ENSO forecast application

Monthly climate outlook notes

At the University of Reading and UK Met Office

Role in SHEAR

• Provides early warnings of potentially damaging temperature and precipitation extremes throughout the developing world.
• Assesses the accuracy and reliability of contemporary subseasonal and seasonal prediction systems in East Africa, particularly for forecasts of temperature and rainfall extremes.

Context

Many humanitarian crises are directly or indirectly affected by extreme temperatures and rainfall, including damaging droughts and floods that are linked to El Niño and La Niña events. Early warnings of the potential for these extreme events are critical to inform forecast-based finance efforts, as well as other anticipatory aid strategies to mobilise resources ahead of impending crises. While many national meteorological agencies issue subseasonal and seasonal forecasts routinely, these forecasts often focus on the likelihood of relatively mundane events, such as 'average', 'above average' or 'below average' conditions, which is not useful to a humanitarian community that is sensitive to extremes. Further, the accuracy and reliability of forecasts for extreme events are not clear, particularly in the developing world where there are few available observations to verify forecasts.

Aims

The project aims to produce monthly outlooks of the likelihood of temperature and precipitation extremes throughout the developing world. The project also aims to assess the accuracy and reliability of contemporary forecasting systems, including techniques for calibrating these systems to improve their accuracy and reliability.

Approach

Each month, subseasonal and seasonal forecasts are combined from global modelling centres to produce a 'climate outlook note', which summarises predictions of temperature and rainfall extremes at the country level for the next one to six months. The note also incorporates forecasts of El Niño and La Niña events and their global impacts.

Innovation

The climate outlook notes are designed to focus on the most extreme conditions (upper and lower deciles), whereas many currently available products focus on only the likelihood of 'above average' or 'below average'. The project is also exploring methods to weight individual forecast systems by their historical accuracy, including weighting by country, season and climatic condition, to produce more accurate, multi-model forecasts of extreme conditions.

If you would like to find out more about this work, please get in touch.