Indian Ocean Dipole (IOD), a major climate variability in the tropics which drives the abiotic stress associated with heavy rainfalls and severe droughts, is not much understood in terms of its role in the carbon cycle, while El Niño‐Southern Oscillation (ENSO)‐related terrestrial carbon cycle variation has been intensively studied. Here, we investigate IOD's impact on land photosynthesis over the Indian ocean rim countries during austral spring using satellite‐based gross primary productivity (GPP) and Earth System Model simulations produced in the Coupled Model Intercomparison Project Phase 6 (CMIP6). IOD independently affects GPP with significant positive partial correlation coefficients () over most of Africa and India, and negative over southern China, Indo‐China peninsula, maritime continent, and Australia, mostly driven by precipitation variations; this obviously differs from the widespread significant negative pattern induced by ENSO. The recent extremely positive IOD in 2019 caused the canonical IOD‐affected GPP patterns, however, with its extreme impacts. Furthermore, though large inter‐model spreads exist, the CMIP6 multimodel median can basically capture the main characteristics of IOD‐affected precipitation and GPP patterns. Importantly, IOD is predicted to occur more frequently in future warming scenarios. Model future projections suggest that it will exert larger impacts on GPP variations over central and eastern Africa, Sumatra, western and southeastern Australia with stronger and enhanced explained variance, but less impacts over southern Africa, east India, Indo‐China peninsula, and northeastern Australia. Therefore, besides ENSO, understanding the IOD impacts can provide us new insights into regional and global carbon cycle interannual variability.

中文翻译：

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印度洋偶极子对陆地光合作用的调节：基于卫星的观测和CMIP6未来预测

印度洋偶极子（IOD）是热带地区的主要气候变率，它引发了与强降雨和严重干旱有关的非生物胁迫，但就其在碳循环中的作用而言，人们对其了解甚少，而厄尔尼诺-南方涛动（ENSO）与陆地有关的碳循环变化已得到深入研究。在这里，我们使用耦合模型比对项目第6阶段（CMIP6）产生的基于卫星的总初级生产力（GPP）和地球系统模型模拟，研究了IOD在南方春季期间对印度洋边缘国家陆地光合作用的影响。在大多数非洲和印度，IOD会以显着的正偏相关系数（）独立影响GPP，而对GPP则有负面影响在华南，印度支那半岛，海洋大陆和澳大利亚，主要受降水变化的影响；这显然不同于ENSO引起的普遍的显着负面模式。然而，2019年最近的IOD极度乐观，导致受IOD规范化影响的GPP模式产生了极端影响。此外，尽管存在较大的模型间差异，但CMIP6多模型中值基本上可以捕获受IOD影响的降水和GPP模式的主要特征。重要的是，预计在未来的变暖情况下，IOD会更频繁地发生。未来的模型预测表明，它将对中部和东部非洲，苏门答腊，澳大利亚西部和东南部的GPP变动产生更大的影响，并且影响更大并增强了解释方差，但对南部非洲，印度东部，印度支那半岛和澳大利亚东北部的影响较小。因此，除了ENSO，了解IOD的影响可以为我们提供有关区域和全球碳循环年际变化的新见解。