A multiple model assessment of seasonal climate forecast skill for applications.

摘要: Skilful seasonal climate forecasts have potential to affect decision making in agriculture, health and water management. Organizations such as the National Oceanic Atmospheric Administration (NOAA) are currently planning move towards a services paradigm, which will rest heavily on skilful at (1 9 months) timescales from coupled atmosphere-land-ocean models. We present careful analysis of predictive skill temperature precipitation eight forecast models with joint distribution observations forecasts. Using correlation coefficient, shift conditional given can be detected, determines usefulness for applications. Results suggest there is deficiency beyond month-1, having more pronounced drop than temperature. At long lead times only equatorial Pacific Ocean exhibits significant skill. This could an influence planned use these results may also seen benchmark current prediction capability using (dynamic) couple