The nature of mean sea level variation over the global coastal ocean is considered based on 219 historical tide gauge records and three barotropic ocean circulation models forced by reanalysis surface air pressure and wind stress. The consistency of the models and their ability to reproduce the data are considered on nonseasonal timescales (seasonal cycles and linear trends removed) from bimonthly to multidecadal over 1900–2010. Models consistently simulate stronger sea level variability at higher latitude, higher frequency, between winters, and over broad shallow shelves and semi-enclosed marginal seas; standard deviations in modeled monthly sea level grow from 1–2 cm on average at low latitude (0°–30°) to 5–10 cm at high latitude (60°–90°), with larger values simulated over some shelf areas (e.g., North Sea). Models are more consistent over narrow shelf regions adjacent to deep basins and less consistent along the broad shallow continental shelf. On monthly timescales, discrepancies between models arise mostly from differences in model configuration (e.g., fine vs. coarse horizontal resolution), whereas model configuration and surface forcing (i.e., choice of atmospheric reanalysis) contribute comparably to model differences on annual timescales. Model solutions become more uncertain at earlier times (e.g., prior to 1950). The models show more skill explaining variance in tide gauge data at higher latitude, higher frequency, between winters, and over broad shallow shelves and within semi-enclosed marginal seas; at middle and high latitudes (poleward of 45°), model sea level solutions on average explain 30–50% of the monthly variance and 35–70% of the variance from one winter to the next in the tide gauge data records. Statistically significant relationships between the model solutions and observational data persist on long decadal periods. The relative skill of individual models is sensitive to region and timescale, such that no one model considered here consistently performs better than the others in all cases. Results suggest that barotropic models are useful for reducing noise in tide gauge records for studies of sea level rise and motivate additional model comparison studies in the context of sea level extremes.

中文翻译：

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正压模型从沿海潮位数据模拟历史平均海平面变化的能力

全球沿海海洋平均海平面变化的性质是根据​​ 219 条历史潮位计记录和由再分析表面气压和风应力强迫的三个正压海洋环流模型来考虑的。模型的一致性及其再现数据的能力在 1900 年至 2010 年期间从双月到数十年的非季节性时间尺度（季节性周期和线性趋势已去除）被考虑在内。模型始终如一地模拟更高纬度、更高频率、冬季之间以及宽阔的浅陆架和半封闭边缘海上的更强的海平面变化；模拟的每月海平面的标准偏差从低纬度（0°–30°）的平均 1–2 厘米增加到高纬度（60°–90°）的 5–10 厘米，在某些陆架区域模拟的值更大（例如，北海）。模型在与深盆相邻的狭窄大陆架区域更一致，而在宽阔的浅大陆架上则不太一致。在每月的时间尺度上，模式之间的差异主要来自模式配置的差异（例如，精细与粗糙的水平分辨率），而模式配置和表面强迫（即大气再分析的选择）对年度时间尺度上的模式差异的贡献相当。模型解决方案在早期（例如，1950 年之前）变得更加不确定。这些模型显示出更多的技巧来解释更高纬度、更高频率、冬季之间以及宽阔的浅陆架和半封闭边缘海内的潮汐测量数据的差异；在中高纬度（极地 45°），模型海平面解平均解释了潮位计数据记录中 30-50% 的月方差和 35-70% 的从一个冬天到下一个冬天的方差。模型解与观测数据之间的统计显着关系在很长的十年内持续存在。单个模型的相对技能对区域和时间尺度很敏感，因此这里考虑的任何一个模型都不会在所有情况下始终比其他模型表现得更好。结果表明，正压模型可用于减少潮汐测量记录中的噪声，以研究海平面上升，并在海平面极端情况下激发额外的模型比较研究。模型解与观测数据之间的统计显着关系在很长的十年内持续存在。单个模型的相对技能对区域和时间尺度很敏感，因此这里考虑的任何一个模型在所有情况下都不会始终比其他模型表现得更好。结果表明，正压模型可用于减少潮汐测量记录中的噪声以研究海平面上升，并在海平面极端情况下激发额外的模型比较研究。模型解与观测数据之间的统计显着关系在很长的十年内持续存在。单个模型的相对技能对区域和时间尺度很敏感，因此这里考虑的任何一个模型都不会在所有情况下始终比其他模型表现得更好。结果表明，正压模型可用于减少潮汐测量记录中的噪声，以研究海平面上升，并在海平面极端情况下激发额外的模型比较研究。