The main goals of this workshop are to establish current capabilities in sub-seasonal to seasonal prediction, to identify high-priority research topics and demonstration projects and to develop recommendations for the establishment of an international research project. Considerable progress has been made in improving the skill of medium range weather forecasts and in developing operational seasonal forecasting. Forecasting in the intermediate range between medium range and seasonal is difficult as the importance of the initial conditions wanes, and the importance of slower boundary conditions such as sea surface temperature increases but has only a modest influence on the weather and climate, especially away from the tropical regions. Tropi...
Skillful subseasonal-to-seasonal (hereafter S2S; 10 days - 12 weeks) prediction can greatly benefit ...
Seasonal prediction is based on changes in the probability of weather statistics due to changes in s...
Numerical and statistical predictions of simplified models are linearly combined in a sensitivity st...
Seasonal prediction is based on changes in the probability of weather statistics due to changes in s...
This review paper presents an assessment of the current state of knowledge and capability in seasona...
AbstractSeasonal prediction is based on changes in the probability of weather statistics due to chan...
The evidence for predictability of interannual fluctuations in the atmosphere and oceans is reviewed...
Dr Steve Woolnough is a Principal Research Fellow in the Climate directorate of the National Centre ...
The El Niño-Southern Oscillation (ENSO) phenomenon is the main source of the predictability skill i...
The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have ide...
Skilful seasonal climate forecasts have potential to affect decision making in agriculture, health a...
While seasonal outlooks have been operational for many years, until recently the extended-range time...
Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthe...
Although it is impossible to forecast the weather more than a few days in advance, the science of se...
The impact of land surface and atmosphere initialization on the forecast skill of a seasonal predict...
Skillful subseasonal-to-seasonal (hereafter S2S; 10 days - 12 weeks) prediction can greatly benefit ...
Seasonal prediction is based on changes in the probability of weather statistics due to changes in s...
Numerical and statistical predictions of simplified models are linearly combined in a sensitivity st...
Seasonal prediction is based on changes in the probability of weather statistics due to changes in s...
This review paper presents an assessment of the current state of knowledge and capability in seasona...
AbstractSeasonal prediction is based on changes in the probability of weather statistics due to chan...
The evidence for predictability of interannual fluctuations in the atmosphere and oceans is reviewed...
Dr Steve Woolnough is a Principal Research Fellow in the Climate directorate of the National Centre ...
The El Niño-Southern Oscillation (ENSO) phenomenon is the main source of the predictability skill i...
The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have ide...
Skilful seasonal climate forecasts have potential to affect decision making in agriculture, health a...
While seasonal outlooks have been operational for many years, until recently the extended-range time...
Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthe...
Although it is impossible to forecast the weather more than a few days in advance, the science of se...
The impact of land surface and atmosphere initialization on the forecast skill of a seasonal predict...
Skillful subseasonal-to-seasonal (hereafter S2S; 10 days - 12 weeks) prediction can greatly benefit ...
Seasonal prediction is based on changes in the probability of weather statistics due to changes in s...
Numerical and statistical predictions of simplified models are linearly combined in a sensitivity st...