【中文介绍】

       验证气候预估可信度的最有说服力的方法是量化过去预估与后续观测结果的一致性程度。自1990年IPCC发布第一次气候变化评估报告以来，30多年已经过去，这一时间长度足以开展回顾性分析并回答一个关键问题：IPCC系列评估报告中的未来气候变化预估是否可信？基于这30多年的观测数据，已有部分研究分析了模式对温度、二氧化碳和海平面高度变化预估的可信度。作为水文循环的核心组分，降水对农业生产、社会经济、自然生态和人类生活至关重要。然而，模式对降水变化预估的可信度如何尚不清楚。

      为此，课题组使用IPCC第三（TAR）、第四（AR4）和第五次（AR5）评估报告中的多模式多情景试验数据，研究了气候模式对全球陆地降水变化预估的信度，发现在全球尺度上，模式能提前几年到十几年预估出2002−2020年陆地降水的气候态变化；但在区域尺度上的预估技巧有限，模式仅在北半球中高纬陆地表现出一定的预估技巧，这可能部分源于区域尺度上降水变化的信噪比较低。此外，他们还分析了模式对全球和区域尺度降水变化趋势预估的可信度。由于降水变化趋势的信噪比远低于气候态变化的信噪比，特别是在相对较短（几年到十几年）的时间尺度和较小的空间尺度上，模式对全球和区域尺度上降水变化趋势预估的信度均要低于气候态的。

  【英文介绍】

  The most convincing way of validating the credibility of climate projections is to quantify the extent to which past projections agree with subsequent observations. More than thirty years have passed since the First Assessment Report (FAR) was published in 1990 (IPCC, 1990). This length of the period is sufficient to conduct a retroactive analysis and answer a key question: are the projections of future climate changes credible in the series of IPCC assessment reports? Based on those observations, several studies have analyzed the credibility of models projected changes of temperature, CO2, and sea level. As the core component of the hydrological cycle, precipitation is most important for agricultural production, social economy, natural ecology, and human life. However, little attention has been given to whether precipitation projections over the past more than ten years agree with subsequent observations to date.

       In this study, we retroactively investigate the skill of the IPCC TAR, AR4, and AR5 models for near-term precipitation projections over global land under 13 emissions scenarios by comparing them with the CRU dataset during 2002−2020. Results show that models show robust skills in projecting the subsequent climatological changes in global mean land precipitation from several to ten years ahead. Relative to global scale land, the models are less skillful in projecting the subsequent changes in precipitation at regional scale, although they exhibit some skills in northern mid- to high-latitudes, which is likely to be at least partly explained by the lower signal-to-noise ratio. Besides the climatological changes, we also analyze the projection skills of IPCC models for the precipitation trends both at global and regional scales. Since the signal-to-noise ratio for the trends is much lower than that for the climatological mean changes, especially on relatively short (multiannual to decadal) time scales and small spatial scales, the multimodel medians show much lower skills in projecting the precipitation trends both at global and regional scales compared to the climatological changes.

  【关键图表】

  【引用格式】       

  Hu, D., Tian, Z., Lang, X., & Jiang, D. (2023). Limited skill of projected land precipitation by IPCC models during 2002−2020. Journal of Geophysical Research: Atmospheres, 128, e2022JD037851. https://doi.org/10.1029/2022JD037851.