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Prediction of Climate Variations and its Application in the Southern African Region

Environment / Energy (Climate Change)

Republic of South Africa

Terminated

Prediction of Climate Variations and its Application in the Southern African Region

The “Virtual Earth” Will Change Agriculture in South Africa

  • SDGs13
  • SDGs02

Principal Investigator

    • Head of Laboratory, Dr.
      YAMAGATA Toshio

      Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
    • researchmap

ODA Recipient Country

Republic of South Africa

Research Institutions in Japan

Japan Agency for Marine-Earth Science and Technology (JAMSTEC) / The University of Tokyo

Research Institutions in Counterpart Country

Applied Centre for Climate and Earth Systems Science (ACCESS), etc.

Adoption fiscal year

FY 2009

Research Period

3 Years

Overview of the Research Project

Predicting climate variations up to a year in advance to mitigate the effect of abnormal weather
The southern African region is vulnerable to abnormal weather and researchers are trying to improve skills of seasonal forecasting to mitigate the impacts of abnormal weather. Specifically, they are using a high-resolution ocean-atmosphere coupled model (SINTEX-F) (a virtual earth on the Earth Simulator supercomputer that reproduces interactions between the atmosphere and oceans) to predict global climate variations up to one year in advance. These prediction results will be used to conduct downscaling seasonal prediction for southern Africa.

Seasonal prediction skills will also be applied in Japan
This project has clarified the mechanism of the subtropical dipole modes in the southern Indian Ocean and the South Atlantic, which induce abnormal weather in South Africa. It also successfully predicted heavy rainfalls during the summer of 2010-2011. In the future, this technology will be applied to agriculture, etc. in southern Africa and seasonal prediction in Japan.

Photo gallery

Farmers in Limpopo Province benefit from forecasts.

Farmers in Limpopo Province benefit from forecasts.

Table Mountain in Cape Town. Improved seasonal predictions achieved by this project will contribute to the production of wine grapes grown at the base of the mountain.

Table Mountain in Cape Town. Improved seasonal predictions achieved by this project will contribute to the production of wine grapes grown at the base of the mountain.

South African research team at agricultural field

South African research team at agricultural field

Associate members at ACCESS.

Associate members at ACCESS.

Research Project Web site

Press Release

Links

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