Decadal Climate Predictions (DCP) have gained considerable attention for their potential utility in promoting optimised plans of adaptation to climate change and variability. Their effective applicability to a targeted problem is nevertheless conditional on a detailed evaluation of their ability to simulate the near-term climate evolution under specific conditions. Here we explore the performance of the IPSL-CM5A-LR DCP system in predicting air temperature over Europe, by proposing a systematic assessessment of the prediction skill for different time windows (periods of the calendar time, forecast years and months/seasons). In this framework, we also compare raw and de-biased hindcasts, in which the temperature outputs have been corrected using a quantile matching method. The systematic analysis allows to discern certain conditions conferring larger predictability, which we find to be intermittent in time. The predictions appear more skilful around the 1960s and after the 1980s, in coincidence with large shifts of the Atlantic Multidecadal Variability, which are well reproduced in the hindcasts. Averages on longer forecast periods also generally imply better prediction skill, while the best predicted months appear to be mainly those between late spring and early autumn. Moreover, we find an overall added value due to initialisation, while de-biased predictions significantly outperform raw predictions only for a few specific time windows. Finally, we discuss the potential implications of the proposed systematic exploration of skill opportunities in DCPs for integrated applications in climate sensitive sectors.

年代际气候预测 (DCP) 因其在促进适应气候变化和变率的优化计划方面的潜在效用而获得了相当多的关注。然而，它们对目标问题的有效适用性取决于对其在特定条件下模拟近期气候演变的能力的详细评估。在这里，我们通过提出对不同时间窗口（日历时间段、预测年和月/季）的预测技能的系统评估，探索了 IPSL-CM5A-LR DCP 系统在预测欧洲气温方面的性能。在这个框架中，我们还比较了原始和去偏差的后报，其中使用分位数匹配方法校正了温度输出。系统分析允许辨别赋予更大可预测性的某些条件，我们发现这些条件在时间上是间歇性的。在 1960 年代前后和 1980 年代之后，这些预测似乎更加巧妙，恰逢大西洋多年代际变率的巨大变化，这些变化在后报中得到了很好的再现。更长预测期的平均值通常也意味着更好的预测技能，而最佳预测月份似乎主要是晚春和初秋之间的月份。此外，我们发现由于初始化的整体附加值，而去偏差预测仅在几个特定时间窗口内显着优于原始预测。最后，我们讨论了提议的系统探索 DCP 技能机会的潜在影响，以用于气候敏感部门的综合应用。