The Atmosphere and Ocean non-tidal De-aliasing Level-1B (AOD1B) product is widely used in precise orbit determination and satellite gravimetry to correct for transient effects of atmosphere–ocean mass variability that would otherwise alias into monthly mean global gravity fields. The most recent release is based on the global ERA5 reanalysis and ECMWF operational data together with simulations from the general ocean circulation model MPIOM consistently forced with fields from the corresponding atmospheric dataset. As background models are inevitably imperfect, residual errors will consequently propagate into the resulting geodetic products. Accounting for uncertainties of the background model data in a statistical sense, however, has been shown before to be a useful approach to mitigate the impact of residual errors leading to temporal aliasing artefacts. In light of the changes made in the new release RL07 of AOD1B, previous uncertainty assessments are deemed too pessimistic and thus need to be revisited. We here present an analysis of the residual errors in AOD1B RL07 based on ensemble statistics derived from different atmospheric reanalyses, including ERA5, MERRA2 and JRA55. For the oceans, we investigate the impact of both the forced and intrinsic variability through differences in MPIOM simulation experiments. The atmospheric and oceanic information is then combined to produce a new time-series of true errors, called AOe07, which is applicable in combination with AOD1B RL07. AOe07 is further complemented by a new spatial error variance–covariance matrix. Results from gravity field recovery simulation experiments for the planned Mass-Change and Geosciences International Constellation (MAGIC) based on GFZ’s EPOS software demonstrate improvements that can be expected from rigorously implementing the newly available stochastic information from AOD1B RL07 into the gravity field estimation process.

大气和海洋非潮汐去混叠 1B 级 (AOD1B) 产品广泛用于精确轨道确定和卫星重力测量，以纠正大气-海洋质量变化的瞬态影响，否则这些影响会混叠到月平均全球重力场中。最新版本基于全球 ERA5 再分析和 ECMWF 运行数据以及一般海洋环流模型 MPIOM 的模拟，该模型与相应大气数据集的场一致。由于背景模型不可避免地是不完美的，因此残余误差将传播到最终的大地测量产品中。然而，从统计意义上考虑背景模型数据的不确定性，之前已被证明是减轻导致时间混叠伪影的残余误差影响的有用方法。鉴于AOD1B新版本RL07中所做的更改，之前的不确定性评估被认为过于悲观，因此需要重新审视。我们在此根据不同大气再分析（包括 ERA5、MERRA2 和 JRA55）得出的集合统计数据，对 AOD1B RL07 中的残余误差进行分析。对于海洋，我们通过 MPIOM 模拟实验的差异研究了受迫变异性和内在变异性的影响。然后将大气和海洋信息组合起来，产生一个新的真实误差时间序列，称为 AOe07，它可与 AOD1B RL07 结合使用。新的空间误差方差-协方差矩阵进一步补充了 AOe07。基于 GFZ 的 EPOS 软件的计划中的质量变化和地球科学国际星座 (MAGIC) 的重力场恢复模拟实验的结果表明，通过严格地将 AOD1B RL07 中新提供的随机信息应用到重力场估计过程中，可以预期得到改进。