dc.contributor.author |
Landman, WA
|
|
dc.contributor.author |
Barnston, AG
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dc.contributor.author |
Vogel, C
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|
dc.date.accessioned |
2016-06-27T08:40:33Z |
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dc.date.available |
2016-06-27T08:40:33Z |
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dc.date.issued |
2015-09 |
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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
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|
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 -
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en_ZA |