scholarly journals First evaluation of MyOcean altimetric data in the Arctic Ocean

2012 ◽  
Vol 9 (1) ◽  
pp. 291-314 ◽  
Author(s):  
Y. Cheng ◽  
O. B. Andersen ◽  
P. Knudsen
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
The Arctic ◽  
Data Sets ◽  
Tide Gauge Data ◽  
Data Set ◽  
Altimetric Data ◽  
Gauge Data ◽  
Sea Level Trend ◽  
Annual Signal

Abstract. The MyOcean V2 preliminary (V2p) data set of weekly gridded sea level anomaly (SLA) maps from 1993 to 2009 over the Arctic region is evaluated against existing altimetric data sets and tide gauge data. Compared with DUACS V3.0.0 (Data Unification and Altimeter Combination System) data set, MyOcean V2p data set improves spatial coverage and quality as well as maximum temporal correlation coefficient between altimetry and tide gauge data. The estimated amplitude of sea level annual signal and linear sea level trend from MyOcean data set are evaluated against altimetry from DUACS and RADS (Radar Altimeter Database System), the SODA (Simple Ocean Data Assimilation) ocean reanalysis and tide gauge data sets from PSMSL (Permanent Service for Mean Sea Level). The results show that the MyOcean data set fits in-situ measurements better than DUACS data set with respect to amplitude of annual signal and linear sea level trend. However, the MyOcean V2p data set exhibits an unrealistic large linear sea level trend compared with that from other data sources.

scholarly journals More confounders at global and decadal scales in detecting recent sea level accelerations

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
H. Bâki Iz
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Almost Periodic ◽  
Altimetry Data ◽  
Tide Gauge Data ◽  
Gauge Data ◽  
Close Range ◽  
Globally Distributed ◽  
Satellite Altimetry Data

AbstractThe residuals of 27 globally distributed long tide gauge recordswere scrutinized after removing the globally compounding effect of the periodic lunar node tides and almost periodic solar radiation’s sub and superharmonics from the tide gauge data. The spectral analysis of the residuals revealed additional unmodeled periodicities at decadal scales, 19 of which are within the close range of 12–14 years, at 27 tide gauge stations. The amplitudes of the periodicitieswere subsequently estimated for the spectrally detected periods and they were found to be statistically significant (p «0.05) for 18 out of 27 globally distributed tide gauge stations. It was shown that the estimated amplitudes at different localities may have biased the outcome of all the previous studies based on tide gauge or satellite altimetry data that did not account for these periodicities, within the range −0.5 – 0.5 mm/yr., acting as another confounder in detecting 21st century sea level rise.

scholarly journals Modeling regional sea level rise using local tide gauge data

2012 ◽  
Vol 2 (3) ◽  
pp. 188-199 ◽  
Author(s):  
H. Bâki Iz ◽  
L. Berry ◽  
M. Koch
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Reference Level ◽  
Tide Gauge Data ◽  
Mean Sea Level ◽  
Proposed Model ◽  
Gauge Data ◽  
Local Reference ◽  
Order Of Magnitude ◽  
Serial Correlations

AbstractCurrently regional mean sea level trends and variations are inferred from the analysis of several individual local tide gauge data that spanonly a long period of time at a given region. In this study, we propose using a model to merge various tide gauge data, regardless of theirtime span, in a single solution, to estimate parameters representative of regional mean sea level trends. The proposed model can accountfor the geographical correlations among the local tide gauge stations as well as serial correlations, if needed, for individual stations’ data.Such a vigorous regional solution enables statistically optimal uncertainties for estimated and projected trends. The proposed formulationalso unifies all the local reference levels by modeling their offsets from a predefined station’s reference level. To test its effectiveness, theproposed model was used to investigate the regional mean sea level variations for the coastal areas of the Florida Panhandle using 26 localtide gauge stations that span approximately 830 years of monthly averages from the Permanent Service for Mean Sea Level repository. Thenew estimate for the regional trend is 2.14 mm/yr with a ±0.03 mm/yr standard error, which is an order of magnitude improvement overthe most recent mean sea level trend estimates and projections for the Florida region obtained from simple averages of local solutions.

Review and Assessment of gap-filling methods from tide-gauges: Maxima missing at the Esbjerg, Denmark station, before 1910.

2020 ◽  
Author(s):  
Peter Thejll
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Model Fit ◽  
Tide Gauges ◽  
Harmonic Model ◽  
Gap Filling ◽  
Tide Gauge Data ◽  
Tide Gauge Record ◽  
Long Baseline ◽  
Gauge Data

<p>Information on extremes of the sea-level is obtained from tide-gauge<br>records.  Such records may have gaps.</p><p>Estimates of potential changes in the size and/or frequency of sea-level<br>extremes are hampered by long gaps, or when just the high extremes are<br>missing due, e.g. to equipment failure.</p><p>Methods used for filling such gaps can be based on having multiple<br>records from gauges near each other; but what to do if there is<br>only one record? This problem can typically occur when old tide-gauge<br>records are used -- the use of multiple recorders at the same place is<br>more wide-spread today. However, especially older and therefore longer<br>records hold the key to obtaining long-baseline insights into the temporal<br>evolution of extreme tides and thus impacts of e.g. climate change.</p><p>In this work, we review and assess methods for gap filling. We asses using<br>the 'known truth' method, i.e. by applying realistic gaps to complete<br>gauge records and reconstructing and then comparing errors calculated as<br>the diffrence between modelled and actual values.  We compare a simple<br>harmonic model fit method to various spline methods as well as Neural<br>network and deep learning approches.  We also test a hybrid method<br>which uses not just tide-gauge data but also air pressure readings<br>from a meteorological station near the tide-gauge.</p><p>We then attempt to fill in the missing maxima of the Esbjerg, Denmark<br>hourly tide-gauge record since 1889. Particularly, before 1910 the maxima<br>above 300 cm are missing (Bijl, et al., 1999), and we try to fill these in.</p>

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