Seasonal mode-1 M2 internal tides from satellite altimetry

2021 ◽  
Author(s):  
Zhongxiang Zhao
Keyword(s):  
Seasonal Variations ◽  
Seasonal Variability ◽  
World Ocean ◽  
Internal Tide ◽  
Internal Tides ◽  
Altimeter Data ◽  
Model Errors ◽  
Tropical Zone ◽  
Phase Variations ◽  
World Ocean Atlas

AbstractThe seasonal variability of mode-1 M2 internal tides is investigated using 25 years of multi-satellite altimeter data from 1992–2017. Four seasonal internal tide models are constructed using seasonally-subsetted altimeter data and World Ocean Atlas seasonal climatologies. This work is made possible by a newly-developed mapping procedure that can significantly suppress model errors. Seasonal-mean and seasonally-variable internal tide models are derived from the four seasonal models. All the models are inter-compared and evaluated using independent CryoSat-2 data. The seasonal-mean model is overall the best model because averaging the four seasonal models further reduces model errors. The seasonally-variable models are better in the tropical zone, where large seasonal signals may overcome model errors. Each seasonal model works best in its own season and worst in its opposite season. These internal tide models reveal that mode-1 M2 internal tides are subject to significant seasonal variability and their seasonal variations are a function of location. Large seasonal variations dominantly occur in the tropical zone, where the World Ocean Atlas climatology shows strong seasonal variations in ocean stratification. Seasonal phase variations are obtained from the directionally-decomposed internal tide components. They are dominantly ±60° at the equator and up to ±120° in the central Arabian Sea. Incoherence caused by seasonal phase variations is usually <10%, but may be up to 40–50% in the tropical zone.

Seasonal variations of mode-1 M2 internal tides observed by satellite altimetry

2021 ◽  
Author(s):  
Zhongxiang Zhao
Keyword(s):  
Seasonal Variation ◽  
Seasonal Variations ◽  
Internal Tide ◽  
Spatial Filtering ◽  
Internal Tides ◽  
Mapping Technique ◽  
Phase Variable ◽  
Model Errors ◽  
Tropical Zone ◽  
Variable Amplitude

&lt;p&gt;The seasonal variations of M&lt;sub&gt;2&lt;/sub&gt; internal tides is investigated using 25 years of satellite altimetric sea surface height measurements from 1992--2017. The satellite data are divided into four seasonal subsets, from which four seasonal M&lt;sub&gt;2&lt;/sub&gt; internal tide models are constructed. This study employs a new mapping technique that combines along-track spatial filtering, harmonic analysis, plane wave analysis, and two-dimensional spatial filtering. The vector mean of the four seasonal models yields the seasonal-mean model, which is equivalent to the 25-year-coherent model constructed directly using all the data. The seasonal models have larger errors than the seasonal-mean model, because the seasonally-subsetted data sets are short. Two seasonally-variable models are derived: The first model is a step function of the four seasonal models (phase-variable, amplitude-variable); The second model is same as the first one but that the amplitude is from the seasonal-mean model (phase-variable, amplitude-invariable). All these models are evaluated using independent CryoSat-2 data. Each seasonal model reduces most variance in its own season and least variance in its opposite season. Based on globally-integrated variance reductions, the two seasonally-variable models reduce 13% and 23% more variance than the seasonal models, respectively. The seasonal-mean model can reduce 27% more variance, thanks to its small model errors. However, the seasonally-variable models are better than the seasonal-mean model in the tropical zone, where the seasonal signals are larger than model errors. The satellite results reveal that M&lt;sub&gt;2&lt;/sub&gt; internal tides are subject to seasonal variation in varying degrees and that the seasonal variation is a function of location. Large variations in amplitude and phase mainly occur in the tropical zone. The seasonal phase variations are mainly caused by the seasonal variations of ocean stratification and internal tide speed. Significant amplitude variations are usually associated with strong internal tides such as from the Luzon and Lombok Straits, and in the Amazon River plume, the western Pacific and the Arabian Sea. At higher latitudes such as the North Pacific and North Atlantic Oceans, the seasonal variations are weak but detectable. The seasonally-variable models can partly account for the seasonal variations of internal tides, in particular, in the tropical zone. &amp;#160;A major challenge is the large model errors, which will be further reduced with the accumulation of new altimeter missions and data (e.g., SWOT).&lt;/p&gt;

scholarly journals Satellite Investigation of Semidiurnal Internal Tides in the Sulu-Sulawesi Seas

2021 ◽  
Vol 13 (13) ◽  
pp. 2530
Author(s):  
Xiaoyu Zhao ◽  
Zhenhua Xu ◽  
Ming Feng ◽  
Qun Li ◽  
Peiwen Zhang ◽  
...  
Keyword(s):  
Interference Pattern ◽  
Energy Flux ◽  
Internal Tide ◽  
Tidal Energy ◽  
Internal Tides ◽  
Altimeter Data ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Sulu Sea ◽  
Tidal Energy Flux

The mode-1 semidiurnal internal tides that emanate from multiple sources in the Sulu-Sulawesi Seas are investigated using multi-satellite altimeter data from 1993–2020. A practical plane-wave analysis method is used to separately extract multiple coherent internal tides, with the nontidal noise in the internal tide field further removed by a two-dimensional (2-D) spatial band-pass filter. The complex radiation pathways and interference patterns of the internal tides are revealed, showing a spatial contrast between the Sulu Sea and the Sulawesi Sea. The mode-1 semidiurnal internal tides in the Sulawesi Sea are effectively generated from both the Sulu and Sangihe Island chains, forming a spatially inhomogeneous interference pattern in the deep basin. A cylindrical internal tidal wave pattern from the Sibutu passage is confirmed for the first time, which modulates the interference pattern. The interference field can be reproduced by a line source model. A weak reflected internal tidal beam off the Sulawesi slope is revealed. In contrast, the Sulu Island chain is the sole energetic internal tide source in the Sulu Sea, thus featuring a relatively consistent wave and energy flux field in the basin. These energetic semidiurnal internal tidal beams contribute to the frequent occurrence of internal solitary waves (ISWs) in the study area. On the basis of the 28-year consistent satellite measurements, the northward semidiurnal tidal energy flux from the Sulu Island chain is 0.46 GW, about 25% of the southward energy flux. For M2, the altimetric estimated energy fluxes from the Sulu Island chain are about 80% of those from numerical simulations. The total semidiurnal tidal energy flux from the Sulu and Sangihe Island chains into the Sulawesi Sea is about 2.7 GW.

Incoherent Nature of M2 Internal Tides at the Hawaiian Ridge

2011 ◽  
Vol 41 (11) ◽  
pp. 2021-2036 ◽  
Author(s):  
N. V. Zilberman ◽  
M. A. Merrifield ◽  
G. S. Carter ◽  
D. S. Luther ◽  
M. D. Levine ◽  
...  
Keyword(s):  
Energy Conversion ◽  
Low Frequency ◽  
Internal Tide ◽  
Internal Tides ◽  
Ridge Crest ◽  
Tide Propagation ◽  
Phase Variations ◽  
Perturbation Pressure ◽  
Work Done ◽  
The Impact

Abstract Moored current, temperature, and conductivity measurements are used to study the temporal variability of M2 internal tide generation above the Kaena Ridge, between the Hawaiian islands of Oahu and Kauai. The energy conversion from the barotropic to baroclinic tide measured near the ridge crest varies by a factor of 2 over the 6-month mooring deployment (0.5–1.1 W m−2). The energy flux measured just off the ridge undergoes a similar modulation as the ridge conversion. The energy conversion varies largely because of changes in the phase of the perturbation pressure, suggesting variable work done on remotely generated internal tides. During the mooring deployment, low-frequency current and stratification fluctuations occur on and off the ridge. Model simulations suggest that these variations are due to two mesoscale eddies that passed through the region. The impact of these eddies on low-mode internal tide propagation over the ridge crest is considered. It appears that eddy-related changes in stratification and perhaps cross-ridge current speed contribute to the observed phase variations in perturbation pressure and hence the variable conversion over the ridge.

scholarly journals M2 Internal Tides and Their Observed Wavenumber Spectra from Satellite Altimetry

2016 ◽  
Vol 46 (1) ◽  
pp. 3-22 ◽  
Author(s):  
R. D. Ray ◽  
E. D. Zaron
Keyword(s):  
Internal Tide ◽  
Internal Tides ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
Wave Dynamics ◽  
Spectral Signatures ◽  
Tasman Sea ◽  
Mode 2 ◽  
Satellite Altimeter Data ◽  
Good Agreement

AbstractA near-global chart of surface elevations associated with the stationary M2 internal tide is empirically constructed from multimission satellite altimeter data. An advantage of a strictly empirical mapping approach is that results are independent of assumptions about ocean wave dynamics and, in fact, can be used to test such assumptions. A disadvantage is that present-day altimeter coverage is only marginally adequate to support mapping such short-wavelength features. Moreover, predominantly north–south ground-track orientations and contamination from nontidal oceanographic variability can lead to deficiencies in mapped tides. Independent data from Cryosphere Satellite-2 (CryoSat-2) and other altimeters are used to test the solutions and show positive reduction in variance except in regions of large mesoscale variability. The tidal fields are subjected to two-dimensional wavenumber spectral analysis, which allows for the construction of an empirical map of modal wavelengths. Mode-1 wavelengths show good agreement with theoretical wavelengths calculated from the ocean’s mean stratification, with a few localized exceptions (e.g., Tasman Sea). Mode-2 waves are detectable in much of the ocean, with wavelengths in reasonable agreement with theoretical expectations, but their spectral signatures grow too weak to map in some regions.

Seasonal variability of mesoscale eddies in the Banda Sea inferred from altimeter data

2020 ◽  
Vol 39 (12) ◽  
pp. 11-20
Author(s):  
Baiyang Chen ◽  
Lingling Xie ◽  
Quanan Zheng ◽  
Lei Zhou ◽  
Lei Wang ◽  
...  
Keyword(s):  
Seasonal Variability ◽  
Mesoscale Eddies ◽  
Altimeter Data

scholarly journals Springtime Upwelling and Its Formation Mechanism in Coastal Waters of Manaung Island, Myanmar

2020 ◽  
Vol 12 (22) ◽  
pp. 3777
Author(s):  
Yuhui Li ◽  
Yun Qiu ◽  
Jianyu Hu ◽  
Cherry Aung ◽  
Xinyu Lin ◽  
...  
Keyword(s):  
Surface Layer ◽  
Satellite Remote Sensing ◽  
Subsurface Layer ◽  
World Ocean ◽  
Remote Sensing Data ◽  
Remote Forcing ◽  
Forcing Mechanisms ◽  
World Ocean Atlas ◽  
The Impact ◽  
Local Wind Forcing

Multisource satellite remote sensing data and the World Ocean Atlas 2018 (WOA18) temperature and salinity dataset have been used to analyze the spatial distribution, variability and possible forcing mechanisms of the upwelling off Manaung Island, Myanmar. Signals of upwelling exist off the coasts of Manaung Island, in western Myanmar during spring. It appears in February, reaches its peak in March and decays in May. Low-temperature (<28.3 °C) and high-salinity (>31.8 psu) water at the surface of this upwelling zone is caused by the upwelling of seawater from a depth below 100 m. The impact of the upwelling on temperature is more significant in the subsurface layer than that in the surface layer. In contrast, the impact of the upwelling on salinity in the surface layer is more significant. Further research reveals that the remote forcing from the equator predominantly induces the evolution of the upwelling, while the local wind forcing also contributes to strengthen the intensity of the upwelling during spring.

Monthly Water Exchange through the Ryukyu Islands Revealed by Salinity Structural Changes

2013 ◽  
Vol 864-867 ◽  
pp. 2335-2339
Author(s):  
Ya Pan Liu ◽  
Jian Cheng Kang ◽  
Jiong Zhu ◽  
Qin Chen Han
Keyword(s):  
Structural Changes ◽  
Water Exchange ◽  
High Salinity ◽  
World Ocean ◽  
Core Layer ◽  
Ryukyu Islands ◽  
High Salinity Water ◽  
The Ryukyu Islands ◽  
Salinity Water ◽  
World Ocean Atlas

Using salinity database of World Ocean Atlas 2009 (WOA09) issued by NOAA in 2010, refer the range of high-salinity tongue to indicate the strength about high-salinity water, from the perspective of structural changes of salinity; the water exchange through Ryukyu Islands upper 500 m have been analyzed, the results show that: due to Ryukyu Trough, currents on both sides of Ryukyu Islands occur exchange, for upper 500 m, high-salinity water in east of the Ryukyu Islands mainly invade the west waterthe Kuroshio in East China Sea; the intrusion strength is powerful from the depth of 100 m to 200 m, and the 150 m layer is the core layer of high-salinity water intrusion; the high-salinity water at the east of Ryukyu Islands invades the Kuroshio are stronger in March, May, June, September, October and November, are weaker in April and December.

scholarly journals A Comparison Between the World Ocean Atlas and Hydrobase Climatology

2000 ◽  
Vol 27 (8) ◽  
pp. 1191-1194 ◽  
Author(s):  
C. -W. June Chang ◽  
Yi Chao
Keyword(s):  
World Ocean ◽  
The World ◽  
World Ocean Atlas

scholarly journals MAREDAT: towards a World Ocean Atlas of MARine Ecosystem DATa

2012 ◽  
Vol 5 (2) ◽  
pp. 1077-1106 ◽  
Author(s):  
E. T. Buitenhuis ◽  
M. Vogt ◽  
R. Moriarty ◽  
N. Bednaršek ◽  
S. C. Doney ◽  
...  
Keyword(s):  
Marine Ecosystem ◽  
World Ocean ◽  
Zooplankton Biomass ◽  
Global Ocean ◽  
Special Issue ◽  
Biomass Distribution ◽  
Phytoplankton Pigment ◽  
Autotrophic Biomass ◽  
Ocean Ecosystem ◽  
World Ocean Atlas

Abstract. We present a summary of biomass data for 11 Plankton Functional Types (PFTs) plus phytoplankton pigment data, compiled as part of the MARine Ecosystem biomass DATa (MAREDAT) initiative. The goal of the MAREDAT initiative is to provide global gridded data products with coverage of all biological components of the global ocean ecosystem. This special issue is the first step towards achieving this. The PFTs presented here include picophytoplankton, diazotrophs, coccolithophores, Phaeocystis, diatoms, picoheterotrophs, microzooplankton, foraminifers, mesozooplankton, pteropods and macrozooplankton. All variables have been gridded onto a World Ocean Atlas (WOA) grid (1° × 1° × 33 vertical levels × monthly climatologies). The data show that (1) the global total heterotrophic biomass (2.0–6.4 Pg C) is at least as high as the total autotrophic biomass (0.5–2.6 Pg C excluding nanophytoplankton and autotrophic dinoflagellates), (2) the biomass of zooplankton calcifiers (0.9–2.3 Pg C) is substantially higher than that of coccolithophores (0.01–0.14 Pg C), (3) patchiness of biomass distribution increases with organism size, and (4) although zooplankton biomass measurements below 200 m are rare, the limited measurements available suggest that Bacteria and Archaea are not the only heterotrophs in the deep sea. More data will be needed to characterize ocean ecosystem functioning and associated biogeochemistry in the Southern Hemisphere and below 200 m. Microzooplankton database: doi:10.1594/PANGAEA.779970.

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