Long‐range low‐frequency CW propagation in the deep ocean: Antigua‐Newfoundland

1974 ◽  
Vol 56 (1) ◽  
pp. 58-69 ◽  
Author(s):  
A. N. Guthrie ◽  
R. M. Fitzgerald ◽  
D. A. Nutile ◽  
J. D. Shaffer
Keyword(s):  
Long Range ◽  
Low Frequency ◽  
Deep Ocean

Autosub Long Range 6000: A Multiple-Month Endurance AUV for Deep-Ocean Monitoring and Survey

2021 ◽  
pp. 1-13
Author(s):  
Daniel Roper ◽  
Catherine A. Harris ◽  
Georgios Salavasidis ◽  
Miles Pebody ◽  
Robert Templeton ◽  
...  
Keyword(s):  
Long Range ◽  
Deep Ocean ◽  
Ocean Monitoring

Quantifying the Predictive Skill in Long-Range Forecasting. Part II: Model Error in Coarse-Grained Markov Models with Application to Ocean-Circulation Regimes

2012 ◽  
Vol 25 (6) ◽  
pp. 1814-1826 ◽  
Author(s):  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Long Range ◽  
Ocean Circulation ◽  
Climate Models ◽  
Markov Models ◽  
Low Frequency ◽  
Model Error ◽  
Ocean Model ◽  
Coarse Grained ◽  
Predictive Skill ◽  
Relaxation To Equilibrium

Abstract An information-theoretic framework is developed to assess the predictive skill and model error in imperfect climate models for long-range forecasting. Here, of key importance is a climate equilibrium consistency test for detecting false predictive skill, as well as an analogous criterion describing model error during relaxation to equilibrium. Climate equilibrium consistency enforces the requirement that long-range forecasting models should reproduce the climatology of prediction observables with high fidelity. If a model meets both climate consistency and the analogous criterion describing model error during relaxation to equilibrium, then relative entropy can be used as an unbiased superensemble measure of the model’s skill in long-range coarse-grained forecasts. As an application, the authors investigate the error in modeling regime transitions in a 1.5-layer ocean model as a Markov process and identify models that are strongly persistent but their predictive skill is false. The general techniques developed here are also useful for estimating predictive skill with model error for Markov models of low-frequency atmospheric regimes.

Low-frequency vibrational spectroscopy: a new tool for revealing crystalline magnetic structures in iron phosphate crystals

2021 ◽  
Vol 23 (39) ◽  
pp. 22241-22245
Author(s):  
Zihui Song ◽  
Xudong Liu ◽  
Anish Ochani ◽  
Suling Shen ◽  
Qiqi Li ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Long Range ◽  
Vibrational Spectroscopy ◽  
Strong Dependence ◽  
Low Frequency ◽  
Lithium Ion ◽  
Iron Phosphate ◽  
Promising Material ◽  
Vibrational Dynamics ◽  
Magnetic Structures

In this report, the strong-dependence of low-frequency (terahertz) vibrational dynamics on weak and long-range forces in crystals is leveraged to determine the bulk magnetic configuration of iron phosphate – a promising material for cathodes in lithium ion batteries.

scholarly journals Climate Process Team on Internal Wave–Driven Ocean Mixing

2017 ◽  
Vol 98 (11) ◽  
pp. 2429-2454 ◽  
Author(s):  
Jennifer A. MacKinnon ◽  
Zhongxiang Zhao ◽  
Caitlin B. Whalen ◽  
Amy F. Waterhouse ◽  
David S. Trossman ◽  
...  
Keyword(s):  
Internal Wave ◽  
Turbulent Mixing ◽  
Low Frequency ◽  
Internal Tide ◽  
Deep Ocean ◽  
Global Ocean ◽  
Primary Role ◽  
Inverse Models ◽  
Lee Waves ◽  
Mixing Rates

Abstract Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.

Propagation of Low‐Frequency CW Sound Signals in the Deep Ocean

1965 ◽  
Vol 38 (6) ◽  
pp. 1060-1061 ◽  
Author(s):  
Albert N. Guthrie ◽  
John D. Shaffer
Keyword(s):  
Low Frequency ◽  
Deep Ocean

scholarly journals Low-frequency discrete breathers in long-range systems without on-site potential

2018 ◽  
Vol 97 (6) ◽  
Author(s):  
Yoshiyuki Y. Yamaguchi ◽  
Yusuke Doi
Keyword(s):  
Long Range ◽  
Low Frequency ◽  
Discrete Breathers

scholarly journals Climate models can correctly simulate the continuum of global-average temperature variability

2019 ◽  
Vol 116 (18) ◽  
pp. 8728-8733 ◽  
Author(s):  
Feng Zhu ◽  
Julien Emile-Geay ◽  
Nicholas P. McKay ◽  
Gregory J. Hakim ◽  
Deborah Khider ◽  
...  
Keyword(s):  
Climate Models ◽  
Initial Conditions ◽  
Low Frequency ◽  
Deep Ocean ◽  
Critical Element ◽  
Average Temperature ◽  
Global Mean Temperature ◽  
Low Frequency Variability ◽  
Climate Forcings ◽  
Global Mean

Climate records exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It is unclear whether climate models are capable of simulating these fluctuations, which draws into question their ability to simulate such variability in the coming decades and centuries. Using the latest simulations and data syntheses, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multimillennial. Our results confirm the existence of a scaling break between orbital and annual peaks, occurring around millennial periodicities. That both simple and comprehensive ocean–atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. This result implies that Holocene low-frequency variability is partly a consequence of the climate system’s integrated memory of orbital forcing. We conclude that climate models appear to contain the essential physics to correctly simulate the spectral continuum of global-mean temperature; however, regional discrepancies remain unresolved. A critical element of successfully simulating suborbital climate variability involves, we hypothesize, initial conditions of the deep ocean state that are consistent with observations of the recent past.

Sign in / Sign up

Export Citation Format

Share Document