Comparison of Full and Empirical Bayes Approaches for Inferring Sea-Level Changes From Tide-Gauge Data
Comparison of Full and Empirical Bayes Approaches for Inferring Sea-Level Changes From Tide-Gauge Data
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从验潮数据推断海平面变化的完整贝叶斯方法和经验贝叶斯方法的比较
DOI：
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
M. Tingley
中科院分区：
文献类型：
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作者：
C. Piecuch;P. Huybers;M. Tingley
潮汐测量数据是海洋最长的仪器记录之一，但这些数据可能是嘈杂的，有间隙的和有偏见的。以往的研究使用经验贝叶斯方法来推断海平面场验潮记录，但没有考虑到模型参数估计的不确定性。在这里，我们比较一个完全贝叶斯方法，占模型参数的不确定性，并证明经验贝叶斯方法低估了海平面的不确定性推断验潮记录。我们使用一个合成的验潮数据集来评估经验和全贝叶斯方法的技能。海平面场的双贝叶斯可信区间比全贝叶斯可信区间窄且不可靠：双贝叶斯95%可信区间比全贝叶斯95%可信区间平均窄42.8%;全贝叶斯95%可信区间捕获95.6%的真实字段值，而双贝叶斯95%可信区间仅捕获77.1%的真实值，表明参数的不确定性对海平面场的不确定性有重要影响。最有影响力的是数据偏差的模型参数的不确定性（即，验潮基准）;假设数据偏差参数随海平面过程沿着变化，但保持所有其他参数不变，则95%可信区间捕获真实合成场值的92.8%。结果表明，全贝叶斯方法是最好的重建海平面估计的情况下，完整和准确的估计不确定性是必要的。
Tide-gauge data are one of the longest instrumental records of the ocean, but these data can be noisy, gappy, and biased. Previous studies have used empirical Bayes methods to infer the sea-level field from tide-gauge records but have not accounted for uncertainty in the estimation of model parameters. Here we compare to a fully Bayesian method that accounts for uncertainty in model parameters, and demonstrate that empirical Bayes methods underestimate the uncertainty in sea level inferred from tide-gauge records. We use a synthetic tide-gauge data set to assess the skill of the empirical and full Bayes methods. The empirical-Bayes credible intervals on the sea-level field are narrower and less reliable than the full-Bayes credible intervals: the empirical-Bayes 95% credible intervals are 42.8% narrower on average than are the full-Bayes 95% credible intervals; full-Bayes 95% credible intervals capture 95.6% of the true field values, while the empirical-Bayes 95% credible intervals capture only 77.1% of the true values, showing that parameter uncertainty has an important influence on the uncertainty of the inferred sea-level field. Most influential are uncertainties in model parameters for data biases (i.e., tide-gauge datums); letting data-bias parameters vary along with the sea-level process, but holding all other parameters fixed, the 95% credible intervals capture 92.8% of the true synthetic-field values. Results indicate that full Bayes methods are preferable for reconstructing sea-level estimates in cases where complete and accurate estimates of uncertainty are warranted.
影响因子：
5.2
作者：
Higginson S
通讯作者：
Higginson S
影响因子：
3
作者：
Miller,ME;Hui,SL;Tierney,WM;McDonald,CJ
通讯作者：
McDonald,CJ
影响因子：
2.8
作者：
Bos, M. S.;Williams, S. D. P.;Bastos, L.
通讯作者：
Bastos, L.