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The future of buy-to-let
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Land Commodities Asset Management AG, 2012
Climate Risk Primer: Australian Broadacre Cropping
A Primer on the Facts and Current State of the Science Relating to the Spatial Variabilityof Climate Risk and the Implications for Australian Broadacre Cropping Investors
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Background
Much of the variability in Australias climate is connectedwith the atmospheric phenomenon known as the SouthernOscillation, a major see-saw of air pressure and rainfallpatterns between the Australian/Indonesian region and theeastern Pacific. The Southern Oscillation gives rise to twomajor weather phenomena: El Nio, generally associatedwith dryer conditions in Australia and its opposite twin, La
Nia, generally associated with wetter conditions.
Given the challenges of accurately predicting weatherconditions over the longer term, agricultural planning anddecision making is usually focused on the short-term; namelythe current crop or pasture growing season and periods outto a maximum of one year. These timescales are exactlythose impacted by the extremes of the Southern Oscillation- La Nia and El Nio - both of which often last for about
10 -12 months, and typically have the biggest impact inthe Australian winter and spring; a key period agriculturallygiven the winter to spring growing season of the AustralianWheatbelt.
Figure 1: Schematic maps indicative of typical rainfall tendencies during El Nio and La Nia events
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El Nio
El Nio refers to the weather conditions which occur whensea surface temperatures in the central to eastern PacificOcean are significantly warmer than normal. This recursevery three to eight years and is generally associated with astrong negative phase in the Southern Oscillation pendulum.
The El Nio phenomenon significantly impacts rainfall and
ensuing crop yields in many parts of the world. In Australia,El Nio events are often associated with severe droughtconditions. Since rainfall variability is the dominant factorcausing year-to-year fluctuations in Australian wheat yield,El Nio is the most significant climate phenomenon withrespect to volatility in farm operating income (and hencelandowner and operator risk).
Whilst in aggregate the relationship between rainfall andyield is broadly similar (i.e. in the majority of cases El Nioevents are associated with reduced yields) the effects differspatially and temporally in their manifestations and impacts
depending on the type of El Nio event. Various studies haveinvestigated the relationship between ENSO and Australianrainfall and found it to be significant, particularly in easternand southern parts of Australia (Pittock, 1975; Ropeleswskiand Halpert, 1987; McBride and Nicholls, 1983; Stone et al.,1996, Mason and Goddard, 2001).
Figure 2 shows the average rainfall pattern in the growingseason during the 12 most extreme El Nio events in the lastcentury (1905, 1914, 1940, 1941, 1946, 1965, 1972, 1977,1982, 1991, 1994 and 1997). As Figure 2 demonstrates,whilst some parts of the extreme south of the western partof Australia receive below average rainfall during El Nio
growing seasons, the risk of drought is higher in the eastern,southern and northern regions.
Figure 3 shows the average rainfall pattern in the summerduring the same 12 El Nio events. As Figure 3 demonstrates,in contrast to the majority of Australia, the eastern edgeof the south western Wheatbelt region can receive aboveaverage rainfall during the summer months in El Nio years.Whilst this can increase the risk of crop damage if excessiveand persistent rainfall is received during the early summerharvest period, these rains can also result in higher residualsoil moisture which can act to boost yields by mitigating the
risk of lower rainfall in the following growing season. Thismay explain the tendency of low rainfall far eastern districts inthe Western Australian Wheatbelt to produce above averageyields in some dryer years when higher rainfall districts to thewest produce below average yields.
(Note: Although Figures 2 & 3 describe the average rainfallduring El Nio, they should not be misinterpreted as aguarantee that any particular region will always experience atypical response to an El Nio event.)
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Figure 2: Average growing season rainfall anomalies (deciles) during the 12 most extreme El Nio years in the last century
Figure 3: Average summer rainfall anomalies (deciles) during the 12 most extreme El Nio years in the last century
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The most comprehensive studies (Potgieter et al., 2002,2005) examining the spatial variability of wheat yields inAustralia during El Nio years separated the 24 occurrencesover the last century (the period 1900 to 2002) into threecategories of El Nio depending on their effect on rainfalland yields. Figures 4 to 6 from this study show the spatialvariability of the impact on Australian wheat yields.
The first category (Figure 4) resulted in a marked reduction
in rainfall and yields in north eastern regions, but had alesser effect on other parts of Australia, with some areas inthe south east, south and south west experiencing higher
rainfall and yields. The second category (Figure 5) resulted ina reduction in rainfall and yields in almost all regions exceptfor the south west (including the lower rainfall Shires of thesouth west which also experienced little or no reductionin rainfall and yields), with some areas in the south westexperiencing higher rainfall and yields. The third category(Figure 6) resulted in a reduction in rainfall and yields inalmost all regions, but the effect was very severe in theeastern and southern regions and less severe in the south
west, with some areas of the south west experiencing higherrainfall and yields.
Figure 4: First category of El Nio event (number of standard deviations of the average anomaly in annual wheat yieldsfrom the long-term mean: 9 years out of 100 years)
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Figure 5: Second category of El Nio event (number of standard deviations of the average anomaly in annual wheat yieldsfrom the long-term mean: 6 out of 100 years)
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Figure 6: Third category of El Nio event (number of standard deviations of the average anomaly in annual wheat yieldsfrom the long-term mean: 9 years out of 100 years)
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La Nia
La Nia refers to the weather conditions which occur whensea surface temperatures in the central to eastern PacificOcean are significantly cooler than normal. This occurswith broadly similar frequency to El Nio and is generallyassociated with a strong positive phase in the SouthernOscillation pendulum.
The effect of La Nia on wheat yields can be either positiveor negative depending on the extent and timing of theincreased rainfall usually associated with the phenomenon.If additional rainfall is experienced during the growingseason this can have a positive impact on yields, however, ifexcessive rainfall results in waterlogging of soils, or in extremecases flooding, the effects can be detrimental. Additionally,excessive and persistent rainfall during the harvest seasoncan damage crops, negatively impacting yields.
As with El Nio, the effects of La Nia differ spatially andtemporally in their manifestations and impacts. Figure 7
shows the average rainfall pattern in the winter and autumngrowing season during the 12 most extreme La Nia eventsin the last century (1910, 1916, 1917, 1938, 1950, 1955,1956, 1971, 1973, 1975, 1988 and 1998). As Figure 7demonstrates, whilst some parts of the south west receiveabove average rainfall during La Nia growing seasons,the risk of flooding is predominantly associated with thenorthern, central, southern and eastern regions.
Recent La Nia years include 197374, Brisbanes worstflooding of the 20th century, the 19982000 period whichsaw flooding across parts of northern and eastern Australiaand the 2011 floods which resulted in more than AU$2
billion of crop damage in eastern Australia.
Figure 8 shows the average rainfall pattern in the summerduring the same 12 La Nia events. As Figure 8 demonstrates,in La Nia years excessive rainfall is more commonly associatedwith the northern and eastern regions during the summermonths. Whilst increased soil moisture from higher summerrainfall can improve yields in the next growing season, therisk of excessive rainfall early in the summer resulting in cropdamage during harvest time is lower in the south west ofAustralia than it is in the eastern and north eastern regions.
(Note: Although Figures 7 & 8 describe the average rainfallduring La Nia, they should not be misinterpreted as aguarantee that any particular region will always experience atypical response to a La Nia event.)
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Figure 7: Average growing season rainfall anomalies (deciles) during the 12 most extreme La Nia years in the last century
Figure 8: Average summer rainfall anomalies (deciles) during the 12 most extreme La Nia years in the last century
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Summary and Conclusion
In conclusion, for the majority of extreme weather years occurring in Australia over the last century,owning farms in different parts of Western Australia, as opposed to different parts of Australia aswhole, would have been a more effective diversification strategy from the perspective of mitigating
climate related risk.
References
BOM, 2010: Australian rainfall patterns during La Nia events. Australian Bureau of Meteorology, Product Code: IDCKGEERL0. Availableonline at: http://www.bom.gov.au/climate/enso/ninacomp.shtml
BOM, 2010: Australian rainfall patterns during El Nio events. Australian Bureau of Meteorology, Product Code: IDCKGEERE0. Availableonline at: http://www.bom.gov.au/climate/enso/ninocomp.shtml
Mason, S.J. and L. Goddard, 2001: Probabilistic precipitation anomalies associated with ENSO. Bulletin of the American MeteorologicalSociety. 82(4), 619-638.
McBride, J. L. and N. Nicholls, 1983: Seasonal relationships between Australian rainfall and the Southern Oscillation. Monthly WeatherReport. 111(1822), 1998-2003.
Pittock, A.B. 1975: Climatic change and the patterns of variation in Australian rainfall. Search. 6(11-12), 498-504.
Potgieter, A.B., G.L. Hammer and D. Butler, 2002: Spatial and temporal patterns in Australian wheat yield and their relationship with ENSO.Australian Journal of Agricultural Research. 53, 77-89.
Potgieter, A. B., G. L. Hammer, H. Meinke, R. C. Stone, L. Goddard, 2005: Three Putative Types of El Nio Revealed by Spatial Variability inImpact on Australian Wheat Yield. J. Climate, 18, 15661574
Ropelewski, C.F. and M.S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Nio/Southern Oscillation.Monthly Weather Review. 115, 1606-1626.
Stone, R.C., G.L. Hammer and T. Marcussen, 1996: Prediction of global rainfall probabilities using phases of the Southern Oscillation Index.
Nature. 384, 252-255.
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