Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG (GAMIL)
Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG (GAMIL)
复制标题
利用 IAP LASG (GAMIL) 网格点大气模型预测亚洲-澳大利亚季风年际变化
DOI：
10.1007/s00376-008-0387-8
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发表时间：
2008-05
期刊：
影响因子：
--
通讯作者：
吴志伟
中科院分区：
文献类型：
--
作者：
李建平;吴志伟
亚澳季风（A-AM）降水的季节性预测是气候预测中最重要和最具挑战性的任务之一。本文对IAP LASG的网格大气模式（GLAMIL）在回顾性预报A-AM年际变化（IAV）方面的性能进行了评价，并确定了GLAMIL在多大程度上能够捕捉到1979-2003年A-AM降水IAV的两个主要观测模态。第一种模式与厄尔尼诺3.4区域的变暖（变冷）的转折有关，而第二种模式导致变暖/变冷约一年，标志着ENSO的异常条件。我们表明，季节性降水异常的GAMIL一个月的领先预测主要是能够捕捉到IAV的两个观测到的领先模式的主要特征，第一种模式比第二种更好地预测。它也很好地描述了第一模态与ENSO的关系。另一方面，GAMIL在捕捉第二模态与ENSO之间的关系方面存在缺陷。我们得出结论：（1）成功地再现厄尔尼诺激发的季风-海洋相互作用和厄尔尼诺强迫可能是利用GAMIL对A-AM降水IAV进行季节性预报的关键：（2）不仅在Niño3.4区域，而且在亚洲和印度洋-太平洋连接区，都需要进一步努力改进模拟;（3）选择一层系统可以提高A-AM降水IAV的最终预报。这些结果为改进GAMIL及其季节预报技术提供了参考。
Seasonal prediction of Asian-Australian monsoon (A-AM) precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG (GAMIL) on retrospective prediction of the A-AM interannual variation (IAV), and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV for the period 1979–2003. The first mode is associated with the turnabout of warming (cooling) in the Niño 3.4 region, whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO.We show that the GAMIL one-month lead prediction of the seasonal precipitation anomalies is primarily able to capture major features of the two observed leading modes of the IAV, with the first mode better predicted than the second. It also depicts the relationship between the first mode and ENSO rather well. On the other hand, the GAMIL has deficiencies in capturing the relationship between the second mode and ENSO. We conclude: (1) successful reproduction of the El Niño-excited monsoon-ocean interaction and El Niño forcing may be critical for the seasonal prediction of the A-AM rainfall IAV with the GAMIL; (2) more efforts are needed to improve the simulation not only in the Niño 3.4 region but also in the joining area of Asia and the Indian-Pacific Ocean; (3) the selection of a one-tier system may improve the ultimate prediction of the A-AM rainfall IAV. These results offer some references for improvement of the GAMIL and associated seasonal prediction skill.
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影响因子：
56.9
作者：
Lennart Bengtsson;U. Schlese;E. Roeckner;Mojib Latif;T. Barnett;Nicholas E. Graham
通讯作者：
Lennart Bengtsson;U. Schlese;E. Roeckner;Mojib Latif;T. Barnett;Nicholas E. Graham
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通讯作者：
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作者：
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通讯作者：
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影响因子：
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作者：
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