Medium-range, monthly, and seasonal prediction for Europe and the use of forecast information
Medium-range, monthly, and seasonal prediction for Europe and the use of forecast information
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DOI：
10.1175/jcli3944.1
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发表时间：
2006-12-01
影响因子：
4.9
通讯作者：
Doblas-Reyes, Francisco J.
中科院分区：
文献类型：
--
作者：
Rodwell, Mark J.;Doblas-Reyes, Francisco J.
欧洲中期天气预报中心在2003年欧洲夏季热浪期间进行的业务概率（集合）预报表明，在中期（3-10天）和月度（10-30天）时间尺度上具有显著的技能。对许多中期、月度和季节性预报的更一般性的“统一”分析证实了欧洲第一个月气温的高度概率预报能力。统一分析还确定了欧洲的季节性可预测性，这在季节性预测中尚未实现。有趣的是，初始大气状态似乎是重要的，即使是2个月的耦合forecast.Seasonal耦合模式预测捕捉到的一般水平，观察到的欧洲确定性的可预测性与持续性的异常。对改进季节性预报的可能性进行了审查。这包括多模型和概率技术，以及“机会窗口”的潜力，其中更好地表示边界条件的影响（例如，海洋表面温度和土壤湿度）可能会改善预报。“完美耦合模式”潜在可预测性估计对所使用的耦合模式敏感，因此尚不可能估计季节性可预测性的最终水平。应对天气或气候事件的方法）进行了调查。使用预测信息，以减少波动性，以及减少预期费用的重要性突出。考虑了天气预报可能影响减灾行动成本的可能性。简化的分析导致了不同的结论预测的有用性，可以指导决策的发展“端到端”（预测到用户的决策）系统。
Operational probabilistic (ensemble) forecasts made at ECMWF during the European summer heat wave of 2003 indicate significant skill on medium (3-10 day) and monthly (10-30 day) time scales. A more general "unified" analysis of many medium-range, monthly, and seasonal forecasts confirms a high degree of probabilistic forecast skill for European temperatures over the first month. The unified analysis also identifies seasonal predictability for Europe, which is not yet realized in seasonal forecasts. Interestingly, the initial atmospheric state appears to be important even for month 2 of a coupled forecast.Seasonal coupled model forecasts capture the general level of observed European deterministic predictability associated with the persistence of anomalies. A review is made of the possibilities to improve seasonal forecasts. This includes multimodel and probabilistic techniques and the potential for "windows of opportunity" where better representation of the effects of boundary conditions (e.g., sea surface temperature and soil moisture) may improve forecasts. "Perfect coupled model" potential predictability estimates are sensitive to the coupled model used and so it is not yet possible to estimate ultimate levels of seasonal predictability.The impact of forecast information on different users with different mitigation strategies (i.e., ways of coping with a weather or climate event) is investigated. The importance of using forecast information to reduce volatility as well as reducing the expected expense is highlighted. The possibility that weather forecasts can affect the cost of mitigating actions is considered. The simplified analysis leads to different conclusions about the usefulness of forecasts that could guide decisions about the development of "end-to-end" (forecast-to-user decision) systems.