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• W2076202396 abstract "We investigate spatial variations in the shape of the spectrum of sea level variability based on a homogeneously sampled 12 year gridded altimeter data set. We present a method of plotting spectral information as color, focusing on periods between 2 and 24 weeks, which shows that significant spatial variations in the spectral shape exist and contain useful dynamical information. Using the Bayesian Information Criterion, we determine that, typically, a fifth‐order autoregressive model is needed to capture the structure in the spectrum. Using this model, we show that statistical errors in fitted local trends range between less than 1 and more than 5 times of what would be calculated assuming “white” noise and that the time needed to detect a 1 mm/yr trend ranges between about 5 years and many decades. For global mean sea level, the statistical error reduces to 0.1 mm/yr over 12 years, with only 2 years needed to detect a 1 mm/yr trend. We find significant regional differences in trend from the global mean. The patterns of these regional differences are indicative of a sea level trend dominated by dynamical ocean processes over this period." @default.
• W2076202396 created "2016-06-24" @default.
• W2076202396 creator A5013421890 @default.
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• W2076202396 date "2010-10-01" @default.
• W2076202396 modified "2023-09-27" @default.
• W2076202396 title "The color of sea level: Importance of spatial variations in spectral shape for assessing the significance of trends" @default.
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• W2076202396 doi "https://doi.org/10.1029/2010jc006102" @default.
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