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为了每年更新迄今为止的强迫变暖和受约束的气候预测
A Ribes1, O Tessiot2,3, P M Forster4
1Météo France, CNRS, Univ. Toulouse, CNRM, Toulouse, France. aurelien.ribes@meteo.fr.
定期更新气候变化预测,以新的观测数据提高准确性. 年度更新提供了当前人为变暖和未来气候趋势的稳定,强有力的指标.
科学领域:
- 气候科学 气候科学
- 统计建模 统计建模
- 地球系统科学 地球系统科学
背景情况:
- 人类造成的气候变化需要经常更新当前和未来的气候状况.
- 最近的IPCC报告使用了具有观察约束的统计方法来估计气候变化.
- 随着新数据的出现,需要确定更新气候变化预测的最佳方法.
研究的目的:
- 通过使用新的观测数据,研究如何最好地更新气候变化预测.
- 评估纳入年度观测数据对预测准确性的影响.
- 评估当前年气候变暖估计的稳定性,作为气候指标.
主要方法:
- 利用一个完美的模型框架进行模拟.
- 将连续几年的观测数据纳入预测.
- 分析了更新的气候预测的准确性和可变性.
主要成果:
- 结合每一年的观测数据,可以提高气候预测的准确性.
- 该过程不会引入显著的虚假年对年变化.
- 估计今年的强迫变暖显示出高度稳定性.
结论:
- 每年更新新的观测数据对于完善气候变化预测是有益的.
- 当前一年的变暖估计是气候系统状态的可靠指标.
- 这种方法提高了气候变化评估的可靠性.
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