Error variance-covariance matrix of global mean sea level estimated from satellite altimetry (TOPEX, Jason 1, Jason 2, Jason 3)

Satellite altimetry missions now provide more than 25 years of accurate, continuous and quasi-global measurements of sea level along the reference ground track of TOPEX-Poseidon. These measurements are used by different groups to build the Global Mean Sea Level (GMSL) record, an essential climate change indicator. Estimating a realistic uncertainty of the GMSL record is of crucial importance for climate studies such as estimating precisely the current rate and acceleration of sea level, analyzing the closure of the sea level budget, understanding the causes for sea level rise, detecting and attributing the response of sea level to anthropogenic activity, or estimating the Earth energy imbalance. Ablain et al. (2015) estimated the uncertainty of the GMSL trend over the period 1993-2014 by thoroughly analyzing the error budget of the satellite altimeters and showed that it amounts to 0.5 mm.yr-1 (90% confidence level). Here, we extend Ablain et al. (2015) analysis by providing a comprehensive description of the uncertainties in the satellite GMSL record. We analyse 25 years of satellite altimetry data and estimate for the first time the error variance-covariance matrix for the GMSL record with a time resolution of 10 days. Three types of errors that can affect satellite altimetry measurements are modelled (drifts, biases, noise) and combined together to derive a realistic estimate of the GMSL error variance-covariance matrix. From the error variance-covariance matrix, the uncertainty on any metrics related to GMSL can be derived including the 90% confidence envelop of the GMSL record on a 10-day basis, the GMSL trend and acceleration uncertainties over any time periods of 2 years and longer in between October 1992 and December 2017. Over 1993-2017 we find a GMSL trend of 3.35+-0.4 mm.yr-1 (90% CL) and a GMSL acceleration of 0.12 +-0.07 mm.yr-2 (90% CL) in agreement (within error bars) with previous studies. The full GMSL error variance-covariance matrix is freely available here.

卫星测高任务迄今已积累了超过25年的精准、连续且准全球尺度的海平面观测数据，观测沿TOPEX-Poseidon参考地面轨迹展开。不同研究团队利用此类观测数据构建了全球平均海平面（Global Mean Sea Level，GMSL）序列，该序列是关键的气候变化指标。精准估算GMSL序列的合理不确定性，对诸多气候研究具有关键意义——包括精确估算当前海平面变化速率与加速度、分析海平面收支闭合情况、厘清海平面上升的成因、探测并归因海平面对人为活动的响应，以及估算地球能量失衡状况。Ablain等人（2015）通过全面分析卫星高度计的误差预算，估算了1993-2014年期间GMSL趋势的不确定性，结果显示其不确定性为0.5毫米·年⁻¹（90%置信水平）。本研究拓展了Ablain等人（2015）的分析工作，全面阐述了卫星观测GMSL序列中的不确定性来源。我们分析了25年的卫星测高数据，并首次估算了时间分辨率为10天的GMSL序列误差方差-协方差矩阵。研究对影响卫星测高观测的三类误差（漂移、偏差、噪声）进行建模，并将三者结合，以得到合理的GMSL误差方差-协方差矩阵估算结果。借助该误差方差-协方差矩阵，可推导出与GMSL相关的任意指标的不确定性，包括10天分辨率下GMSL序列的90%置信包络线、1992年10月至2017年12月期间任意2年及以上时段的GMSL趋势与加速度不确定性。在1993-2017年时段内，我们得到的GMSL趋势为3.35±0.4毫米·年⁻¹（90%置信水平），GMSL加速度为0.12±0.07毫米·年⁻²（90%置信水平），该结果与既往研究在误差范围内一致。完整的GMSL误差方差-协方差矩阵可在此处免费获取。