 12. In the Northern Hemisphere the spatial pattern of the leading EOF mode (Figure 11) resembles the SLP signature of the NAM, with positive correlations extending from North America to Western Europe, and also over the North Pacific. The principal component time series for the leading EOF mode (Figure 12) exhibits a strong positive trend, found to be significant at the 90% confidence level using a bootstrap-t test. This result is consistent with the findings of Hoerling et al. (2004) – suggesting that a positive trend in the NAM, and the associated regional climate change in the Northern Hemisphere extratropics, can be forced solely by a warming Indian Ocean. In the Southern Hemisphere the strongest feature in zonal winds (Figure 10) is an enhancement of the subtropical jet, driven by divergent outflow associated with increased convection over the tropical Indian Ocean. The positive trend in zonal winds associated with this enhancement is largest near 200 hPa, but also extends to the surface from 20-40◦ S, corresponding to a weakening of the subtropical easterly tradewinds in this band. Over the Southern Hemisphere extratropics the pattern of zonally-averaged trends is weaker than that exhibited in the Northern Hemisphere, and has a different zonal and vertical structure. The spatial pattern of the leading

EOF in Southern Hemisphere SLP (Figure 11) has a roughly annular form similar to observations (Sen Gupta and England 2006), although negative correlations extend equatorward at the Indian Ocean longitudes. The principal component time series (Figure 12) for the leading EOF shows little trend component, with a weak negative trend that was found to be not significant at the 90% confidence level, using a bootstrap-t test. Given these results we conclude that it is very unlikely the observed positive trend in the SAM (Marshall 2003) has been forced in any significant way by a warming of Indian Ocean SST. Other causal factors, such as changes to ozone (Gillett and Thompson 2003) and GHG (Cai et al. 2003), have clearly played a greater role. 4.2. Regional Changes to Vertical Circulation The direct response to the warming of Indian Ocean SST is an enhanced deep convection in the atmosphere, clearly visible in Figure 13(a) as an increase in upward motion over the tropical Indian Ocean. This feature in our experiments is consistent with the results of Giannini et al. (2003), who found that the observed SST warming caused preferential and increased convection over the Indian Ocean. We find this trend toward enhanced uplift over the ocean to be a robust response, present in each of the five ensemble members. The convection driven uplift over the tropical Indian Ocean leads to upper-tropospheric divergence, visible in the divergent component of horizontal winds at 220 hPa in Figure 13(a). At lower levels a marked convergence in near-surface winds can also be seen over much of the tropical Indian Ocean (Figure 13(b)), causing a reorganisation of the local wind field in the region. Further east is a corresponding suppression of tropical convection to the north and northeast of Australia, seen as a broad area of subsiding air and associated upper level convergence extending from the eastern end of the Indonesian archipelago to the Coral Sea. The zonal and vertical structure of the vertical velocity anomalies is examined in Figure 14, revealing that the strong east-west sign reversal seen in the 500hPa velocities is consistent throughout the depth of the troposphere. The subsidence trend in the Southern Hemisphere tropics from 125◦ -160◦ E induces an anomalous divergent anticyclonic circulation in near surface winds over northern and northeastern Australia (Figure 13(b)). The result of this broad anomalous anticyclone is a weakening of the subtropical easterlies over Australia from 15◦ 35◦ S, causing an offshore trend in winds over the northeast of the continent and an onshore trend in the west. These changes likely have implications for Australian rainfall, as will be discussed later. Another vertical circulation response to the imposed SST warming is enhanced uplift over the southern Indian Ocean, outside our

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Figure 12. Annual means of the principal component time series of the first EOF of Southern (left) and Northern (right) Hemisphere monthly SLP (hPa) poleward of 20◦ latitude for the ensemble mean of the Indian Ocean warming experiments. region of forced warming. Surface winds reveal an anomalous cyclonic circulation centered near 70◦ E, 40◦ S and enhanced westerlies from 30-40◦ S - indicating that the storm track over the southern Indian Ocean has been enhanced. This increased cyclogenesis over the southern Indian Ocean is also apparent in the spatial structure of the model SAM (Figure 11), where the annular structure deviates equatorward from 40◦ -80◦ E. While we do not conduct a detailed analysis of the model storm track trends, the enhancement of midlatitude depressions over the southern Indian Ocean in the model is likely a result of the increased meridional temperature gradient arising from the warmed tropical SST. It is also likely as a result of the increase in moisture content of the pre-frontal air-mass from 70◦ -90◦ E, where lifting results in condensation and the release of latent heat, warming the air-mass significantly and resulting in further intensification of midlatitude systems. 4.3. Regional changes to Moisture Advection Here we analyse the nature of changes to advection of moisture in the middle and lower troposphere arising from the warming of the Indian Ocean. Figure 15 shows the trend in specific humidity and winds, integrated over the four model levels from 800-500 hPa. In a model climatology taken from a control run forced by a repeating cycle of mean monthly SST during 1970-1999, these four levels account for 56% of global-averaged moisture transport, calculated

using the bulk formula Q · kU k, from a total of 26 vertical levels in the model. Figure 15 shows that the increased uplift over the tropical Indian Ocean and subsidence to the north and northeast of Australia result in an east-west dipole in specific humidity trends over these areas. This dipole is consistent with the vertical circulation described in section 4.2 above, and is a robust feature seen in each of the five ensemble members. Over the tropical Indian Ocean, warmer SST’s increase evaporation rates and lead to higher specific humidities, while the deep convection drives a strong convergence of the tropical wind field. Further east, the anomalous anticyclonic circulation centered near 130◦ E, 10◦ S coincides with an area of decreasing moisture that takes a maximum value directly over northeastern Australia. This region of atmospheric drying coincides with the region of anomalous subsidence seen in Figure 13(a). Over northeastern Australia the subsidence-induced drying is exacerbated by the induced anticyclonic circulation, causing an offshore trend in horizontal wind, both at the surface (Figure 13 b) and integrated over 800-500 hPa. This southwesterly trend opposes the ’northerly’ wind pattern of Watterson (2001), which was found in a model simulation to be correlated with monthly rainfall over northeastern Australia with coefficients greater than 0.80 in both January and July. Over northern Australia, the decreasing trend in specific

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

humidity combines with an easterly trend in near surface winds north of 15◦ S and east of 125◦ E (Figure 13 b) to weaken the northwesterly monsoon surge in this region. In Chapter 5 we examine how these modifications to the atmospheric circulation project onto rainfall patterns over northern and northeastern Australia. Over Australia’s northwest and west, Figure 15 reveals an increase in specific humidity and an onshore trend in winds. The trends in surface winds and vertical velocity (Figure 13) indicate a weakening of the mean Indian Ocean anticyclone and a southward extension of the Intertropical Convergence Zone (ITCZ) over the Indian Ocean. The ITCZ is progressively shifted away from southern Asia by warmer SST’s in the Indian Ocean, causing a reduced land/sea temperature gradient. The increase in specific humidity over northwestern and western Australia (Figure 15) extends from the tropical Indian Ocean near the mean position of the ITCZ, indicating that the source of the increasing moisture is the enhanced convective activity forced by increasing Indian Ocean SST. 4.4. Seasonal Evolution of Regional Climate Anomalies

likely as the trend forcing is projected onto natural unforced seasonal variability in the atmospheric circulation. In the case of horizontal moisture transport across Australia, we expect that the effect of the trend in Indian Ocean SST will be non-uniform across the different mean flow regimes which typically affect the continent at different times of the year. Specific humidity and wind trends (Figure 16) for the austral summer (DJF) reveal a decrease in atmospheric moisture content over the northeast of the continent associated with the region of subsidence also seen in the annual trends over this region. The centre of this region of anomalous subsidence lies between 15◦ -20◦ S at this time of year as the ITCZ is drawn south toward the strongly heated Australian land-mass. Also evident is a smaller area of increasing specific humidity centered over the northwest of the continent from 120◦ -130◦ E. Trends in moisture transport during the austral autumn (MAM) exhibit a marked dipole in moisture, qualitatively resembling the annual plot (Figure 15) but of greater magnitude, indicating that the atmospheric drying effect over the northeast due to a warming Indian Ocean reaches its maximum in the autumn months. The increasing moisture and wind field convergence associated with

In this section we analyse the seasonal nature of the regional climate response to a warming Indian Ocean. Although the magnitude and spatial pattern of the SST trend forcing is fixed throughout the year, a seasonal component to the atmospheric response is

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Figure 13. Ensemble mean trends in atmospheric circulation over 1971-2005: (a) Vertical velocity (shaded) at 500 hPa (P a·s−1 per century) and divergent component of horizontal wind (arrows) at 220 hPa (m·s−1 per century), (b) Near-surface winds (m·s−1 per century). Trend values determined to be significantly different from zero at the 90% confidence level using a bootstrap-t test are dashed, trend vectors significantly different from zero at the 90% confidence level are shown in black.

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

DJF Trend in 800−500hPa specific humidity and wind

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Figure 16. Ensemble mean seasonal trend integrated over vertical levels in the 800-500 hPa band; specific humidity (g·kg −1 per century) and horizontal wind (m·s−1 per century). Trend values determined to be significantly different from zero at the 90% confidence level using a bootstrap-t test are dashed, trend vectors significantly different from zero at the 90% confidence level are shown in black. enhanced convective activity reaches a maximum over the Indian Ocean at this time of year (Figure 16), with the corresponding area of subsidence over northeast Australia also at a maximum. In MAM the ITCZ is in a transient state, centered near the equator where the observed SST increase since 1970 (Figure 1) has been greatest. With the ITCZ in a mean position over the region of greatest warming, the available thermal energy source for convective instability is maximised and the regional west-east pattern of uplift and subsidence is greatest. The implications of this subsidence and drying response for autumn rainfall trends over northeastern Australia are examined in Chapter 5. With the increasing moisture content of the lower troposphere over the tropical Indian Ocean at a maximum in austral autumn, the annual trend toward increased inflow of moisture over the northwest and west of the continent also reaches a peak during these months. The increasing trend of this moisture advection pathway can be seen clearly in Figure 16, extending from near 90◦ E, 10◦ S to the west of the Australian continent. The resulting model rainfall trends are analysed in Chapter 5. In the austral winter (JJA), patterns of atmospheric moisture trends across northern Australia are weak as the ITCZ is in its maximum northward position, corresponding to the dry season in this region. A strong area of increasing moisture over the Indian Ocean south of the equator is advected toward the southeast as a result of enhanced midlatitude baroclinic eddies over the southern Indian Ocean (Section 4.2), leading to a trend of increasing moisture transport toward western and southern Australia. In the austral spring (SON) the ITCZ would ordinarily be held north over the strongly heated south Asian land-mass, but the warming trend in SST has enhanced deep convection over the tropi-

cal Indian Ocean (Figure 13 a) by weakening the land-sea temperature gradient and drawing the ITCZ southward of its mean climatological position. The increased specific humidity over the southern equatorial Indian Ocean due to this enhanced uplift is evident in Figure 16, as is the drying trend over continental south Asia. With the ITCZ enhanced over the tropical Indian Ocean, there is an increase in eastward advection of moisture south of Java and over subtropical Australia. As the zone of subsidence over northeast Australia has migrated north over the Coral Sea during the austral winter, the significant band of increase in moisture advection from the northwest is able to reach parts of the eastern inland.

5. Modeled Response in Australian Precipitation One of the goals of this study is to analyse the trends in precipitation over Australia occurring in our AGCM ensemble forced only by the trend component of Indian Ocean SST over 1971-2005. Because all other climate system forcings are held steady throughout each integration, the atmospheric response can be interpreted as a result of the linear SST increase in the Indian Ocean. A 35year control integration forced only by the climatological SST values yields a maximum global precipitation trend four times smaller than the maximum trend in the ensemble mean of the trend forced experiments, indicating that some precipitation changes imposed by the linear SST trend in the Indian Ocean are larger than those arising from any internal low-frequency variability in the atmosphere.

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

5.1. Spatial Pattern of Modeled Rainfall Trends The ensemble mean trend in Australian precipitation in the Indian Ocean warming experiments is shown in Figure 17. The most clearly defined features are an increase over the northwest and west of the continent, and a decrease over the north and northeast. Also evident is a smaller area of increase in the east between 25◦ S and 30◦ S, though this feature is not significant at the 90% confidence level over land or over the adjacent Tasman Sea. The largest areas of significance over the continental landmass and surrounding oceans are associated with the increasing trend over the west and the decrease over the northeast. A clear trend evident in the ensemble mean is a drying over the north and northeast of Australia, with the negative trend over land as large as 800 mm per century in some areas. The largest observed decrease over 1971-2005 also lies in the northeast of the continent, with large areas of Arnhem Land and northeast Queensland exhibiting decreases greater than 500 mm per century. We saw in Chapter 4 that enhanced convection over the Indian Ocean produces an anomalous zone of subsidence centered near northeastern Australia, with the induced atmospheric drying exacerbated in this region by an offshore trend in winds. It is therefore not surprising that the largest model decreases in precipitation over Australia in the forced experiment occur over the northeast of the continent. The magnitude and spatial extent of the decreasing trend in modeled precipitation over the northeast of the continent suggest that changes to Indian Ocean SST could account for some of the observed decrease. Whilst the observed drying trend over northeastern Australia reaches west to approximately 130◦ E, the decrease exhibited by our ensemble average extends somewhat further west, to include eastern parts of the Kimberley region. The combination of a drying airmass and modification to the wind field seen in Chapter 4 account for the decrease in model precipitation over northern Australia, particularly in the summer and autumn months (Figure 18) when the monsoon is most active. A similar effect was noted over the African continent by Giannini et al. (2003) whereby the land/sea temperature gradient was reduced, weakening the monsoon mechanism and resulting in a reduction of precipitation over land. The modeled increase over the west and northwest of Australia appears over a large area from the Kimberley region to the southern coastline. Included in this area are some positive trends significant at the 90% confidence level over parts of the northwest coast and

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also the interior of the continent. We saw in Chapter 4 that the increase in onshore moisture transport over the northwest and west of the continent combines with enhanced uplift within the prevailing west coast trough (Figure 13 a), accounting for the modeled increase in precipitation. It has been shown by Smith (2004) that observed rainfall trends over the 20th Century showed their most significant increase over a similar area, however the observed 1971-2005 trends are mostly in the range 100-300 mm per century while our ensemble mean has a maximum increase of only 110 mm per century. A rainfall increase over the northwest of Australia closer in magnitude to the observed was shown by Rotstayn et al. (2007) to appear in experiments including Asian anthropogenic aerosols in a coupled GCM. Whilst the area of increase over northwestern Australia modeled by Rotstayn et al. (2007) extends east to about 135◦ E, our model increase extends to 125◦ E. The observed trends since 1970 (Figure 4) show that the increase extends to near the intermediate meridian at 130◦ E, suggesting that the combined forcings of a warming Indian Ocean and Asian aerosols have operated in concert to produce a significant precipitation trend over this region. Our focus is on the rainfall trends forced by the increase in Indian Ocean SST. It is likely that the additional inclusion of increasing anthropogenic aerosols would produce a modeled rainfall increase over the northwest of Australia closer in magnitude to observations. Over SWWA our ensemble mean shows an increase of 40-120 mm per century as part of the broad increase over the west of the continent, though the modeled trend over SWWA is not found to be significant on an annual basis at the 90% confidence level. However, our study mostly post-dates the 20th Century decline in rainfall over this region, with observed 1971-2005 trends estimated from the Bureau of Meteorology gridded rainfall data over SWWA (30◦ -35◦ S, 115◦ -120◦ E) showing a mean increase of 20 mm per century, comprising localised areas of increase and decrease (Figure 4). Given the results of our trend forced experiments, it is possible that Indian Ocean warming has moderated to some extent the observed drying otherwise caused by factors such as the drift in the Southern Annular Mode (SAM) and land cover changes (Timbal et al. 2006; Pitman et al. 2004). The small area of modeled increase over the east of the continent between 25◦ S and 35◦ S covers the eastern coastal areas of northeast NSW and southeast Queensland. The simulated precipitation trend over this area is not significant at the 90% confidence level using a bootstrap-t test, and inspection of the individual members reveals that this feature is primarily accounted for by one of our five members. In fact, observed trends since 1970 show a general decline in rainfall over this area, most severe along the coastal fringe, but with some small areas of increase inland of the Great Dividing Range near 30◦ S (Figure 4). Adjacent to this area of modeled increase is an area of decreasing precipitation over a large area of the southeast inland, which is primarily a wintertime feature (Figure 18) but is also not significant at the 90% confidence level. 5.2. Seasonal Rainfall Trends

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The marked seasonality component of the moisture advection trends over Australia (Section 4.4) suggests that the regional circulation response to the linear trend in Indian Ocean SST has a seasonally varying projection onto mean flow regimes. In particular, the gradient in the specific humidity trends from an increase in the west to a decrease in the northeast is greatest in the autumn months. In addition, the spring-time pattern exhibits a band of increasing moisture transport from the northwest across the northern interior in agreement with observed rainfall trends. The model seasonal rainfall trends are shown in Figure 18. In the austral summer (DJF) the primary feature is a decrease across the north and northeast of the continent, though the land area significant at the 90% confidence level is somewhat less than for the modeled annual trends. The significant increase in modeled precipitation over the northwest remains offshore between the northwest

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

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Figure 18. Ensemble mean linear trends in seasonal precipitation (mm per century) over Australia for the period 1971-2005 from CAM3 forced by increasing Indian Ocean SST. Trend values determined to be significantly different from zero at the 90% confidence level using a bootstrap-t test are dashed. Australian coast and Java at this time of year, while the observed increase over northwestern Australia is strongest during the summer months (Figure 5). A large portion of the observed DJF increase over this area since 1970 has been the result of an increase in tropical cyclone activity, and these systems are only partially captured by the model at T42 resolution (Tsutsui and Kasahara 1996). The area of our offshore model rainfall increase is a formation region for tropical cyclones, which generally track southward over the northwest and west of Australia. As these systems are not well resolved by the model, our simulations could be underestimating the impact of Indian Ocean warming on precipitation over northwest Australia. The decrease in precipitation over the north and northeast is most extensive during autumn (MAM), with the trend significant at the 90% confidence level across a large area. The observed autumn trend also exhibits a decrease across the north and northeast of the continent (Figure 5). The modeled MAM trend pattern is positively correlated with the annual pattern, with a drying in the northeast and an area of increase in the northwest and west, significant across the subtropical western interior and also over the higher rainfall area of SWWA. We saw in Chapter 4 that the imposed circulation changes from a warming Indian Ocean reach a maximum over Australia during the austral autumn, accounting for the significant modifications to model rainfall at this time of year. The rainfall trend pattern across the north of the country is greatly weakened during the austral winter (JJA), as the monsoon trough lies well to the north, corresponding to the dry season in northern Australia. Trends are weak across most of the continent, except in the southeast where there is an increasing trend to the south of the mainland including Tasmania. This region of increased winter rainfall extends from the west of the continent to the South-

ern Ocean, and east of Tasmania, in a pattern qualitatively similar to that shown by Ashok et al. 2003 to be positively correlated with the negative phase of the IOD. Our SST forcing is calculated from observed values which exhibit no trend in the IOD mode index, although there is clearly a warming of both regions of the IOD anomaly. Our results are consistent with the notion that an increase in SST over the ’eastern’ IOD region off Sumatra exerts more of an influence over the Australian winter rainfall region than the corresponding warming over the ’western’ region closer to Africa. We saw in Chapter 4 that the winter-time increase of moisture advection to the south of Australia appears to originate in the tropical eastern Indian Ocean near 90◦ E, 10◦ S, part of the ’eastern’ IOD region defined by Saji et al. (1999). Both the wintertime and annual model trends show an increase in rainfall extending across the island of Tasmania. The observed late 20th Century rainfall trends exhibit a marked east/west pattern across the island (Figure 4), with an increase in the west and a decrease in the east. Because the island spans only ∼3◦ in longitude and ∼4◦ latitude, amounting to only two grid boxes at the model’s T42 resolution, the model cannot be expected to account for the marked east-west gradient in rainfall trends across Tasmania. The east-west difference is likely to be related to significant local topography across the island (Hill et al. – submitted 2007). The modeled wintertime decrease extending across much of South Australia, Victoria and southern New South Wales is not significant at the 90% confidence level, however observed trends show a decrease over a similar area, particularly severe over northern and eastern Victoria. The modeled decrease over the southeast mainland and increase over Tasmania exhibits a north-south pattern, which has previously been associated with the positive phase of the SAM (Sen Gupta and England 2006), although our model SAM index shows no significant trend. However, the subtropical ridge in

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LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING

CAM3 lies too far to the south, effectively shifting the modelled midlatitude trends northward to cover larger areas of South Australia and Victoria. This would act to partially offset the effects of the observed trend towards the positive phase of the SAM. The east-west pattern across the north of the continent returns in spring (SON) as the monsoon trough begins to move back toward the south with the approach of austral summer. Also present at this time of year is a band of increase extending from the northwest of the continent to the eastern inland, and also over parts of the western interior with large areas significant at the 90% confidence level. The spatial pattern of this increase is similar to the observed SON rainfall trends (Figure 5), which exhibit positive maxima over the western interior, northwest coast and an area of the eastern inland near 30◦ S. This band of spring-time increase in model rainfall corresponds to the anomalous moisture advection pathway at this time of year seen in Chapter 4. The good agreement between model and observed SON rainfall trends, with a band of increase in this area, suggests that Indian Ocean warming can account for part of the observed trend via these modifications to the intensity and position of the ITCZ, and the subsequent changes to moisture advection pathways in the region.

6. Discussion and Conclusions The strong surface warming of the tropical Indian Ocean over the late 20th Century is increasingly seen as a consequence of radiative flux changes imposed by increasing GHG concentrations in the atmosphere. We have sought to examine the regional climate response to this imposed SST change through an ensemble of AGCM experiments, forced only by the linear trend component of Indian Ocean SST, with sea and ice temperatures taking their seasonallyvarying climatological values elsewhere across the globe. In order to test statistical significance we conducted a five member ensemble with identical forcing, totalling 175 years of integration time. Our forcing methodology allowed us to examine, to a linear approximation, the particular atmospheric signal of a warming Indian Ocean in isolation from other potential forcing agents. An additional set of experiments with the trend-forced SST region extended east of the Indonesian archipelago exhibited a regional climate response in agreement with our major findings. A schematic diagram showing the regional climate response to Indian Ocean warming is given in Figure 19. The linear trend component of Indian Ocean sea surface temperature projects onto regional climate through significant modifications to the vertical circulation in the tropics and a reorganisation

Figure 19. Schematic diagram representing the anomalous regional atmospheric response to surface heating over the Indian Ocean. Horizontal vectors shown are indicative of the near surface layer (black), the 800-500 hPa layer (red/blue) and the enhanced subtropical jet (green).

of moisture advection pathways. The resulting precipitation trends over Australia exhibit an increase over the western part of the continent and a decrease over the northeast and north. The drying of the northeast and north is due to an anomalous zone of subsidence caused by the divergent outflow from increased convective activity over the tropical Indian Ocean, coupled with an offshore trend in the lower-tropospheric wind field. The confluence of these two factors leads to a strong drying signal over northeastern Australia, with significant modeled rainfall decreases as large as 800 mm per century in some areas, quantitatively similar to the observed trends. Therefore we conclude that the rapid late 20th Century warming of the Indian Ocean is quite likely to have contributed to the observed drying of northeastern Australia over the same period. The enhancement of tropical convective activity by warming SST was also found to increase the moisture content of the lower and middle troposphere across most of the basin, with a weakening of the mean Indian Ocean anticyclone leading to an onshore trend in winds to produce a modeled increase in rainfall over northwestern and western parts of Australia, significant over parts of the northwest coast and also the western interior. Given the results of Rotstayn et al. (2007) it is conceivable that rainfall over this area has been enhanced by a combination of increasing Asian anthropogenic aerosols and warming Indian Ocean sea temperatures. This hypothesis needs to be tested with further idealised GCM experiments. Over the southeast of the continent our ensemble average trends exhibit an increase over coastal areas poleward of 25◦ S, and a decrease over the adjacent southeast inland. This modeled pattern of increase and decrease in the southeast is not found to be significant at the 90% confidence level, and multidecadal variability appears to dominate the five ensemble members across these areas. For example, observed rainfall trends in the southeast show a particularly strong decrease across northern and eastern Victoria, and while our ensemble average exhibits a decrease over these areas, it is not statistically significant. The relatively poor resolution of the model and its tendency to place the subtropical ridge too far to the south make it difficult for us to evaluate the precipitation signal of a warming Indian Ocean over southeastern Australia. Given the importance of this region to agriculture and the persistence of observed trends into the first decade of this century, further attribution studies focussing on rainfall trends over southeastern Australia are required. The model increase over the western part of the Australian continent extends over the Southern Ocean to Tasmania, with broad areas significant at the 90% confidence level in a spatial pattern resembling that shown by Ashok et al. (2003) to be positively correlated with the negative phase of the IOD. Given our SST forcing contains no trend in the IOD, it is likely that the rainfall response over southern Australia is more influenced by the ’eastern’ IOD region off Sumatra than the western region close to Africa. The model precipitation increase over the entire island of Tasmania is likely due to the relatively poor resolution of the model, although it is impossible to know whether a higher resolution would have simulated an observed decrease over the eastern part of the island. Because the model subtropical ridge is too far to the south, midlatitude storm tracks are displaced poleward, so that the model increase maxima over Tasmania may actually reflect an increasing signal over the southern fringe of the Australian continent, where it would act to offset recent changes related to the SAM (Sen Gupta and England 2006). The relatively narrow band of high winter rainfall regions across the south of Australia lie between the dry regions under the subtropical ridge and the higher rainfall regime of the southern ocean storm track, making the region sensitive to small perturbations and presenting a challenge for future modeling studies. Another limitation of our results is that the seasonality of the model trends shows that the signal reaches a maximum in the austral autumn, while the observed trends across northern Australia

LUFFMAN: REGIONAL CLIMATE RESPONSE TO INDIAN OCEAN WARMING reach a peak amplitude in the summer months. This may be a consequence of the linear assumption implicit in using a single forcing mechanism (i.e. the linear trend in Indian Ocean SST), or a consequence of the tropical circulation within the model, or a combination of the two. Further studies using different models may help to resolve this issue. Interestingly, our model experiments show a band of spring-time rainfall increase extending from northwestern Australia to the eastern inland of the continent which is also present in observed trends. An analysis of moisture advection changes shows that this increase is related to changes in the position of the ITCZ over the tropical Indian Ocean at this time of year. The major modifications to the atmospheric circulation imposed by the observed trend in Indian Ocean SST suggest this is an important mechanism through which changes in the global radiation budget are projected onto regional climate. Given the resulting changes to precipitation across large areas of Australia, and the projected continuation of the increasing SST trend, studies into the future evolution of this teleconnection should be conducted. 1. Determining Significance of Modeled Trends In order to determine whether modeled trends are significantly different from zero, we conduct a hypothesis test using a bootstrap procedure. This technique is particularly effective in dealing with non-Gaussian data such as precipitation, because other hypothesis tests may make invalid assumptions regarding the sampling distribution; and in particular, its normality. Here we outline the particular method used for hypothesis testing of modeled trends in this study, whilst a more generalised treatment of bootstrapping is given by Efron (1982). At each (x, y) model gridpoint, the linear trend is calculated for each of the n ensemble members (where n = 5 in this case) using a least squares linear regression, yielding the vector m: mx,y = [m1 , m2 , m3 , m4 , m5 ] We then draw N random samples of size n from the vector m with replacement, and take the mean of each sample to produce the bootstrap vector x. N is an arbitrarily chosen large number, and as x becomes larger it will more closely reflect the variation in the original sample m. We choose N = 10, 000 at each gridpoint, which we expect is sufficiently large and within the constraint of available computing resources. We find that the probability density function of x is centered close to the original sample mean x, and that by inspection the distribution is approximately normal. The standard error of the bootstrap distribution is given simply by its standard deviation; qnamely:


2

1 SEboot = Σ x−x N −1 Given the original sample size n, the data contain (n − 1) degrees of freedom, and we can construct a 90% bootstrap confidence interval by excluding the left and right 5% tails of the bootstrap distribution: CIboot = x ± [t.95 ∗ SEboot ]

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If the 90% confidence interval does not contain zero, we can conclude that the population mean trend at that gridpoint is significantly different from zero at the 90% confidence level. 2. Abbreviations AGCM CAM3 CCSM CLM3 DJF ENSO GCM GHG HadISST1 IOD IPCC ITCZ JJA MAM NAO NAM NCAR NOAA SAM SOI SLP SON SST SWWA

Atmospheric General Circulation Model Community Atmosphere Model version 3 Community Climate System Model Community Land Model version 3 December, January, February El Ni˜no Southern Oscillation General Circulation Model Greenhouse Gas Hadley Centre Sea Ice and Sea Surface Temperature dataset version 1 Indian Ocean Dipole Intergovernmental Panel on Climate Change Intertropical Convergence Zone June, July, August March, April, May North Atlantic Oscillation Northern Annular Mode National Center for Atmospheric Research National Oceanic and Atmospheric Administration Southern Annular Mode Southern Oscillation Index Sea Level Pressure September, October, November Sea Surface Temperature Southwest Western Australia

Acknowledgments. I would like to thank a number of people who have assisted me in this pursuit, and without whom this paper would not have been possible. Firstly to Professor Matthew England who provided guidance and support, and generously gave time as a sounding board for ideas despite being extremely busy. To Dr Andrea Taschetto, for her paitence in spending countless hours assisting with the model configuration, and also some finer points of MATLAB. Further advice, ideas and technical expertise were provided by Dr Alex Sen Gupta, Mr Agus Santoso, Miss Caroline Ummenhofer and Miss Jessica Trevena. Plots were generated in MATLAB with the M Map toolbox by Rich Pawlowicz from the University of British Columbia, using the computing resources of the School of Mathematics at the University of New South Wales. The model simulations were conducted using the Altix Cluster at the Australian Partnership for Advanced Computing National Facility in Canberra, comprising approximately 25 000 hours of processor time.

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