A long-term volume transport time series estimated by combining in situ observation and satellite altimeter data in the northern South China Sea

2015 ◽  
Vol 71 (6) ◽  
pp. 663-673 ◽  
Author(s):  
Xiao-Hua Zhu ◽  
Ruixiang Zhao ◽  
Xinyu Guo ◽  
Yu Long ◽  
Yun-Long Ma ◽  
...  
Keyword(s):  
Time Series ◽  
Northern South China Sea ◽  
Volume Transport ◽  
Altimeter Data ◽  
In Situ Observation ◽  
Transport Time ◽  
Satellite Altimeter ◽  
Satellite Altimeter Data

scholarly journals The East Madagascar Current: Volume Transport and Variability Based on Long-Term Observations

2016 ◽  
Vol 46 (4) ◽  
pp. 1045-1065 ◽  
Author(s):  
Leandro Ponsoni ◽  
Borja Aguiar-González ◽  
Herman Ridderinkhof ◽  
Leo R. M. Maas
Keyword(s):  
Volume Transport ◽  
Altimeter Data ◽  
Surface Transport ◽  
Sea Level Anomalies ◽  
Anticyclonic Eddies ◽  
Satellite Altimeter Data ◽  
Observational Program ◽  
Good Agreement

AbstractThis study provides a long-term description of the poleward East Madagascar Current (EMC) in terms of its observed velocities, estimated volume transport, and variability based on both ~2.5 yr of continuous in situ measurements and ~21 yr of satellite altimeter data. An array of five moorings was deployed at 23°S off eastern Madagascar as part of the Indian–Atlantic Exchange in present and past climate (INATEX) observational program. On average, the EMC has a horizontal scale of about 60–100 km and is found from the surface to about 1000-m depth. Its time-averaged core is positioned at the surface, at approximately 20 km from the coast, with velocity of 79 (±21) cm s−1. The EMC mean volume transport is estimated to be 18.3 (±8.4) Sverdrups (Sv; 1 Sv ≡ 106 m3 s−1). During the strongest events, maximum velocities and transport reach up to 170 cm s−1 and 50 Sv, respectively. A good agreement is found between the in situ transport estimated over the first 8 m of water column [0.32 (±0.13) Sv] with the altimetry-derived volume transport [0.28 (±0.09) Sv]. Results from wavelet analysis display a dominant nearly bimonthly (45–85 days) frequency band of transport variability, which explains about 41% of the transport variance. Altimeter data suggest that this band of variability is induced by the arrival of westward-propagating sea level anomalies, which in turn are likely represented by mesoscale cyclonic and anticyclonic eddies. Annual averages of the altimeter-derived surface transport suggest that interannual variabilities also play a role in the EMC system.

scholarly journals On the Use of Satellite Altimeter Data in Argo Quality Control

2009 ◽  
Vol 26 (2) ◽  
pp. 395-402 ◽  
Author(s):  
Stephanie Guinehut ◽  
Christine Coatanoan ◽  
Anne-Lise Dhomps ◽  
Pierre-Yves Le Traon ◽  
Gilles Larnicol
Keyword(s):  
Time Series ◽  
Quality Control ◽  
Real Time ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
Sea Level Anomalies ◽  
The Impact ◽  
Satellite Altimeter Data ◽  
Made In

Abstract Satellite altimeter measurements are used to check the quality of the Argo profiling floats time series. The method compares collocated sea level anomalies from altimeter measurements and dynamic height anomalies calculated from Argo temperature and salinity profiles for each Argo float time series. Different kinds of anomalies (sensor drift, bias, spikes, etc.) have been identified on some real-time but also delayed-mode Argo floats. About 4% of the floats should probably not be used until they are carefully checked and reprocessed by the principal investigators (PIs). The method appears to be very complementary to the existing quality control checks performed in real time or delayed mode. It could also be used to quantify the impact of the adjustments made in delayed mode on the pressure, temperature, and salinity fields.

Coastal Sea Level Change from in the North Eastern Atlantic

2020 ◽  
Author(s):  
Luciana Fenoglio-Marc ◽  
Bernd Uebbing ◽  
Jürgen Kusche ◽  
Salvatore Dinardo
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Level Change ◽  
Altimeter Data ◽  
Level Change ◽  
The North ◽  
North Eastern ◽  
Coastal Sea

<p>A significant part of the World population lives in the coastal zone, which is affected by coastal sea level rise and extreme events. Our hypothesis is that the most accurate sea level height measurements are derived from the Synthetic Aperture Altimetry (SAR) mode. This study analyses the output of dedicated processing and assesses their impacts on the sea level change of the North-Eastern Atlantic. </p><p>It will be shown that SAR altimetry reduces the minimum usable distance from five to three kilometres when the dedicated coastal retrackers SAMOSA+ and SAMOSA++ are applied to data processed in SAR mode. A similar performance is achieved with altimeter data processed in pseudo low resolution mode (PLRM) when the Spatio-Temporal Altimeter sub-waveform Retracker (STAR) is used. Instead the Adaptive Leading Edge Sub-waveform retracker (TALES) applied to PLRM is less performant. SAR processed altimetry can recover the sea level heights with 4 cm accuracy up to 3-4 km distance to coast. Thanks to the low noise of SAR mode data, the instantaneous SAR and in-situ data have the highest agreement, with the smallest standard deviation of differences and the highest correlation. A co-location of the altimeter data near the tide gauge is the best choice for merging in-situ and altimeter data. The r.m.s. (root mean squared) differences between altimetry and in-situ heights remain large in estuaries and in coastal zone with high tidal regimes, which are still challenging regions. The geophysical parameters derived from CryoSat-2 and Sentinel-3A measurements have similar accuracy, but the different repeat cycle of the two missions locally affects the constructed time-series.</p><p>The impact of these new SAR observations in climate change studies is assessed by evaluating regional and local time series of sea level. At distances to coast smaller than 10 Kilometers the sea level change derived from SAR and LRM data is in good agreement. The long-term sea level variability derived from monthly time-series of LRM altimetry and of land motion-corrected tide gauges agrees within 1 mm/yr for half of in-situ German stations. The long-term sea level variability derived from SAR data show a similar behaviour with increasing length of the time series.</p><p> </p>

Volume Transport Variability Southeast of Okinawa Island Estimated from Satellite Altimeter Data

2004 ◽  
Vol 60 (6) ◽  
pp. 953-962 ◽  
Author(s):  
Xiao-Hua Zhu ◽  
Hiroshi Ichikawa ◽  
Kaoru Ichikawa ◽  
Kensuke Takeuchi
Keyword(s):  
Volume Transport ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
Okinawa Island ◽  
Satellite Altimeter Data

scholarly journals Bermuda’s Tale of Two Time Series: Hydrostation S and BATS*

2007 ◽  
Vol 37 (3) ◽  
pp. 554-571 ◽  
Author(s):  
Helen E. Phillips ◽  
Terrence M. Joyce
Keyword(s):  
Time Series ◽  
Sea Water ◽  
Altimeter Data ◽  
Labrador Sea ◽  
Seasonal Cycles ◽  
Satellite Altimeter ◽  
Spatial View ◽  
The Individual ◽  
Satellite Altimeter Data ◽  
Series Study

Abstract This paper describes the oceanic variability at Bermuda between 1989 and 1999, recorded in two overlapping hydrographic time series. Station S and Bermuda Atlantic Time Series Study (BATS), which are 60 km apart, both show that a multidecadal trend of deep warming has reversed, likely as a result of the increased production of Labrador Sea Water since the early 1980s. In addition to recording similar changes in watermass properties, the two time series show similar mean vertical structure and variance as a function of pressure for temperature, salinity, and density above 1500 dbar. The seasonal cycles of these water properties at the two sites are statistically indistinguishable. The time series differ in the individual eddy events they record and in their variability below 1500 dbar. The two time series are used to investigate the propagation of eddy features. Coherence and phase calculated from the low-mode variability of density show westward propagation at ∼3 cm s−1 of wavelengths around 300–500 km. Satellite altimeter data are used to provide a broader spatial view of the eddy (or wave) field near Bermuda.

scholarly journals Study of the Overflow Transport of the Nordic Sea

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2675
Author(s):  
Wenqi Shi ◽  
Ning Li ◽  
Xianqing Lv
Keyword(s):  
Ocean Circulation ◽  
Pressure Difference ◽  
Deep Convection ◽  
Volume Transport ◽  
Altimeter Data ◽  
Water Production ◽  
Satellite Altimeter ◽  
Salt Structure ◽  
The Mean ◽  
Satellite Altimeter Data

Changes in the climate system over recent decades have had profound impacts on the mean state and variability of ocean circulation, while the Nordic Sea overflow has remained stable in volume transport during the last two decades. The changes of the overflow flux depend on the pressure difference at the depth of the overflow outlet on both sides of the Greenland-Scotland Ridge (GSR). Combining satellite altimeter data and the reanalysis hydrological data, the analysis found that the barotropic pressure difference and baroclinic pressure difference on both sides of the GSR had a good negative correlation from 1993 to 2015. Both are caused by changes in the properties of the upper water, and the total pressure difference has no trend change. The weakening of deep convection can only change the temperature and salt structure of the Nordic Sea, but cannot reduce the mass of the water column. Therefore, the stable pressure difference drives a stable overflow. The overflow water storage in the Nordic Sea is decreasing, which may be caused by the reduction of local overflow water production and the constant overflow flux. When the upper interface of the overflow water body in the Nordic Sea is close to or below the outlet depth, the overflow is likely to greatly slow down or even experience a hiatus in the future, which deserves more attention.

A Feasibility Demonstration of Ocean Model Eddy-resolving Nowcast/Forecast Skill Using Satellite Altimeter Data

2000 ◽  
Author(s):  
Harley E. Hurlburt ◽  
Robert C. Rhodes ◽  
Charlie N. Barron ◽  
E. J. Metzger ◽  
Ole M. Smedstad
Keyword(s):  
Ocean Model ◽  
Forecast Skill ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
Satellite Altimeter Data

Estimating discharge of the Ganga River from satellite altimeter data

2021 ◽  
pp. 126860
Author(s):  
Atul Kumar Rai ◽  
Zafar Beg ◽  
Abhilash Singh ◽  
Kumar Gaurav
Keyword(s):  
Ganga River ◽  
Altimeter Data ◽  
Satellite Altimeter ◽  
Satellite Altimeter Data
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