Abstract. We present an analysis of atmospheric transport impact on estimating CO₂ fluxes using two atmospheric inversion systems (CarboScope Regional (CSR) and LUMIA) over Europe for 2018. The main focus of this study is to quantify the dominant drivers of spread amid CO₂ estimates derived from atmospheric tracer inversions. The Lagrangian transport models STILT and FLEXPART were used to assess the impact of mesoscale transport. The impact of lateral boundary conditions for CO₂ was assessed by applying the global transport models TM3 and TM5. CO₂ estimates calculated with an ensemble of eight inversions differing in the regional and global transport models, as well as the inversion systems show a relatively large spread for the annual domain wide flux ranging between -0.72 and 0.20 PgC yr^-1 with a mean estimate of -0.29 PgC. The largest discrepancies resulted from varying the mesoscale transport model, which amounted to a difference of 0.51 (PgC yr^-1), in comparison with 0.23 and 0.10 (PgC yr^-1) that resulted from the far-field contributions and the inversion systems, respectively. Additionally, varying the mesoscale transport caused large discrepancies in spatial and temporal patterns, while changing the lateral boundary conditions lead to more homogeneous spatial and temporal impact. We further investigated the origin of the discrepancies between transport models. The meteorological forcing parameters (forecasts versus reanalysis obtained from ECMWF data products) used to drive the transport models are responsible for a small part of the differences in CO₂ estimates, but the largest impact seems to come from the models themselves. Although a good convergence in the differences between the inversion systems was achieved by applying a strict protocol of using identical priors, and atmospheric datasets, there was a non-negligible impact arising from applying a different inversion system. Specifically, the choice of prior error structure accounted for a large part of system-to-system differences.

中文翻译：

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大气传输对由大气示踪剂反演得出的 CO2 通量估计的影响

摘要。我们分析了 2018 年欧洲使用两个大气反演系统（CarboScope 区域 (CSR) 和 LUMIA）估算 CO ₂通量的大气传输影响。本研究的主要重点是量化 CO ₂估算中传播的主要驱动因素来自大气示踪剂反演。拉格朗日传输模型 STILT 和 FLEXPART 用于评估中尺度传输的影响。通过应用全球传输模型 TM3 和 TM5 评估了横向边界条件对 CO _{2的影响。}二氧化碳₂使用在区域和全球传输模型中不同的八个反演的集合计算得出的估计值，以及反演系统显示，在 -0.72 和 0.20 PgC yr ^-1之间的年度域宽通量分布相对较大，平均估计值为 - 0.29 PgC。最大的差异来自改变中尺度传输模型，与 0.23 和 0.10 (PgC yr -1 ) 相比，^差异为 0.51 (PgC yr ^{-1 )}) 分别由远场贡献和反演系统产生。此外，改变中尺度输运会导致空间和时间模式的巨大差异，而改变横向边界条件会导致更均匀的空间和时间影响。我们进一步调查了运输模型之间差异的根源。用于驱动传输模型的气象强迫参数（预测与从 ECMWF 数据产品获得的再分析）是造成 CO _{2差异的一小部分原因}估计，但最大的影响似乎来自模型本身。尽管通过应用使用相同先验和大气数据集的严格协议实现了反演系统之间差异的良好收敛，但应用不同的反演系统产生了不可忽视的影响。具体来说，先验错误结构的选择占系统间差异的很大一部分。