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Ranking seasonal rainfall forecast skill of emerging and developing economies

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dc.contributor.author Landman, WA
dc.contributor.author Barnston, AG
dc.contributor.author Vogel, C
dc.date.accessioned 2016-06-27T08:40:33Z
dc.date.available 2016-06-27T08:40:33Z
dc.date.issued 2015-09
dc.identifier.citation Landman, WA, Barnston, AG and Vogel, C. 2015. Ranking seasonal rainfall forecast skill of emerging and developing economies. In: 31st Conference of the South African Society for Atmospheric Science: Applying the weather, Hennops River Valley, Centurion, South Africa, 21-22 September 2015 en_US
dc.identifier.uri http://hdl.handle.net/10204/8584
dc.description 31st Conference of the South African Society for Atmospheric Science: Applying the weather, Hennops River Valley, Centurion, South Africa, 21-22 September 2015. en_US
dc.description.abstract Some of the biggest emerging markets economies include countries in South America, Asia and Africa. In the global south, political and developmental similarities (e.g. climate variability occurring in conjunction with marked developmental challenges) offer opportunities for comparative research and thereby possible societal benefits (e.g. enhanced disaster risk reduction). In fact, countries or geographical regions of the world significantly affected by climate extremes may consider collaboration on issues such as understanding and modelling of the climate system, especially if there is a common dominant and somewhat predictable climate mode such as the El Niño-Southern Oscillation (ENSO) affecting the climate variability over these regions. Notwithstanding the value of enhanced understanding and preparedness for ENSO, better predictions are not enough to reduce the risks associated with such events. The socio-economic and political context in which forecasts are located also needs to be understood. Here we present seasonal forecast skill over a large number of regions including emerging or developing countries, but also for a small number of developed regions, in order to rank their ENSO-related seasonal rainfall predictability in an attempt to cluster regions of similar predictability. This paper attempts to find out where southern Africa seasonal rainfall predictability ranks with a good number of other countries or regions linked to ENSO so that collaboration may be sought and established. en_US
dc.language.iso en en_US
dc.publisher SASAS en_US
dc.relation.ispartofseries Workflow;15727
dc.subject Emerging economies en_US
dc.subject El Niño-Southern Oscillation en_US
dc.subject ENSO en_US
dc.subject Forecast skill en_US
dc.subject Seasonal climate modelling en_US
dc.title Ranking seasonal rainfall forecast skill of emerging and developing economies en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Landman, W., Barnston, A., & Vogel, C. (2015). Ranking seasonal rainfall forecast skill of emerging and developing economies. SASAS. http://hdl.handle.net/10204/8584 en_ZA
dc.identifier.chicagocitation Landman, WA, AG Barnston, and C Vogel. "Ranking seasonal rainfall forecast skill of emerging and developing economies." (2015): http://hdl.handle.net/10204/8584 en_ZA
dc.identifier.vancouvercitation Landman W, Barnston A, Vogel C, Ranking seasonal rainfall forecast skill of emerging and developing economies; SASAS; 2015. http://hdl.handle.net/10204/8584 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Landman, WA AU - Barnston, AG AU - Vogel, C AB - Some of the biggest emerging markets economies include countries in South America, Asia and Africa. In the global south, political and developmental similarities (e.g. climate variability occurring in conjunction with marked developmental challenges) offer opportunities for comparative research and thereby possible societal benefits (e.g. enhanced disaster risk reduction). In fact, countries or geographical regions of the world significantly affected by climate extremes may consider collaboration on issues such as understanding and modelling of the climate system, especially if there is a common dominant and somewhat predictable climate mode such as the El Niño-Southern Oscillation (ENSO) affecting the climate variability over these regions. Notwithstanding the value of enhanced understanding and preparedness for ENSO, better predictions are not enough to reduce the risks associated with such events. The socio-economic and political context in which forecasts are located also needs to be understood. Here we present seasonal forecast skill over a large number of regions including emerging or developing countries, but also for a small number of developed regions, in order to rank their ENSO-related seasonal rainfall predictability in an attempt to cluster regions of similar predictability. This paper attempts to find out where southern Africa seasonal rainfall predictability ranks with a good number of other countries or regions linked to ENSO so that collaboration may be sought and established. DA - 2015-09 DB - ResearchSpace DP - CSIR KW - Emerging economies KW - El Niño-Southern Oscillation KW - ENSO KW - Forecast skill KW - Seasonal climate modelling LK - https://researchspace.csir.co.za PY - 2015 T1 - Ranking seasonal rainfall forecast skill of emerging and developing economies TI - Ranking seasonal rainfall forecast skill of emerging and developing economies UR - http://hdl.handle.net/10204/8584 ER - en_ZA


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