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 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.

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

Wave Energy Resource Assessment Using Satellite Altimeter Data

2008 ◽  
Author(s):  
Ed Mackay ◽  
AbuBakr Bahaj ◽  
Chris Retzler ◽  
Peter Challenor
Keyword(s):  
Wave Energy ◽  
Significant Wave Height ◽  
Energy Resource ◽  
Resource Assessment ◽  
Altimeter Data ◽  
Energy Converter ◽  
Mean Power ◽  
Satellite Altimeter ◽  
Buoy Data ◽  
Satellite Altimeter Data

The use of altimeter measurements of significant wave height and energy period for quantifying wave energy resource is investigated. A new algorithm for calculating wave period from altimeter data, developed by the authors in previous work, is used to estimate the power generated by the Pelamis wave energy converter and compared to estimates from collocated buoy data. In offshore locations accurate estimates of monthly and annual mean power can be achieved by combining measurements from six altimeter missions. Furthermore, by averaging along sections of the altimeter ground track, we demonstrate that it is possible to gauge the spatial variability in nearshore areas, with a resolution of the order of 10 km. Although measurements along individual tracks are temporally sparse, with TOPEX/Poseidon and Jason on a 10 day repeat orbit, GFO 17 days, and ERS-2 and ENVISAT 35 days, the long record of altimeter measurements means that multi-year mean power from single tracks are of a useful accuracy.

scholarly journals Interpreting and analyzing King Tide in Tuvalu

2014 ◽  
Vol 14 (2) ◽  
pp. 209-217 ◽  
Author(s):  
C.-C. Lin ◽  
C.-R. Ho ◽  
Y.-H. Cheng
Keyword(s):  
Tide Gauge ◽  
Spring Tide ◽  
Temporal Distribution ◽  
Warm Water ◽  
Altimeter Data ◽  
Spatial And Temporal Distribution ◽  
Water Effect ◽  
Satellite Altimeter ◽  
Loss Of Life ◽  
Satellite Altimeter Data

Abstract. The spatial and temporal distribution of sea-level rise has the potential to cause regional flooding in certain areas, and low-lying island countries are severely at risk. Tuvalu, an atoll country located in the southwest Pacific Ocean, has been inundated by this regional flooding for decades. Tuvaluans call this regional flooding phenomenon King Tide, a term not clearly defined, blaming it for loss of life and property in announcing their intention to migrate. In this study, we clarified and interpreted King Tide, and analyzed the factors of King Tide in Tuvalu. Using tide gauge and topographical data, we estimated that 3.2 m could be considered the threshold of King Tide, which implied half of the island of Tuvalu was flooded with seawater. This threshold is consistent with the finding of the National Oceanic and Atmospheric Administration that King Tide events occur once or twice a year. We surveyed 28 King Tide events to analyze the factors of regional flooding. Tide gauge and satellite altimeter data from 1993 to 2012 were cross-validated and indicated that the King Tide phenomenon is significantly related to the warm-water effect. Warm water contributed to the King Tide phenomenon by an average of 5.1% and a maximum of 7.8%. The height of King Tide is affected by the combined factors of spring tide, storm surge, climate variability, and, significantly, by the warm-water effect.

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