Abstract. The Arabian Sea (AS) was confirmed to be a net emitter of CO₂ to the atmosphere during the international Joint Global Ocean Flux Study program of the 1990s, but since then little in situ data has been collected, leaving data-based methods to calculate air-sea exchange with fewer data and potentially out-of-date. Additionally, coarse-resolution models underestimate CO₂ flux compared to other approaches. To address these shortcomings, we employ a high-resolution (1/24°) regional model to quantify the seasonal cycle of air-sea CO₂ exchange in the AS by focusing on two main contributing factors, pCO₂ and winds. We compare the model to available in situ pCO₂ data and find that uncertainties in dissolved inorganic carbon (DIC) and total alkalinity (TA) lead to the greatest discrepancies. Nevertheless, the model is more successful than neural network approaches in replicating the large variability in summertime pCO₂ because it captures the AS's intense monsoon dynamics. In the seasonal pCO₂ cycle, temperature plays the major role in determining surface pCO₂, except where DIC delivery is important in summer upwelling areas. Since seasonal temperature forcing is relatively uniform, pCO₂ differences between the AS's sub-regions are mostly caused by geographic DIC gradients. We find that primary productivity during both summer and winter monsoon blooms, but also generally, is insufficient to off-set the physical delivery of DIC to the surface, resulting in limited biological control of CO₂ release. The most intense air-sea CO₂ exchange occurs during the summer monsoon where outgassing rates reach ~6 molCm⁻² yr⁻¹ in the upwelling regions of Oman and Somalia, but the entire AS contributes CO₂ to the atmosphere. Despite a regional spring maximum of pCO₂ driven by surface heating, CO₂ exchange rates peak in summer due to winds, which account for ~90 % of the summer CO₂ flux variability versus 6 % for pCO₂ in a Reynolds decomposition. In comparison with other estimates, we find that the AS emits ~160 TgCyr⁻¹, slightly higher than previously reported. Altogether, there is 2x variability in annual flux magnitude across methodologies considered. Future attempts to reduce the variability in estimates will likely require more in situ carbon data. Since summer monsoon winds are critical in determining flux both directly and indirectly through temperature, DIC, TA, mixing, and primary production effects on pCO₂, studies looking to predict CO₂ emissions in the AS with ongoing climate change will need to correctly resolve their timing, strength, and upwelling dynamics.

中文翻译：

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评价阿拉伯海作为大气CO ₂的区域性来源：季节变化和驱动因素

摘要。在1990年代国际联合全球海洋通量研究计划中，阿拉伯海（AS）被确认为向大气中释放CO ₂的净排放者，但此后几乎没有收集到任何原位数据，仅剩下基于数据的方法来进行计算数据较少且可能已过时的海海交换。此外，与其他方法相比，粗分辨率模型低估了CO ₂通量。为了解决这些缺点，我们采用高分辨率（1/24°）区域模型，通过关注两个主要影响因素pCO ₂和风，来量化AS中空气-海洋CO ₂交换的季节性周期。我们将模型与可用的现场pCO ₂进行了比较数据，发现溶解性无机碳（DIC）和总碱度（TA）的不确定性导致最大的差异。尽管如此，该模型在复制夏季pCO ₂的较大变化方面比神经网络方法更为成功，因为它捕获了AS强烈的季风动态。在季节性pCO ₂循环中，温度在确定表面pCO ₂方面起主要作用，除非在夏季上升区重要的DIC输送。由于季节性温度强迫相对均匀，因此pCO ₂AS子区域之间的差异主要是由地理DIC梯度引起的。我们发现，夏季和冬季季风盛开期间的初级生产力，但通常也不足以抵消DIC向地面的物理传递，从而导致对CO ₂释放的生物控制受到限制。最强烈的海气CO ₂交换发生在夏季风，在阿曼和索马里的上升流区，除气率达到〜6 molCm ^-2  yr ^-1，但是整个AS向大气中贡献CO ₂。尽管通过表面加热驱动pCO ₂在局部区域处于春季最大值，但CO ₂夏季，由于风的影响，交换率达到峰值，约占夏季CO ₂通量变化的90％，而雷诺分解中pCO _2的变化为6％。与其他估计值相比，我们发现AS发射的〜TgCyr ^-1约为160 ，略高于以前的报告。总体而言，在所考虑的各种方法中，年通量大小存在2倍的差异。未来为减少估算的可变性而进行的尝试可能需要更多的原位碳数据。由于夏季季风对于直接或间接确定温度，DIC，TA，混合以及对pCO _2的主要生产影响至关重要，因此至关重要的研究旨在预测CO ₂ 随着气候变化而发生的AS排放将需要正确解决其时间，强度和上升动力。