On the identification of ENSO-induced rainfall and runoff variability: a comparison of methods and indices

Abstract

It is known that the El Nino Southern Oscillation (ENSO) phenomenon induces marked climate variability across many parts of the world. However, in seeking useful relationships between ENSO and climate, several indices are available. In addition to the choice of index, previous studies assessing ENSO effects have employed a range of different methods to classify periods as El Nino, La Nina or Neutral. It is therefore clear that significant subjectivity exists in the adoption of ENSO classification schemes. In this study, several ENSO classification methods are applied to a range of ENSO indices. Each method-index combination is investigated to determine which provides the strongest relationship with rainfall and runoff in the Williams River catchment, New South Wales, Australia. The results demonstrate substantial differences between the methods and indices. The Multivariate ENSO Index (or MEI) is found to provide the best classification irrespective of method. The potential for forecasting ENSO-related effects on rainfall, runoff and river abstractions is then investigated. A "rise rule" to account for dynamic ENSO trends is also assessed. Strong relationships were found to exist with runoff (rainfall) up to nine (eight) months in advance of the Summer/autumn period. Implications for improved forecasting of potential river abstractions are apparent.

Synchronicity of historical dry spells in the Southern Hemisphere

“…The four dominant large-scale climate modes operating in the Southern Hemisphere are -ENSO (Chiew et al, 1998;Kiem and Franks, 2001;Verdon et al, 2004), which in this study is represented by the Oceanic Niño Index (ONI) from the United States National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Centre (CPC) (www. cpc.ncep.noaa.gov).…”

Towards understanding hydroclimatic change in Victoria, Australia – preliminary insights into the "Big Dry"

“…Accordingly, the relationship identified between SEA hydroclimatology and the various large-scale climate drivers varies depending on the index and/or classification method chosen (Kiem and Franks, 2001). However, the conclusion that it is the interaction (s) between multiple large-scale climate phenomena that drives SEA climate is not sensitive to the choice of index or classification method.…”

Relationships between the El-Niño Southern Oscillation and spate flows in southern Africa and Australia

“…Kiem and Franks (2001) showed that the MEI outperformed the more traditional SOI and NINO3 indices in identifying ENSO-related changes in rainfall and runoff observations. The MEI can be used to classify ENSO events in various ways, including the approach of Chiew et al (1998), who used mean index values over twelve-month periods from April to March to define both El Niño and La Niña phases.…”

“…The MEI can be used to classify ENSO events in various ways, including the approach of Chiew et al (1998), who used mean index values over twelve-month periods from April to March to define both El Niño and La Niña phases. The method used in this study follows one of the approaches of Kiem and Franks (2001); they used averages of monthly index values over six-month periods from October to March to distinguish annual ENSO phases and claim that this method is the most robust for identifying ENSO variability over the time period being investigated. In this manner, El Niño years are characterised as any year in which the six-month MEI average beginning in the previous October is above 0.5 and La Niña events as years in which this average is below 0.5.…”

“…A more recent development is the Multivariate ENSO Index (MEI) (Wolter and Timlin, 1998). This, being integrated from multiple climate parameters, is less vulnerable to non-ENSO related variability (Kiem and Franks, 2001) because it is able to reflect the complex nature of oceanatmospheric interactions better than indices based on a single variable. The variables used in the MEI include sea-level pressure, sea surface temperature, zonal and meridional components of the surface wind, surface air temperature and total cloudiness fraction of the sky.…”