Affiliation:
1. Climate Prediction Center, National Centers for Environmental Prediction, Camp Springs, Maryland
Abstract
Abstract
Using the retrospective forecasts from the National Centers for Environmental Prediction (NCEP) coupled atmosphere–ocean Climate Forecast System (CFS) and the Atmospheric Model Intercomparison Project (AMIP) simulations from its uncoupled atmospheric component, the NCEP Global Forecast System (GFS), the relative roles of atmospheric and land initial conditions and the lower boundary condition of sea surface temperatures (SSTs) for the prediction of monthly-mean temperature are investigated. The analysis focuses on the lead-time dependence of monthly-mean prediction skill and its asymptotic value for longer lead times, which could be attributed the atmospheric response to the slowly varying SST. The results show that the observed atmospheric and land initial conditions improve the skill of monthly-mean prediction in the extratropics but have little influence in the tropics. However, the influence of initial atmospheric and land conditions in the extratropics decays rapidly. For 30-day-lead predictions, the global-mean forecast skill of monthly means is found to reach an asymptotic value that is primarily determined by the SST anomalies. The lead time at which initial conditions lose their influence varies spatially. In addition, the initial atmospheric and land conditions are found to have longer impacts in northern winter and spring than in summer and fall. The relevance of the results for constructing lagged ensemble forecasts is discussed.
Publisher
American Meteorological Society
Cited by
30 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献