El Niño Southern Oscillation (ENSO) is the fluctuation of sea-surface temperatures, rainfall, air pressure, and atmospheric circulation that occurs in the equatorial Pacific Ocean. ENSO events are cyclical and occur every 3-7 years. Understanding ENSO is important because it is not a simple weather variable but a major climate change that affects areas extending far past the Pacific Ocean. El Niño and La Niña constitute the hydro-meteorological phenomena of ENSO in which sea surface water temperature varies from the average. Specifically, El Nino conditions are defined as when the water temperature in the Nino 3.4 Region (5°N-5°S, 120°-170°W) varies by 0.5ºC or more above the global average water temperature for at least five consecutive three month time intervals. The same classification system is used in identifying La Nina except temperatures must remain at least 0.5ºC below the average. In the western Pacific, El Nino causes drought like conditions by decreasing the amount of precipitation and cloud cover. It was hypothesized that due to its influence on the climates of nations in the western Pacific, ENSO would also have a strong inverse relationship to their agricultural GDP’s (gross domestic products) and overall GDP’s (due to increasing water temperatures causing less precipitation). Sponsors: National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) Goddard Institute for Space Studies (GISS) New York City Research Initiative (NYCRI) National Science Foundation (NSF) CUNY Queensborough Community College Contributors: Matthew O’Connell (HSS) Akilah Lewis (UG) Mr. Daniel Mezzafonte (HST) Dr. Paul Marchese (PI) An Analysis of ENSO Phenomena’s Effect on the GDP of Western Pacific Nations Figure 3: Over the entire available data set, the Philippines’ annual agricultural GDP had a moderate correlation coefficient of.388 supporting the antithesis. Table 1: Correlations varied extensively between nations and time periods leaving inconclusive results. Abstract Introduction Materials and Methods References Results Conclusion and Future Work Figure 2: ENSO events occur every two to seven years but usually only occur for several months. Figure 1: The Niño 3.4 index is a location in the equatorial Pacific where seas surface temperature readings are taken by buoys for the National Weather Service. (Image source: ) Figure 4: The quarterly GDP data provided more data points allowing for correlations to be calculated during the time frames of discrete ENSO phenomena. This provided much stronger values. El Niño Southern Oscillation (ENSO) is a climatological phenomenon that occurs in the Tropical Pacific Ocean and has a direct influence on the weather of western Pacific nations. This study evaluates the potential effect of ENSO on the economies of nations in the area. It was hypothesized that decreased precipitation in the western Tropical Pacific region during El Niño events cause decreases in the agricultural production in the region, and overall GDP. Furthermore, during the anti- El Niño, or La Niña, the opposite effect of increased agricultural GDP and overall GDP is expected. Gross Domestic Product (GDP) data were obtained from the World Bank, and the Bank of Indonesia. Sea surface temperatures, of Niño 3.4 data, were obtained from the NOAA National Climate Data Center. There is an inconclusive correlation between the annual agricultural/total GDP and the ENSO signal. By examining data between smaller time segments of the overall timeframe, more conclusive results could not be discerned. Evaluating ENSO’s influence on annual GDP, a correlation coefficient of was determined. It supported the hypothesis, as did correlations obtained from examining smaller sections of the overall timeframe. Indonesia’s quarterly negated non- oil GDP was independently correlated with ENSO providing better insight on the variables’ relationship during discrete ENSO phenomena. The results provided strong correlation coefficients of and in support of the antithesis as well as in support of the hypothesis. An economic anomaly known as the East Asian Financial Crisis may have been the cause of the unexpected however more data is needed to be certain. Overall, the results demonstrated weak to moderate correlations present between variables. ENSO data was obtained from the National Weather Service’s Climate Prediction Center’s monthly readings of the average sea surface temperature *in the Niño 3.4 index (Figure 1). Time periods that qualified as ENSO events were delineated and graphed by their distance from average sea surface temperature (Figure 2). Annual agricultural GDP and annual overall GDP was obtained from The World Bank* for several nations in the western Pacific. The annual percent change of these values was graphed against ENSO within all-inclusive timeframes (Figures 3). Correlations were calculated on the data within both timeframes yielding inconclusive results (Table 1). Quarterly current GDP of Indonesia was obtained from The Bank of Indonesia*. This data was graphed with a polynomial trend line. The data’s difference from the trend line was graphed against ENSO and correlations between the ENSO and the novel dataset were calculated. Results were overall inconclusive. Overall agricultural GDP and ENSO correlations weakly supported the antithesis. Overall total GDP and ENSO correlations weakly supported the hypothesis. However, once the data sets were broken into smaller timespans it became clear that most had both negative and positive values (conveying that the data of certain timeframes supported the hypothesis and others supported the antithesis). Correlating quarterly GDP of Indonesia within the timeframes of distinct phenomena provided much stronger correlations however they did not concur (.83 and.62 supported the antithesis while -.42 did not). GDP is subject to influence from many external factors. One example is the East Asian Financial Crisis of 1997 which likely affected data from the later 1990’s to early 2000’s. Future work could explore more influences on GDP and develop ways to mitigate their influence on the data so that relationships between ENSO and agricultural/total GDP can be better understood. More discrete ENSO occurrences should be analyzed and correlated to quarterly GDP’s to confirm to strengthen arguments for and/or against the hypothesis. All Availabl e Data Philippines Agricultural GDP Indonesia Agricultural GDP Philippines Overall GDP Indonesia Overall GDP N/A Correlation Coefficients of Annual Agricultural/Total GDP of Selected Nations and ENSO Table 1: Correlations varied extensively between nations and time periods leaving inconclusive results. Limitations A major limitation of using the annually calculated data of The World Bank is that ENSO phenomena last, at most, only a few years. This left only a few data points to represent phenomena over the total timeframe, significantly mitigating any present correlations. With more data points stronger correlations would be found, as observed with the Indonesia Quarterly GDP data. However, by limiting the timeframe from to , important data was omitted. Aldrian, E. E., Gates, L., & Widodo, F. H. (2007). Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the re-analyses: The role of ENSO. Theoretical & Applied Climatology, 87(1-4), doi: /s Climate Prediction Center Internet Team. (2012, April 26). Frequently Asked Questions about El Nino and La Nina. Retrieved from Definitions of El Nino, La Nina, and ENSO. (n.d.). Retrieved from El Nino Related Global Temperature & Precipitation Patterns. (2005, December 19). Retrieved from El Niño/Southern Oscillation (ENSO) Technical Discussion. (n.d.). Retrieved from Erasmi, S., Propastin, P., Kappas, M., & Panferov, O. (2009). Spatial Patterns of NDVI Variation over Indonesia and Their Relationship to ENSO Warm Events during the Period 1982–2006. 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