Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Sciences Discussions Earth System Hydrology and 7462 7461 ˜ no/Southern Oscillation (ENSO) (McBride and Nicholls, 1983; Drosdowsky, This discussion paper is/has beenSystem under Sciences review for (HESS). the Please journal refer to Hydrology the and corresponding Earth final paper in HESS if available. suggesting that the SAM’seven influence greater on than Australian the hydroclimatology influence may be of equal ENSO or or IOD in certain regions during particular ocean-atmospheric processes occurring inthe the El Pacific Ni and Indian1993; Ocean, Kiem specifically anddecadal Franks, 2001; Pacific Oscillation MeyersFranks, (IPO) et 2004) al., (Power and et 2007; theand al., Indian Risbey Franks, Ocean 1999; et 2005; Dipole Meyers al., Kiem (IOD) etOther 2009), al., (Saji et studies 2007; and the al., have Risbey Yamagata, Inter- et also 2003; 2003;(SAM) al., identified Verdon and 2009; Kiem Australia’s relationships hydroclimate, Ummenhofer with and between et Gillett the et al., al. 2009). Southern (2006) and Annular Meneghini Mode et al. (2007) 1 Introduction It is well knownvariability that (e.g. Australia’s Chiew hydroclimate et exhibits al.,et significant al., 1998; 2004; spatial Franks Verdon-Kidd and and and Kuczera, Kiem, temporal 2002; 2009a). Nicholls, Much 2004; of this Verdon variability has been linked to the situation is the existence ofapproximated. numerous indices In (or this methods) paper, by the whichthe various SAM similarities SAM has been definitions and and discrepancies indicesnesses are are of each reviewed discussed, and index along development approach. withbetween Further, SAM the the and sensitivity strengths Australian of and rainfall themendations on weak- relationship are choice of given SAM asimpacts index of is to the quantified the SAM and on recom- most Australia’s hydroclimate. appropriate index to use when assessing the The Southern Annular Modepotentially (SAM) has significant been impacts identified onidentification as of the a some climate Australian relationships mechanism between hydroclimate.sociation SAM with has and not However, Australia’s been hydroclimate, extensively despite explored the or as- the robustly quantified. Further complicating Abstract Hydrol. Earth Syst. Sci.www.hydrol-earth-syst-sci-discuss.net/8/7461/2011/ Discuss., 8, 7461–7498, 2011 doi:10.5194/hessd-8-7461-2011 © Author(s) 2011. CC Attribution 3.0 License. The Southern Annular Mode: a comparison of indices M. Ho, A. S. Kiem, and D.Environmental C. and Verdon-Kidd Climate Change ResearchSciences, Group, Faculty School of of Science Environmental and and Information Life Technology, University ofReceived: Newcastle, 15 Australia June 2011 – Accepted: 15Correspondence July to: 2011 M. – Ho Published: ([email protected]) 1 AugustPublished 2011 by Copernicus Publications on behalf of the European Geosciences Union. 5 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | S with zonal (west to east) winds ◦ 7464 7463 S. SAM also varies seasonally with a strong zonally symmetric ◦ S) in the Southern Hemisphere (Rogers and van Loon, 1982). The alternating ◦ (SAM) The fundamental mechanism driving SAM circulation is the non-uniform heating of Importantly, the recent protracted droughts in south-west Western Australia (SWWA) surface convergence and risingman air and along Tapper, 2006). the The Inter-Tropical rising Convergence air Zone then (Stur- moves polewards, loses heat and sinks. In of 40 or wave-like structure is centredweakening at north approximately of 50 40 pattern in summer thatet deteriorates al., and 2009). becomes weaker in winter and spring (Jones the Earth and the subsequent energy(King transport and and Turner, atmospheric 2007). circulations that The occur build up of heat and energy near the Equator results in ern Hemisphere Circulation (KarolyWang, et 1998) al., and 1996), the theal., Southern 2006; Antarctic Annular Oscillation Meneghini Mode et (Gong(SAM) (Jones al., and will and 2007). be Widmann, used For in 2004;ening consistency, this the Gillett and paper. weakening term et SAM westerly is Southern winds defined Annular between as Mode the the mid alternating to pattern high of latitudes strength- (i.e. polewards 2 The large-scale climate phenomena known as the Southern Annular Mode Past studies have identifiedboth a the zonally symmetric Northern orlace, and annular 1998). Southern structure of Hemispheresthe This circulation (Kidson, Southern in Southern 1988; Hemisphere Hemisphere Annular Thompson annular Mode and (Thompson structure Wal- and has Wallace, been 1998), the referred South- to as discrepancies, along with theapproach. strengths Further, and the sensitivity weaknesses offall of the on relationship each between choice index SAM development and ofmost Australian SAM appropriate rain- index index to isdroclimate. use quantified when and assessing the recommendations impacts are of given SAM as on to Australia’s hy- the reviewing the various SAM definitions and indices and analysing the similarities and provide a fundamental first step in addressing the knowledge gaps identified above by 2005; McGowan et al.,exist 2010). around Despite how these muchSAM studies, of and significant Australia’s knowledge also historical gaps the climateand still role variability Verdon-Kidd, SAM can 2011). may be play Improved attributedhydroclimate will characterisation in to not of determining only increase the Australia’s our future roleity, understanding but of climate of will historical (Kiem also SAM hydroclimate variabil- provide on valuablemodels. Australia’s performance indicators for Realistic global and climategiven regional model the climate suggested representation links ofof between enhanced SAM SAM SAM and impacts and its in Australian an impacts droughts anthropogenically are warmed and world. crucial the This possibility paper aims to and Verdon-Kidd, 2011). and south-east Australia (SEA)Cai have and been Cowan, linked 2006; to2011) Hendon anomalous et that SAM al., is behaviour 2007; projected (e.g. Murphy and to Timbal, become 2008; more Gallant frequent et al., under global warming (Cai et al., the index used toclassified. represent This SAM confusion and as (c)classify to SAM, how how combined to the with the approximate various lack (i.e.from of phases which the research of SAM focusing Southern on index SAM Ocean, climate to has should driversof use) originating led be how and to much a significant of knowledge Australia’smore, gap hydroclimatic it in variability is our can not understanding be yetdrivers clearly attributed (e.g. understood to ENSO, how SAM. IOD, SAM Further- IPO)fluence interacts and Australian with local-scale hydroclimatology other (Meneghini synoptic large-scale et weather climate al., patterns 2007; known Gallant to et in- al., 2011; Kiem 2011) provide adriving comprehensive Australian summary hydroclimatic variability of andin from the these comparison key review with papers ocean-atmospheric it ENSOtionship processes is and with clear that, IOD, Australian very hydroclimate.teleconnections little also is The reveals known literature inconsistencies about that relating the does to SAM exist (a) and on how its SAM SAM rela- and is its defined, (b) seasons and epochs. Recent papers (e.g. Murphy and Timbal, 2008; Gallant et al., 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ˜ na ects were observed ff 5000 m a.s.l.). The air ∼ S. The regions of longitudi- ◦ S in winter). ◦ 7466 7465 S in summer and 20–25 ◦ ect is most pronounced during the austral summer where S) through the mid-troposphere ( ff ◦ S with the exception of Australia, the studies by Fan and Wang ◦ 40–60 ∼ ect) circulations at the surface and in the lower atmosphere as it moves north. Gillett et al. (2006) identifieditive a SAM decrease phases, in however, Meneghini summer et rainfall in al. SWWA (2007) during found pos- that positive SAM was Meneghini et al. (2007) deducedrainfall that in the SWWA cause (from of 1965while long Cai onwards) term and was Cowan reductions unlikely (2006) inand concluded to winter that winter be the rainfall due robust in to relationship SWWAtrend between explained trends SAM being 67 in % statistically SAM, of insignificant; the long-term decline, despiteIn this contrast to the findings ofnorth Gillett of et latitude al. 40 (2006) that no(2004) SAM and e Nan and Li (2003)within attributed China variations to in SAM. precipitation and dust events associated with increased rainfallthat in the SWWA, while decrease Cai inwinter; and rainfall Cowan during (2006) a found positive SAM phase only occurred during ff – – – ects are enhanced by increased insolation (McGowan et al., 2010). The seasonal A positive SAM is associated with warming of mid-latitude areas such as Tasmania, A positive SAM phase is characterised by anomalously high pressure in the mid- The Earth’s poles receive reduced insolation and a large amount of sunlight that ff associated with large-scale climategating drivers. the sensitivities This associated study with builds the on index that chosen to work represent by SAM. investi- The large degree ofthe inconsistency limited availability in of theto reliable findings develop data of a in existing robustindices and studies (discussed SAM around in may index, the Sect. be resulting Southern 3.1).also due exist in Ocean Compounding by to this with SAM which is to which being theand classify fact approximated SAM Franks that into by (2001) numerous its numerous methods positive, haveassociated negative previously and with neutral demonstrated selecting phases. the an Kiem implications index and of classification the method subjectivity to characterise impacts insights there is a lacktween of SAM agreement and and understanding hydroclimatic relating variabilityregions. to in For the example: Australia, relationship and be- other Southern Hemisphere are prevented from moving into the SEA region. However, despite these preliminary that during a positive SAM phase the rain bearing systems resulting from La Ni sure conditions described above and weakeningshift westerly in winds the leading storm to track. a northward south-east Australia, Chile, Argentinaal., and 2006). the south This island warminge of e New Zealand (Gillettinfluences et of the SAMspecific on regions rainfall of have Australia,of been predominantly Australia shown western (Meneghini to Tasmania et and be al., southern stronger 2007). regions than ENSO Kiem over and Verdon-Kidd (2010) also suggested latitudes and anomalously lowpositive pressures SAM indicates in the the occurrence latitudes of(westerly) a winds closer strengthening that to circumpolar circle vortex the Antarctica andthe South zonal which South Pole. Pole leads (Marshall, to A 2003). a A shift negative in SAM the phase storm exhibits a track reverse towards of the pres- cools over Antarctica, increases in densitygenerates and anti-cyclonic sinks. (anti-clockwise The in subsidinglis the air Southern over E Antarctica Hemisphere dueThe to air the moving Corio- north fromsubtropical the high South regions Pole and intersects rises. withpressure This the surrounding results air in moving Antarctica a south at circumpolar fromnally approximately trough, the alternating 60–70 a bounds region of ofby high low the and non-uniform low heating pressure of may the therefore Earth be and crudely ensuing explained air and heat transports. at the surface (around 30–35 is received is reflectedat due high to latitudes. thethe Antarctica relatively mid-latitudes therefore high ( acts albedo as of a the heat ice sink, sheets drawing and in snow warm air from the Southern Hemisphere, the subsiding air forms sub-tropical high pressure regions 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . (1) http: S projected onto ◦ index/aao/aao.shtml ao S) for every month. ◦ er in either the climate variables ff S and 65 erent gridded data sets for variables ◦ ff erence between normalised zonal mean ff 7468 7467 S as shown in Eq. (1). ◦ . S ◦ S and 65 ∗ 65 ◦ P − S ◦ ∗ 40 P S. This SAM index is calculated using National Centres for Envi- ◦ = S averaged over the boreal winter (or austral summer consisting of the ◦ is the normalized zonal MSLP (at 40 ∗ tropical climate variable (e.g. geopotential(MSLP), height temperature) (GpH), (e.g. mean Thompson sea level and pressure Wallace, 2000; NanGong and and Li, Wang 2003); (1999) method:pressure The between di 40 Principal Component (PC) analysis: The first PC of a Southern Hemisphere extra- – – Fan and Wang (2004) compiled another index, referred to in this paper as jisaoSLP, Several existing SAM indices that are readily available, commonly used and com- and May (MAM)). Thesouth jisaoSLP of is 20 calculated using the first PC of MSLP anomalies lies south ofronmental 20 Prediction-National Centre forfrom Atmospheric 1954 Research to (NCEP-NCAR) 2002. data record has Since release been of//jisao.washington.edu/data/aao/ extended the to Fan 1948 and (still Wang (2004) ending study, in thein 2002) jisaoAAO order and to isparticularly assess available prevalent the on: during occurrences the of boreal dust spring (consisting in of storms the in months northern March, April China, which are 3.1.2 jisaoAAO index and jisaoSLP index Fan and Wangstitute (2004) for calculated the a(AAO). Study The SAM definition of index, of Atmosphere jisaoAAO referred is and to based Ocean on here (jisao) the as first Antarctic the PC Oscillation of Joint 850 Index In- hPa GpH anoma- widespread satellite data.data source Satellite for analysing datahence Antarctic SAM has meteorology behaviour. been (Kingenced shown Therefore and by gridded Turner, to spurious 2007, data be errorsHence p. based encountered the 63) on the with and most satellite NOAA earlieris data reliable reanalysis index, is available, data less will which (Marshall, influ- this be covers 2003). study. used the as The periodhttp://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily the NOAA post baseline, index 1979 data or is reference where updated index, satellite in for data real the time remainder and of can be accessed at: National Oceanic and Atmosphericmethod) the Administration NOAA (NOAA) index of calculatedis SAM (using defined (referred the to as by PC the NOAA the as first monthly Antarctic empirical anomalies Oscillation) which 2000. of orthogonal 700hPa function GpH The mode south of NOAA of monthly SAM 20 700hPa index GpH is during based 1979– on a mixture of station observations and component time series. Based on the study by Thompson and Wallace (2000), the Gong & Wang developed to approximate the SAM.used, These indices the di data sourcescommon used methods by or which the SAM method indices are used formulated to are: define the index. The two most 3.1 SAM indices Recent studies aimed at investigatingReason and the Rouault, impacts 2005; of Gillett et the al., SAM 2006) (e.g. have resulted Nan in and numerous indices Li, being 2003; was shown that thetified spatial through structure the of analysis what of GpH is anomalies now regressed known upon as their SAM leading could principal be iden- 3 Data Where: P pared in this studymethod are used reviewed below to and constructavailability summarised and the the in index, temporal Table resolution. 1, the which data shows used the 3.1.1 (source and variable), National Oceanic period and of Atmospheric AdministrationThompson (NOAA) index and Wallace (2000)such as used monthly seven temperature, di analyse MSLP, month GpH, to wind month and variability total of column atmospheric ozone circulations to in the spatially polar regions. It 5 5 25 15 20 10 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | S ◦ . S and 70 erence being ◦ ff (season) S S. The index was ◦ ◦ erence between the 65 ff http://web.lasg.ac.cn/ (season) S ◦ MSLP − ) t S). Nan and Li (2003) believed ( ◦ S MSLP 65 ◦ σ 65 http://www.ifm-geomar.de/fileadmin/ . . S and 65 MSLP ◦ − S. Although Thompson and Wallace (2000) MSLP(season) is the mean of the seasonal ◦ 7470 7469 (season) is the standard deviation of the sea- . A monthly data set is also available and was σ erent selection criteria for stations, resulting in the ann http://jisao.washington.edu/data/aao/slp ff S and six stations close to 65 ◦ (season) S S and 65 erence between the normalized monthly zonal MSLP ◦ ◦ ff 40 ects on Australian rainfall. ff (season) S ◦ MSLP S (as opposed to 40 ◦ − ) t ( S MSLP 40 alle/PO/SAM/sam ◦ σ 40 E to encompass all of Australia and make it region specific. Although S and 70 ◦ ◦ MSLP = t /ljp/data-NAM-SAM-NAO/SAM-AAO.htm E to 180 ff ◦ This seasonal SAM index was calculated using the European Centre for Medium (JFM, AMJ, JAS, OND) andifm-geomar/fuer is available through: 1948-2001 based on the Gongthat and SAMI Wang (1999) is method definedbetween but as 40 with the the di di that the negative correlationwas in stronger than the between zonalshow 40 MSLP that this anomalies is between notSAMI 40 the case, showed the stronger SAMI correlations wasSAMI formulated has with to since summer be been region updated rainfallsta to specific in the as present the spring and Yangtze is River available on: valley. inclusion of 43 stations toimproved develop the data index. coverage This index forwas begins Antarctic in then 1958, stations extended as became this throughries is available. a (Visbeck, when 2009) method The based of on VisbeckAntarctica the reconstructing index concept and the of sub-tropical atmospheric Antarctic latitudes. mass MSLPinally The conservation time between reconstructed extended Visbeck se- to SAM 1884, indexselection was however, criteria orig- since resulted publication, inavailable a the from stricter reconstruction 1887 revision (Martin beingVisbeck of shortened Visbeck, index is the personal and formulated station in communication, data three 22 only monthly periods June, being from 2010). the start The of the calendar year 3.1.5 Southern Annular Mode Index (SAMI) Nan and Li (2003) created the Southern Annular Mode Index (SAMI) for the period of 3.1.6 Visbeck index Visbeck (2009) developed an indexHowever, of the SAM Visbeck using index a used di similar method to Marshall (2003). Hemisphere. Thehttp://www.antarctica.ac.uk/met/gjma/sam.html index is available from 1957 to the present and is available at: AOIR Meneghini et al. (2007)ever, used their the analysis Gong concerned and seasonalto Wang provide rainfall (1999) a and definition seasonal as of SAM such, index: the the SAM, index how- was redefined data set beginning in 1954.regularly This updated data and set available at: has now been extended back3.1.3 to 1948 and Regional is Antarctic Oscillation Index (AOIR) MSLP at sixthen stations normalised close and to used 40 to regress temperature and precipitation in the Southern months of December, January and February (DJF)) and spring months (MAM) with the Where: MSLP (t) is the seasonal MSLP; this data set ismethodology used no to longer develop a available,useful region and in specific identifying index therefore SAM for is e quantifying SAM not proved assessed to3.1.4 be in this study, Marshall the index Marshall (2003) alsodex used of the SAM. Gong However,posed the and to Marshall reanalysis Wang (2003) data), (1999) index which definition measured was the based to monthly on develop mean station an di data in- (as op- sonal MSLP for the season of interest. Range Weather Forecasts’ Re-analysis (ERA) ERA-40and gridded resulted monthly in MSLP one data AOI set 90 value per season per year. The AOIR used only data between MSLP for the season of interest; and 5 5 10 20 25 15 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erent starting ff erent SAM indices and Aus- ff http://polarmet.osu.edu/acd/sam/sam 7472 7471 erence in the reconstructions was that the Fogt reconstructions ff . The JW reconstructions were obtained through personal communication here is restricted togridded rainfall beginning data in is 1900 available; and ending in 2008 as that is when the On a seasonal resolution, correlationtralian between the rainfall di for theindicated entire in period Table 1 that some the SAM indices relevant exist SAM prior index to is 1900, available. however, the As analysis To quantify the sensitivity associated with choice of SAM index when seeking to According to Jones et al. (2009) both the Fogt and JW58 reconstructions are most 1. enable all scatter plots to be easily comparable. quantify relationships between Australian rainfall andducted: SAM two investigations were con- complete to 2002, all indicescorrelations were and compared scatter over the plots.index same as period The the (1979 scatter point to of plotsavailable 2002) reference. a were via All monthly, all indices scale developed were bythe using normalised subtracting 1979 on the the a to NOAA seasonal/monthly seasonal, 2002 mean and period) (calculated where over and dividing by the seasonal/monthly standard deviation to 1973) that applies a weighted averaging process to the station data. 4 Method This analysis compares SAM indices andindex the when sensitivity seeking associated with to choiceSAM quantify of indices the SAM were relationship between comparedAs Australian on the rainfall seasonal and NOAA and, SAM. index where is possible, only monthly resolutions. available from 1979 onwards and the jisaoAAO is only The Australian Monthly Gridded Rainfallreau Dataset of (1900–2008) Meteorology from the israinfall Australian used Bu- and to the compareobserved various the data relationship SAM using between indices. an Australian surface optimized The Barnes gridded successive correction data technique has (Barnes, been generated from 3.2 Rainfall data 2009). robust during the austral summerally (DJF) symmetric due during to this season. theafter nature As of the summer, SAM’s the spring zonal SAM symmetry proved beingtions, begins to most to followed be zon- break by down the winter mostutilised and problematic to reconstruct season autumn, the for where index SAMmore (Jones a reconstruc- et reliable reduced al., than number 2009). the of FogtJW JW reconstructions reconstructions stations proved reconstructions were could to deemed during be be to JJA be equally and reliable SON in while DJF and both MAM Fogt (Jones and et al., dates of 1866, 1905,the 1951 start and 1958. date ofuses Of 1958 the the (JW58 JW most reconstructions, index)period stations only is and in the used has index reconstructing in also with reconstructions the this been (Jones shown SAM study, et to al., as index 2009). be this for a JW the better reconstruction post indicator of 1979 SAM analysis than the longer JW recon.html from 1866 to 2005. Several JW reconstructions were developed with di station MSLP data wereFogt reconstructed used index and to the produceanalysis, Jones and the as Widmann described SAM (JW) reconstructed in index2009). indices. Sect. prior PC 2.1, to The was 1958 keywere used for di fitted to both to calculate the the bothindex Marshall indices using ERA-40 index, (Jones data whilst et (1958–2001) theThe and al., Fogt the JW reconstructions PC reconstructions are method available of were through: developing fitted a SAM to index. a SAM tion, 6 January 2011). 3.1.7 Fogt index andRelationships the developed Jones from and the Widmann ERA-40 index reanalysis MSLP data from 1958–2001 and obtained through personal communication with Martin Visbeck (personal communica- 5 5 25 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erence ff erence between the in- ff erent SAM indices and Aus- ff erences between the various SAM in- ff 7474 7473 erence between the Visbeck index and both the Fogt and JW58 indices ff On a seasonal resolution, correlationtralian between the rainfall di for the periodare over available (i.e. which 1979–2002), all to ofNOAA enable the index-rainfall equitable correlations SAM comparisons are indices used to as being bebetween the made. investigated the baseline The index seasonal and index-rainfall the correlations di relations and are the determined. NOAA index-rainfall cor- Figure 1 shows similar patterns to Table 2, in that all indices correlate well with NOAA To further investigate the similarities and di For both Figs. 1 and 2 consistency between indices (i.e. the NOAA index and the Both jisao indices and the NOAA index are highly correlated. This result was some- 2. is an increasing degree of scatter for the Marshall, SAMI and Visbeck indices. It also points in the second andindices fourth as quadrants to indicate what apositive the SAM complete SAM conditions disagreement phase while from the is the as other for it is indicates a indicating the given negative choice SAM). season oftified index This (i.e. which may is result could one of in lead index the concern to phase is misrepresentationof of of suggesting hydroclimatic SAM SAM’s variability being influence incorrectly to and iden- SAM incorrect behaviour. attribution except Fogt and JW58and and, jisaoSLP to show a little lesser variation degree, in Visbeck. comparison In to particular, the the NOAA jisaoAAO index, however, there necessary to compare monthlyable SAM at a indices monthly and, resolution for (see the Table 1), SAM this indices isSAM shown that index in are being Fig. avail- compared) 2. gradient is depicted and, by importantly, a no clustering data of data points points in around the the second 1:1 and fourth quadrants. Data between the Marshall index (for Fogt) and ERA-40 MSLP PCdices (for in JW). comparison tovalues against the the NOAA normalised index, NOAAsonal index scatter index were values plots developed. plotted of Figurethe against the 1 same the shows normalised time corresponding the period seasonal SAM sea- on (1979–2002). NOAA index sub-seasonal index Many timescales, value hydroclimatic where for studies monthlyare and are required weekly however for focused information historical on investigations climate states as well as for forecasts. Therefore it is also cally based extended SAMrecords. index In record contrast prior tostructions to the (note the physically that availability based as of Visbeck previouslyassessed discussed method, continuous in in the station this Sect. Fogt 3.1.7, paper) and JW58long-term were JW is based station recon- the on data only statistical JW (starting regression index as models far developed using back as 1865) as predictors and relationships mid-latitudes in order to gain insights into SAM behaviour and hence create a physi- The notable di is that the Visbeck index uses a method of reconstructing sea level pressures in the dices based on gridded reanalysis(i.e. data the and the Marshall indices andthe based use on Visbeck station of indices). observations NCEP-NCAR dataor exaggerates Marshall three, trends especially (2003) in in the haswhose SAM winter, previously errors signal due shown increase by to a that atindices the factor higher available of nature prior latitudes two of to when thecorrelated 1950 with compared NCEP-NCAR (i.e. the reconstructions, with Fogt, NOAA station JW58, indexgridded (used data. Visbeck), data as Visbeck that the Of is is reference the the point based in most on this highly a study mixture as of it satellite utilises data and observed surface data). what expected given that theusing NOAA, the jisaoSLP and PC jisaoAAO analysis indicesalso are method highly all and developed correlated NCEP-NCARGong to reanalysis and pressure the Wang data. NOAA (1999)NCEP-NCAR method and SAMI reanalysis and is jisao pressure this indices, data. is despite perhaps There being because is the based a SAMI on clear also the di utilises 5 Results 5.1 Comparison of seasonal and monthlyTable SAM 2 index shows values the correlationsa between the seasonal NOAA scale. index All and correlations the are remaining statistically indices significant on at the 99th percentile. 5 5 25 15 20 10 20 25 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erent erent, ff ff erences in ff erent results ff erences observed in the re- ff erences in the relationship between ff 7476 7475 erent periods of analysis for each SAM index). As such the ff erent to those obtained using Fogt and JW58 indices. Also impor- ff erences between the SAM indices (i.e. in a comparative study), not to establish re- erent results if you used Marshall, SAMI or Visbeck, and extremely di SAM is a climate mechanism that has varying seasonal impacts. It is therefore The results from Figs. 1 and 2 indicate that if you were to characterise the rela- ff ff who showed the positive phasetumn of rainfall). SAM A was negative strongly correlation related in to SWWA a is decrease seen in in SEA all au- of the gridded and station Verdon et al., 2004). 5.2.2 Autumn (MAM) As with summer, therelationship are between significant autumn similarities rainfall and(Fig. and 4). di SAM Autumn depending rainfallin on correlations south-east the with Australia choice SAM (consistent of indices with SAM all the index show finding negative correlations of Kiem and Verdon-Kidd (2010), between the NOAA, jisaoAAO and jisaoSLPespecially indices and in Australian central rainfall are to di the eastern periods Australia. being This analysedand is and are most strongly likely possibly suggests due subjectcould to SAM be to the relationships similar multidecadal di to vary modulation theimpacts over way in via time the Australia other (e.g. IPO Power modulates climatic et the al., drivers. frequency 1999; Kiem and et This magnitude al., of 2003; ENSO Kiem and Franks, 2004; 5.2.1 Summer (DJF) Figure 3 shows the correlation betweenthe summer period SAM indices where and both summerpatterns SAM rainfall are over and observed rainfall for dataSect. the are 5.1) NOAA, and available. these jisaoAAO relationships Broadly and (which2009) speaking, jisaoSLP are are consistent similar indices totally with (consistent the di results with tant of Risbey to et note al., is the fact that despite the SAM indices being very similar, the correlations results obtained based purely on choiceover of SAM a index. consistent Section 5.3 period,comparison repeats 1979–2002 the of analysis where the all relationshipuncertainties of SAM associated various indices with SAM are length indices of available, and SAM to index Australian enable availability rainfall removed. with the results from index to index are not directly comparable but again illustrate the di season and SAMindex index availability the (i.e. period di of analysis corresponds with the period of SAM Australian rainfall and SAM,taken. as It represented is by important the todi note various that SAM correlations indices, arelationships was only between used under- SAM in and this Australiancorrelations study rainfall. in to The establishing identify limitations hydroclimatic the associated relationships with are using discussed in Sect. 6. necessary to consider therainfall correlations and the between results for seasonal this SAM are presented indices in and the following seasonal sections. Note that for each don and Franks, 2005). 5.2 Seasonal relationships between various SAM indicesIn and Australian order rainfall to assesschoice the of inconsistencies SAM resulting index, an from investigation the into subjectivity the associated di with tionship between SAM andexpect hydroclimatic similar variability results at if a you givendi used location the then NOAA, you jisaoAAO, could if jisaoSLP SAM you indices, used slightly FogtJW58 or would JW58 (indeed be in theThis some direct highlights cases opposite the the to results importance thoseuncertainty, obtained obtained associated of using with using acknowledging Fogt choice any the and of of subjectivity, climate the and index other (e.g. quantifying indices). Kiem the and Franks, 2001; Ver- Visbeck indices. Figure 1fan increased (Fogt number against of NOAA) datacating and points a recorded 1g high in (JW58 degree the against of secondat inconsistency and NOAA) the fourth with monthly show quadrants, the resolution indi- NOAA (Fig.seasonal index. 2) scale suggesting The will that results also a are work SAM replicated in index that a is similar acceptable fashion at at the the monthly scale. appears that the NOAA index is often greater in magnitude than either the Marshall or 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erence ff erences in central ff erence. The NOAA index ff erent relationships are obtained ff erence maps in Sect. 5.4 is comparing ff 7478 7477 erent insights can be obtained dependent on (a) which index you ff erences between SAM indices and rainfall relationship (1979–2002) ff erent pattern with positive correlations in SWWA and also clear di The results displayed in Fig. 3 through to Fig. 6 are based on data over the longest ff with rainfall for each season.NOAA Figure a) with in NOAA the di and therefore always results in zero di 5.3 Di In order to makedex with equitable Australian comparisons rainfall, each betweenAustralian SAM the rainfall index from relationships (seasonal 1979–2002 resolution) of (i.e.enable was each the distinctions correlated period SAM between with for the in- whichrainfall) indices all to was SAM be used indices made, exist). asbetween the each To the NOAA SAM baseline. index index correlated (correlated with with Figure rainfall and 7 the correlation through of to the NOAA Fig. index 10 show the di demonstrated by these results, the potentialand multi-decadal magnitude modulation of of SAM the impacts frequency this is is an beyond area the thatSAM-rainfall scope relationships requires of to further SAM this investigation, index paper. choice however the and The analysis to over do focus a that here it consistent is is baseline necessary to period to quantify (see perform Sect. the 5.3). sensitivity of period of rainfall andbased SAM on up index to data 106analysis availability. yr of was As data, carried a while others result,when out are some various simply based correlations on SAM to as are indicestime illustrate little as periods. when that 30 are di yr This of correlatedindices is data. are with a This used fairly Australian obvious interchangeably rainfallover a result or over certain but teleconnections various time one period obtained areAustralian that rainfall assumed using in is to the one represent often past, the SAM now overlooked relationship and between index as in SAM the SAM and future. As mentioned in Sect. 5.2.1, and as Risbey et al. (2009) but inconsistentthe with the correlation study patterns by Meneghini between etsimilar spring al. for (2007). rainfall all Although the and indices, springstrength there SAM and is spatial still indices extent variability appear of between to the positive be or indices with negative correlations. respect to the spring Australian rainfall is consistent with previous work by Hendon et al. (2007) and are negatively correlated to springVictoria, and rainfall SWWA. in The western dominance Tasmania, of the positive southern correlations between coast spring of SAM and jisaoSLP and SAMI indices showthat the completely complete opposite. di Thischoose again and highlights (b) the the fact period of time over which5.2.4 you investigate the Spring relationship. (SON) Figure 6 shows thethe correlation period between where spring both SAM SAM indices and and rainfall spring data rainfall are over available. All of the SAM indices SEA, including Tasmania, whichmagnitude supports and spatial the extent of workand relationship of varies the markedly Risbey patterns dependent (2009). for oningly, SAM Meneghini the However, index et remainder the al. of (2007)eastern Australia found Australia significant are rainfall positive noticeably during correlations winter, inconsistent.when between however the SAM similar Marshall, Interest- and results Visbeck or are JW58 only index indicated is used here (Fig. 5d, f, h) whereas the jisaoAAO, di Australia and SEA. 5.2.3 Winter (JJA) Figure 5 shows thethe period correlation where between both wintertween SAM SAM winter and rainfall indices rainfall and and data winter are winter SAM available. rainfall indices Negative over are correlations a be- consistent feature for SWWA and NOAA index in the latterare case. also found Positive for correlations northern between AustraliaSAM autumn (to index). rainfall varying This and degrees is SAM depending consistent on withlations choice/length Meneghini in of et autumn al. were (2007) who locatedas found in with significant northern corre- summer, and the north-west Fogt central and Australia. JW58, However, and also Visbeck, (Fig. 4f–h) show a markedly data based indices (Fig. 4a–e) as well as Tasmanian rainfall with the exception of the 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | S (Gong and ◦ S and 65 ◦ erences are marked and erent to the NOAA correla- ff ff 7480 7479 erences in the various indices used to represent ff S being the most suitable for identifying the nature of ◦ S and 65 ◦ erent relationships to what is obtained if NOAA is used – this is ff SAM indices based on station records of pressure at 40 To answer the first question, numerous studies have shown that the SAM annular Consistent with results presented in Sect. 5.1, jisaoAAO, jisaoSLP and the SAMI tainty (Visbeck, 2009). The results in Sect. 5.1 (Table 2, Figs. 1, 2) indicate that the based on reanalysis data are flawed,fectively modelled it data does and highlight relationships the obtained factshould using that be reanalysis reanalysis verified based data with SAM is indices observational ef- (i.e. station based) data. Wang, 1999) are most likelylimited to to have the periods most when accurate goodindices representation quality are of stations SAM, both are but developed available.In are using The the station Visbeck case and of based Marshall thethe data use Visbeck as of index, reconstructed opposed the pressure issue to readings, of reanalysis which limited introduces data. data another source is of partially uncer- resolved through exist in the reanalysis datadecades and is that magnified the by strengtheningAlso, a SAM seasonal factor signal analysis observed of using over twocreasing NCEP-NCAR past to SAM data three trends incorrectly as in identifies occurring thedata in the NCEP-NCAR winter being greatest instead reanalysis particularly in- of data. summer poor. due to While winter this reanalysis does not necessarily mean that SAM indices jisaoSLP and SAMI areimplying also that NOAA, very jisaoAAO, similar jisaoSLP orto (Table SAMI 2, represent could Fig. SAM be – 1, usedthree with noting 2) equal are that to confidence NOAA available NOAA is from andfactor only 1948) jisaoAAO between available and from NOAA, jisaoAAO 1979 jisaoSLP, isanalysis jisaoAAO (whereas data. not the and The other available SAMI advantage after of isbroader 2002. reanalysis spatial the data coverage use A is (as opposed the of common in to availability NCEP-NCAR of station the based information re- Southern data with which a Hemisphere). is somewhat However, limited Marshall (2003) warns that spurious trends structure is best characterised byreadings MSLP, 700 at hPa latitudes or 40 850 hPa GpHSAM measurements, (Gong with and Wang, 1999).and Given jisaoAAO this could physical be basis, itbased considered then on good follows indicators the that of the physical NOAA SAM understanding behaviour, outlined since above. they are As discussed in Sect. 5.1, the how does SAM interactand with, local-scale other weather large-scale patterns (e.g. known to ENSO, influence IOD, Australian IPO) hydroclimatology? climate drivers determine the seasonal relationship betweenmagnitude SAM and and spatial Australian rainfall. patternSAM Indeed, of index the chosen. the relationships Therefore,SAM given vary is responsible the drastically for numerous at depending studies leastthat on the some that results of the have and Australia’s conclusions hydroclimatic suggested in variability,following and that these the questions previous studies fact emerge: are not (a) alwayswe consistent, which know the as SAM the index SAM most process?;tralia’s (b) satisfactorily temporal what and represents is spatial what the hydroclimatic true variability?; relationship and between (c) SAM how and is Aus- SAM related to, or same physical process, thereSAM are which di are dependent onthe the index. method, variable, or Inlead source some to of data large cases used uncertainty (e.g.Sections to as develop Fogt 5.2 to and and whether 5.3 JW58) the demonstrate these SAM the di is implications in of its this positive uncertainty or when negative trying phase. to lations with rainfall are similar totions. each Also other, but consistent both with areresult previous di results, in the totally Fogtconsistent di and across JW58 all reconstructed seasons. indices 6 Discussion and conclusions The results presented here demonstrate that, despite supposedly representing the and 6a. correlations with rainfall are similarcolours to on the the NOAA correlation correlations maps)but (as large for indicated discrepancies summer by are (DJF), the observed autumn pale in (MAM) winter and (JJA). spring The (SON) Marshall and Visbeck corre- correlation (i.e. the reference point) for each season can be seen in Figs. 3a, 4a, 5a, 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | eld for ffi 0.3 and − erences in station- ff erences in the various SAM ff , 2006. 7482 7481 doi:10.1029/2006GL028037 MH is supported by the Australian Postgraduate Award with additional forcing account for southwestLett., Western 33(24), Australian L24708, winter rainfall reduction?, Geophys. Res. NOAA Technical Memorandum,Storms ERL Laboratory, Norman, NSSL, OK: 60, 62, 1973. NTIS COM-73-10781, National Severe Climate indices are a practical way of approximating large-scale climate phenom- Following on from that, and with respect to the question as to the true relationship Cai, W. and Cowan, T.: SAM and regional rainfall in IPCC AR4 models: Can anthropogenic Barnes, S. L.: Mesoscale objective map analysis using weighted time-series of observations. Acknowledgements. assistance from a CSIRO LandScholarship. & The Water Flagship authors Scholarshipher would and provision like a of to NCCARF her Water thankGermany Network for reconstructed Julie data Jones SAM clarifications from index and provision the and of University Martin the of monthly Visbeck Visbeck She from index. IFM-GEOMAR, Kiel, References in Australia (e.g. Kiem and Franks, 2001), could be explored. modes other than SAM). Itclimate is impact critical attribution to study consider and andassessments also account in if for climate misunderstandings this model are uncertainty verificationis to in and any sensible performance be to avoided. assume Itresentative that is of an also the index SAM questioned based process whetherof or on it the whether a SAM more state single comprehensive are variable multivariatedex required. can monitors (MEI; Perhaps ever Wolter something be and similar truly Timlin, toand the 1993; rep- more Multivariate 1998), consistently ENSO which In- capture has the been entire shown to ENSO more phenomenon realistically and its related impacts real. It is important tothere realise is that such all a indices thing, arestudy will approximations has depend and highlighted the on that “best” it whatindices index, is you and if crucial are to to using consider be the the aware indexcould fact of for. that the be Importantly, insights di just this gained an using artefact climate index of based the analysis index chosen (this applies equally to indices of climate process and (b) the empirical relationships developed using the index are physically ity. However, this only works if (a) the index is a realistic approximation of the climate et al., 2007; Verdon-Kiddinvestigation and is Kiem, required 2009b; intoSAM Gallant the impacts et and non-linear, novel al., and methodsis 2011). need potentially related to non-stationary, to, Therefore, be or nature further developed interactsand to of with, gain local-scale other insights weather large-scale into patterns (e.g. howquestion known ENSO, SAM (c) IOD, to posed IPO) above). influence climate Australian drivers hydroclimatology (i.e. ena. The climateour indices understanding can into then the be causal used processes in behind empirical observed studies hydroclimatic variabil- aimed at improving majority of correlations0.3 between (Sects. SAM 5.2 and and Australianalso 5.3), be rainfall and recognised are that therefore the not between lackthat statistically of there a significant. is significant correlation However, no doesthe it relationship not should relationship neccessarily between mean is SAM non-linear, and Australian non-stationary rainfall. or It modulated just by may other be factors that (Hendon raises the question – whichion, is and the especially most considering reflectivereanalysis the of data issues the (Marshall, associated true 2003), with relationship? theMarshall SAM station-based In or SAM representation our Visbeck). indices in opin- Given are the sure the most readings reliable uncertainties (i.e. in associated with thewhen the Visbeck it reconstructed index exists pres- (1957–2011) our and recommendation the Visbeck is index to if use analysesbetween are the required SAM Marshall prior index to and that. Australian rainfall (i.e. question (b)), it should be noted that the representations of SAM (correlationsmentioned as of being about realistic 0.9 (i.e.results NOAA, in in jisaoSLP, jisaoAAO all Sect. and cases) SAMI). 5.2based However, and that the and reanalysis-based were indices 5.3 previously result clearlyand in marked illustrate spatial inconsistencies that pattern in the these of magnitude minor the di SAM relationship with Australian rainfall. 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C. and Rouault, M.: Links between theRisbey, Antarctic J. Oscillation S., Pook, and M. winter J., rainfall McIntosh, P. C., Wheeler, M. C., and Hendon, H. H.: On the Remote Power, S., Casey, T., Folland, C., Colman, A., and Mehta, V.: Inter-decadal modulation of the 5 5 30 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1 1958 b x x 2005 2005 2005 c 2011 c 2011 c 7488 7487 2002 2011 c x x x x x NOAA jisaoAAO jisaoSLP Marshall SAMI Visbeck Fogt JW58 a NOAA jisaoAAO jisaoSLP Marshall SAMI Visbeck Fogt JW58 Gridded data 700 hPa GpH850 hPa GpH x End YearSeasonal 2011 x Gong and Wang x x x Correlation between various SAM indices at a seasonal resolution (normalised for Summary of SAM index development methods and periods of availability. Period Start Year 1979 1948 1948 1957 1948 1887 1865 Source Station readings x x x Method PC reanalysis x x x x x Variable Sea level pressure x x x x x x NOAAjisaoAAOjisaoSLPMarshall 1SAMIVisbeck 0.981Fogt 1JW58 0.968 0.989 0.903 0.945 0.893 1 0.890 0.955 0.670 0.897 0.895 0.712 0.650 0.961 0.704 1 0.911 0.643 0.880 0.695 0.880 0.700 1 0.695 0.874 1 0.686 0.677 0.642 0.670 1 0.784 Time scale Monthly x x x x x x NCEP-NCAR gridded data except for JW58,1865 where for ERA-40 summer data and is autumn; used. 1905 for winter and spring. Updated monthly. Table 2. 1979–2002). a b c Table 1. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | JW58. JW58. (g) (g) Fogt; Fogt; (f) (f) Visbeck; Visbeck; (e) (e) SAMI; SAMI; (d) (d) 7490 7489 Marshall; Marshall; (c) (c) jisaoSLP; jisaoSLP; (b) (b) jisaoAAO; jisaoAAO; (a) (a) Monthly SAM index values plotted against monthly NOAA index (normalised 1979– Seasonal SAM index values plotted against seasonal NOAA index (normalised 1979– Fig. 2. 2002) for 2002) for Fig. 1. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | NOAA NOAA (a) (a) JW58 (1958–2005). JW58 (1958–2004). Marshall (1957–2008); Marshall (1957–2008); (h) (h) (d) (d) Fogt (1900–2004); (g) Visbeck (1900–2005); (g) jisaoSLP (1948–2008); jisaoSLP (1948–2008); 7492 7491 (c) (c) Fogt (1900–2005); Visbeck (1900–2005); (f) (f) jisaoAAO (1948–2002); jisaoAAO (1948–2002); (b) (b) Correlations between total autumn (MAM) rainfall and autumn SAM indices Correlations between total summer (DJF) rainfall and summer SAM indices SAMI (1948–2008); SAMI (1948–2008); Fig. 4. (1979–2008); (e) Fig. 3. (e) (1979–2008); Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | NOAA (a) NOAA (1979– (a) JW58 (1958–2005). JW58 (1958–2005). Marshall (1957–2008); (h) Marshall (1957–2008); (h) (d) (d) Fogt (1905–2005); Fogt (1905–2005); (g) (g) jisaoSLP (1948–2008); 7494 7493 jisaoSLP (1948–2008); (d) (c) Visbeck (1900–2005); Visbeck (1900–2005); (f) (f) jisaoAAO (1948-2002); (b) jisaoAAO (1948–2002); Correlations between total spring (SON) rainfall and spring SAM indices Correlations between winter (JJA) rainfall and winter SAM indices (b) SAMI (1948-2008); SAMI (1948–2008); Fig. 6. (1979–2008); (e) Fig. 5. 2008); (e) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Marshall; Marshall; (d) (d) jisaoSLP; jisaoSLP; (c) (c) jisaoAAO; jisaoAAO; (b) (b) 7496 7495 JW58. JW58. (h) (h) Fogt; Fogt; (g) (g) Visbeck; Visbeck; erence between autumn NOAA index-rainfall correlation and autumn SAM index- erence between summer NOAA index-rainfall correlation and summer SAM index- (f) ff (f) ff Di Di SAMI; SAMI; (e) rainfall correlations for the period 1979–2002 for Fig. 8. Fig. 7. (e) rainfall correlations for the period 1979–2002 for Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | SAMI; Marshall; (e) (d) Marshall; (d) jisaoSLP; (c) jisaoSLP; (c) jisaoAAO; (b) jisaoAAO; 7498 7497 (b) JW58. (h) Fogt; JW58. (g) (h) Fogt; erence between spring NOAA index-rainfall correlation and spring SAM index- Visbeck; ff (g) erence between winter NOAA index-rainfall correlation and winter SAM index-rainfall (f) Di ff Di SAMI; Visbeck; (e) rainfall correlations for the period 1979–2002 for Fig. 10. correlations for the period 1979–2002 for Fig. 9. (f)