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Weather – July 2009, Vol. 64, No. 7 –orange; 90% – yellow; 110% – cyan; 120% – blue; and blue; – 120% cyan; – 110% yellow; – 90% –orange; i rainfallAustraliaover June–August (a) Figure1. seriesin ? affectthe results of CouldEl Niño Southern Oscillation A–Adelaide; M–; S–Sydney; B–Brisbane. (b) As (a) but for La Niña years.Niña La for but (a) As (b) B–Brisbane. S–Sydney; M–Melbourne; A–Adelaide; mzna Bsn xeine drier-than- experiences Basin Amazonian the while flooding, of incidences increased with rainfall, higher-than-usual experiences the America Ocean, South of Pacific region Andes the On equatorial of side regions. other the Indonesian and Australian the increased in fires bush also and forest of are occurrences There drought. even and rainfall, lower-than-usual Asia experiences Southeast Niño, northern El an In during winters regions. Pacific western eastern the and between gradient pressure the in change associated an causing circu-lation atmospheric tropical the in change positive the than phase. anomaly SST smaller a have to tends phase negative the general In slightly. cools Pacific the Niña of region La this – as known – phase negative its In months. few a of period a for degC 1 about by warms Pacific the of region this – El Niño as known – phase positive its In Ocean. Pacific equatorial eastern the of part some of involvetemperature sea-surface the (SST) measurements most but measured ways, different be in can phase Its temperature. vari-surface averaged globally of terms in ability climate interannual of mode largest the is (ENSO) Oscillation Southern Niño El results and Introduction UKReading, of University Joshi Manoj soitd ih h cag i ST s a is SST in change the with Associated (a) n El Niño years divided by the climatological mean f mean climatological the by divided years Niño El n obtained from the CPC Merged Analysis Analysis Merged CPC the from been obtained has and average, by time divided (26-year) years the Niño El in precipitation shows which 1(a), Figure is in This demonstrated 1983). Nichols, and (McBride peak ENSO the following June–August months winter (austral) of the in is regions especially rainfall large Australia, play years, normal Niño does than El lower In ENSO role. large 2006), a Sharma, and several are there (Westra mecha variability this Although behind nisms year. to year from variable highly is rainfall, its of terms drier-than-average apparent.also arewinters, having midwestern States the United as such effects, tropical extra- Reversed region. Pacific eastern the in conditions drier with Asia, Southeast the in prevail conditions of wetter reverse happens; above the approximately Niña, centuries.for fishermen of coast between by local known been has ENSO and fisheries link western the Indeed, America. the South off moves which northwards areas Current, these Humboldt to the by supplied water cold rich Pacific nutrient- of equatorial amount the changing by Ocean eastern the in disrupt fisheries also can event Niño El prolonged wetter. is USA western the while Niño El an during winters warm get to tends Canada Western conditions. average 150% – dark blue. The locations of the Testthe v of locationsMatch The blue. dark – 150% The climate of Australia, especially in in especially Australia, of climate The La or ENSO, of phase negative the In a in circulation ocean the in change The (b) or years 1979–2004. The colours are: 60% of mean – red; 80% red; – mean of 60% are: colours The 1979–2004. years or enues are marked with their initial letters: P–Perth; letters: initial their with markedare enues index corresponds to La Niña conditions. Niña La to corresponds index negativeNiño-3 a conditions,and Niño El to therefore index positivecorresponds Niño-3 A 210E–270E. 5N-5S, region the in Kelvin in anomaly temperature surface the is which index, Niño-3 the using measured is ENSO the between results of these series and ENSO. found In this study been significant has a correlation and matches, of results the Ashes of made An been 1970. has sinceanalysis Australia matches hosted Western only in has Perth instance, for case; the been always not has this Sydney), and in Melbourne each Perth, Adelaide, (one Brisbane, fixed now are matches the for venues the While total. in matches six) in days occasionally (and five five are there and of length, maximum a each are and Matches) Testtake place between November and February (called matches The years. as four every host the Australiais that hosts,so alternate countries two The years. two every approximately series Ashes the play 1(b). Figure in shown as country, slightly with the of most over existing found, conditions wetter is reverse the years, Niña La In 2000). Trewin, and (Jones Niño years El in moisture soil of values average lower-than- to contribute also evaporation and temperatures Higher- land-surface than-usual Australia. northwest exception and the west over with of exist country, the conditions of most Dry 1997). and (Xie Arkin, dataset (CMAP) Precipitation of Cricket teams from and Australia and England from teams Cricket ENSO and the Ashes series Weather – July 2009, Vol. 64, No. 7 179 It is theorized that in El Niño years, An attempt was made to decompose the It is finally noted that the US-NOAA NCEP The The Ashes scorelines have been collated CMAP precipitation data obtained from The author would like to thank the are are faster, so that when bowled, the bounces off the faster. Not surface only higher that but and a ball bowled cricket swerves or less ‘swings’ when conditions in are dry. flight On average, English much bowlers tend speed and to more swing than their Australian bowl with counterparts less because the relatively damp and cool English summer climate this favours style. In addition, dry wickets favour tend to bowlers, which teams have historically had more of. Australian Australian pitches tend dry, and to the be conditions are relatively therefore conducive to the less style favoured by the majority of English bowlers, which will favour the Australian team. It is interesting that in La Niña years, the results shown Figure in 2 are almost even. This is consistent with the mechanism above, which indicate would cooler which and might wetter favour England, cancel conditions, or the advantage at of least dry pitchesNiño years. in El present results to individual cities, but statisticallyno significant link was found. This is not unexpected given that the response of Australian weather to ENSO is variable,both temporally and spatially (JonesTrewin, and 2000). In course addition, many there different are factorsthe outcome of any given of sporting contest, governing which would act as noise in Future this analysis. work statisticaltests totry totease out anysignal might in individual involve venues. different prediction website shows Niño-3 predictions index of up to approximately in a advance. year Therefore it may to tell be as possible soon as the winter of whether 2009/2010 or not the England cricket team’s next austral tour has chance of a success better than or previous might even tours. worsebe possible that It the prediction could inform the selection of the England touring team, in terms of whether more fast bowlers bowlers or ‘swing’ are more picked. It is, of course, stressed that this last factor is a minor one in the context of winning cricket pickingteam. a Acknowledgements The Niño-3 time series has been obtained from http://climexp.knmi.nl/ from www.334notout.com NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.cdc. noaa.gov/ anonymous reviewers of this and manuscript, John Nicol and Steve Woolnough their comments. for

s s 900 900 ore ore rcles rcles 2002). El Niño et al., 1983); associated with the , The The dryness of a can have yearsare also associated with significantly higher land surfacemost of temperatures Australia, over whichthan the last rainfall for anomalies longer andaboveTrewin, 2000), and (Jonesalso lead to greater evaporation and drier soils. significant effects on a match. Dry pitches and Nichols the number of Ashes series) and a normal distribution with a mean standard deviation of of 0.8, zero which and is to similar a ENSO observations. correlation The more chance negative than of -0.31 5%, a suggesting that was the is statistically significant. Discussion The physical above mechanism correlation is El behind now Niño discussed. the years, nificantly In austral drier winters than are average sig- reduced (McBride rainfall is lower-than-average soil moisture which can last months afterENSO’s the peak (Timbal n n year N vs aggregate Ashes series score in an Ashe Where data points overlap they have been slightly regate regate score is simply the number of England wins es es into spring of year N+1. The Niño-3 index theref f f points in each quartile is shown in the purple ci series of 1962/1963 and 1965/1966). Each Each data point is marked as year N (scores before 1 Figure 2 shows Niño-3 index vs the In El Niño years, Australia has won 13 The significance of this result was tested aggregate Ashes scoreline (see caption for details). Scores before and 1900, post 1970 have been 1900–1970, colour-coded for clarity. The correlation between axes the is –0.31. two Indeed, it only appears time that that England the has won an seriesAshes following a January–June Niño-3 significantlyindex in the last 100 positive years is the infamous ‘’ 1932/1933: a series seriesthat to this day remains of controversial. out of 17 Ashes series played. On the other hand Australia has only won series 5 in out La of Niña 13 years. The England probability winning of an Ashes series therefore changes by over a factor 50% of in La Niña 2, years, to less than from 25% in El over Niño years. by calculating the correlation between the Ashes series results shown in Figure 2 and randomlygeneratednumbersof sets 000 10 to represent the Niño-3 had index: 32 each members set (the same number as (note (note the quartiles scores do not include the drawn series series that starts in December of year N and continu leads the Ashes series score by 6–12 months. The agg minus the number of Australia wins in each series. marked in and red, scores after 1970 marked in blue). offset from each other to ease The clarity. number o Figure 2. Figure Niño-3January–June anomaly temperature i 180

Weather – July 2009, Vol. 64, No. 7 ENSO and the Ashes series ovcie ytm (Cs cn rvl over travel can (MCSs) systems convective Westoutflowswhere mesoscale fromAfrica, in particularly imagery, satellite in seen be as a density current. Large haboobs can often surface land the along propagates outflow cold-pool cold resultant a the and in downdraught, results clouds convective from precipitation of evaporation The features. these to refer to globally used now is term Arabic the (from ‘haboobs’ as to referred are they of, 1925). There(Sutton, Sudan awarethe on focusing are these authors the of which features, earliest discussion the scientific with published well- phenomenon, a is known systems convective deep from probably is and contributinggenerationto thistower. of cloud, congestus the of tower right-hand cold-pool the below seen is dusty outflow The uplift. resulted dust visible that in outflows and generated precipitation which and clouds, congestus cumulus cumulonimbus of number a of first the was cloud theFigure 1(b), In cloud. the to same the priorwith visible was rainbow a minutesphoto, few is A dust uplifted. but ground,still the reach to appear not be does precipitation can 1(a), Figure virgae in seen Although the Niger. of and regions USA arid in clouds convective precipitating small from outflows pool cold 2005). (Tompkins dynamics regional affect can dust desert airborne of impact radiative the and system climate the of component important an is dust Such atmosphere. the into uplift dust in resultingprocesses pheric atmos- small-scale show photographs The small-scaleatmospheric features Photographsof dust uplift from References h ulf o ds b cl-ol outflows cold-pool by dust of uplift The in uplift dust show (b) and 1(a) Figures Weather.Rev. Oscillation, Southern the and fall rain-Australian between relationships N. Nichols JL, McBride perature. Oscillationand Australian land surface tem- tionshipsbetween the El-Niño Southern JonesDA, TrewinBC J and Lirola S.Lirola and J PowerTimbalB,R, Colman Viviand S, habb Int. J. Climatology , meaning ‘strong wind’) and this

111: 2002. Does soil moisture soil Does 2002. 1998–2004. .2000. On the rela- 1983. Seasonal Seasonal 1983.

20: 697–719. Mon. et al., airbornedust (Haywood thedifferences between modelled and observed radia (GERBIntercomparsion of Longwave and Shortwave rad Sahelnear Niamey, Niger, during monsoon onset, 26 visibledust uplift. (a) Searles Valley near Death Figure1. Two photographs showing cold pool outflow 2539–2559. model outputs. outputs. model numerical and estimate satellite tions, observa- gauge on based analysis P,PA Xie Arkin lets. wave-using analyzed rainfall Australian in variability interannual of modes Westra S, Sharma A.WestraSharma S, 1230–1238. dictability over Australia?over dictability pre-and variability climate influence J. Geophys. ResGeophys. J. (b) (a) . 1997. A 17-year monthly monthly 17-year A 1997. . Bull. Am. Met. Soc Met. Am. Bull. . 111 etal., 2006. Dominant 2006. , D05102., 2005). (© C. M. Grams.) J. ClimateJ. . . 78:

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Valley in California, USA, 16 September 2008; (b) June2007. Figure 1(b) was taken during the GERBILS tionin West Africa, which may be largely due to th sfrom precipitating convective clouds resulting in iation)field campaign, aimed at understanding DOI: 10.1002/wea.403DOI: RoyalMeteorological2009Society,© [email protected]: UK 6BB, RG6 Reading, Gate,EarleyReading, of University Meteorology,of Department Research,Systems WalkerClimate for Institute Joshi, Manoj Correspondenceto: WestAfrican

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