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ENVIRONMENTAL RISKS - PROJECT SUMMARY

Stratospheric influence on monthly-to-seasonal climate predictability

Gaëlle OUZEAU, AXA Research Fellow

  • Nationality
    French citizen
  • Year of selection
    2009
  • Institution
  • Country
    France

Support by the AXA Research Fund

TYPE OF SUPPORT GRANTED AMOUNT DURATION
Doctoral Fellowships 120,000 3 years

Project Informations

Somewhere over the Troposphere

In 1999, three extreme storms hit Europe, taking more than 130 lives and causing about 130 billion euros in economic losses. Today, dynamical seasonal forecasting systems are mainly based on oceanic forcing, but they remain particularly poor in the northern extratropics, including over Europe, where the variability is only weakly influenced by oceanic conditions.

To improve the forecasting from monthly to seasonal timescales, Gaelle Ouzeau is looking for additional sources of long-range climate predictability and studying the stratosphere, the second major layer of Earth’s atmosphere. She will develop and test a seasonal forecasting system using both oceanic and stratospheric sources of climate memory, combined with dynamical and statistical tools. Her results may enable better prediction of extreme climate events, such as cold spells over Europe in the winter, which could be rougher in the coming decades.

My research focuses on stratospheric influence on Northern Hemisphere winter climate variability and predictability. In Northern extratropics, the wintertime climate shows large intraseasonal and interannual fluctuations compared to other regions and seasons. As experienced in Europe during the winter 2009-2010, cold spells induce particularly strong socio-economic impacts. Both statistical analysis and improvements in the predictability of such climate events are therefore crucial challenges for scientists and decision makers. Current dynamical seasonal forecasting systems, based on coupled ocean-atmosphere models, still show low predictability in Northern mid-latitudes. The main objective of the PhD is to look for additional sources of long-range climate predictability in the middle atmosphere and to propose simple statistical models for improving the prediction of stratospheric variability..


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