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Alexandre Ganachaud

introduces a residual error into the calculation. This error is estimated here in the North Atlantic. Section 2 presents the formalism of the problem and basic notations; section 3 gives estimates of the effect of oceanic variability on one-time sections; section 4 quantifies the various measurement noise sources; section 5 provides values for the a priori size of the solution (reference velocities); while section 6 analyzes the conservation of silicate, followed by a general discussion and

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Yanzhou Wei, Sarah T. Gille, Matthew R. Mazloff, Veronica Tamsitt, Sebastiaan Swart, Dake Chen, and Louise Newman

et al. (2018) , who sought to identify the spatial scale over which heat fluxes decorrelate. As the high-frequency heat flux variability is less well constrained by the large-scale energy budget of the Earth system, it is therefore more challenging to determine than low-frequency Q net . In addition, because the mooring observing system is expensive to build and often relies on short-term funding, it is unlikely to be maintained for decades. Therefore, the mooring observing system for high

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Xianglei Huang, Norman G. Loeb, and Huiwen Chuang

through April 2007 . J. Atmos. Oceanic Technol. , 28 , 3 – 21 . Wielicki, B. A. , Barkstrom B. R. , Harrison E. F. , Lee R. B. , Smith G. L. , and Cooper J. E. , 1996 : Clouds and the Earth’s Radiant Energy System (CERES): An earth observing system experiment . Bull. Amer. Meteor. Soc. , 77 , 853 – 868 . Wong, T. , Wielicki B. A. , Lee R. B. , Smith G. L. , Bush K. A. , and Willis J. K. , 2006 : Reexamination of the observed decadal variability of the earth radiation

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Hyejin Ok, Yign Noh, and Yeonju Choi

.1 . 10.1175/2008JPO3984.1 Tomita , T. , S.-P. Xie , and M. Nonaka , 2002 : Estimates of surface and subsurface forcing for decadal sea surface temperature variability in the mid-latitude North Pacific . J. Meteor. Soc. Japan , 80 , 1289 – 1300 , doi: 10.2151/jmsj.80.1289 . 10.2151/jmsj.80.1289 Toyoda , T. , and Coauthors , 2017 : Intercomparison and validation of the mixed layer depth fields of global ocean syntheses . Climate Dyn. , 49 , 753 – 773 , doi: 10.1007/s00382

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Don P. Chambers and Josh K. Willis

1. Introduction Other than tides, there are three main drivers of ocean bottom pressure (OBP) variability. Locally, the largest arises from changes in wind stress curl and circulation, which force internal mass redistribution. These OBP changes are typically correlated over several thousand kilometers, although even larger-scale exchanges between basins have been simulated in models ( Stepanov and Hughes 2006 ). There are also two smaller components of OBP variability that are correlated over

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Pavel Sakov and Peter R. Oke

1. Introduction The use of models and data assimilation theory to aid in the design of atmospheric and oceanic observing systems has gained momentum over recent decades (e.g., Kållberg 1984 ; McIntosh 1987 ; Barth and Wunsch 1990 ; Kuo et al. 1998 ; Hackert et al. 1998 ; Bishop et al. 2001 ; Hirschi et al. 2003 ; Schiller et al. 2004 ; Oke and Schiller 2007b ). The applications described in this study are motivated by the proposal of the Climate Variability and Predictability

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Femke C. Vossepoel, Richard W. Reynolds, and Laury Miller

–1088. ——, and ——, 1998b: An OGCM study for the TOGA decade. Part II: Barrier layer formation and variability. J. Phys. Oceanogr., 28, 1089–1106. 10.1175/1520-0485(1998)028<1089:AOSFTT>2.0.CO;2 Webster, P. J., and R. Lukas, 1992: TOGA COARE: The Coupled Ocean–Atmosphere Response Experiment. Bull. Amer. Meteor. Soc., 73, 1377–1416. 10.1175/1520-0477(1992)073<1377:TCTCOR>2.0.CO;2 Woodgate, R. A., 1997: Can we assimilate temperature data alone into a full equation of state model? Ocean Modelling

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Tara Howatt, Stephanie Waterman, and Tetjana Ross

parameterization (FP) method infers turbulent dissipation, ϵ FP , based on theory describing the downscale spectral energy cascade between internal wave scales [typically O (10–100 m)] and turbulent microscales where dissipation and mixing occur [see Polzin et al. (2014) for a detailed review]. Over the past few decades, many studies have demonstrated the utility of FP in mapping the space and time variability of internal wave-driven dissipation and mixing rates throughout the world’s oceans (e.g., D

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Sergey K. Gulev

Release 1 has for the earlier decades. At the same time, in the northwest Atlantic the drop of the number of reports is not so pronounced, and for some boxes there is even a tendency of increasing number of samples. For the comparison with instrumental observations, we used the data collected by the research vessels (R/Vs) in the northwest Atlantic within a 10-yr period 1981–91 under the Energetically Active Zones of the Ocean and Climate Variability program (SECTIONS) ( Gulev 1994 ). Figure 2a

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Cheng-Zhi Zou and Wenhui Wang

trends from the same satellite observations. The most recent analysis of different datasets shows a global ocean-mean T 2 trend of 0.080 ± 0.103 K decade −1 for UAH, 0.135 ± 0.113 K decade −1 for RSS, and 0.200 ± 0.067 K decade −1 for STAR for the 1987–2006 period ( Z09 ). These differences exceed the widely accepted accuracy requirement of 0.01–0.02 K decade −1 for the trends. Accurate determination of the MSU–AMSU temperature trends is essential for resolving the global warming debate ( Karl

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