Recently, several global temperature series have been updated using new data sets, new methods, and importantly, assessments of their uncertainties. This enables us to produce a timely estimate of the annual global mean temperature with a smaller combined estimate of uncertainty. We describe the hierarchical model we propose, and a Bayesian scheme for fitting the model, allowing for dependence between the data sets, which all use some of the same observations. The discrepancy between individual data series and the combined estimate illustrates potential sources of deviation between them. In addition, we test the sensitivity of the results to each of the series, using a leave-one-out approach. This is a way of combining all the data sets in a way that improves on the straight or precision weighted ensemble mean, thus providing a more authoritative global temperature series with corresponding standard errors, which are smaller than that of individual products. Using the combined estimate of the global temperature series, we estimate that the global temperature has increased 1.2°C with a standard error of 0.03°C over the 1880–1900 average. By taking into account the uncertainties of the estimates rather than just comparing the estimates, we find that the probability that 2020 was the warmest year on record is 0.44, while the years 2015–2020 are virtually certain to have been the six warmest years in recorded history. We show that our estimate performs similarly to the reanalysis product ERA5, and that the satellite record from University of Alabama does not agree very well neither with ERA5 nor with our product.

中文翻译：

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全球温度的综合估计

最近，已经使用新的数据集、新方法以及重要的是对其不确定性的评估更新了几个全球温度序列。这使我们能够以较小的不确定性组合估计值对年全球平均温度进行及时估计。我们描述了我们提出的分层模型，以及用于拟合模型的贝叶斯方案，允许数据集之间存在依赖性，这些数据集都使用一些相同的观察结果。单个数据系列与综合估计之间的差异说明了它们之间潜在的偏差来源。此外，我们使用留一法测试结果对每个系列的敏感性。这是一种组合所有数据集的方法，以改进直接或精确加权集成平均值，从而提供更权威的全球温度系列，其对应的标准误差小于单个产品的标准误差。使用全球温度序列的综合估计，我们估计全球温度比 1880-1900 年的平均值增加了 1.2°C，标准误差为 0.03°C。通过考虑估计的不确定性而不是仅仅比较估计，我们发现 2020 年是有记录以来最热年份的概率为 0.44，而 2015-2020 年几乎可以肯定是有记录以来最热的六个年份历史。我们表明，我们的估计与再分析产品 ERA5 的表现相似，阿拉巴马大学的卫星记录与 ERA5 和我们的产品都不太一致。