Impact of the CHAMP Mission on Estimating the Mean Sea Surface

2005 ◽  
pp. 205-210
Author(s):  
Verena Seufer ◽  
Jens Schröter ◽  
Manfred Wenzel ◽  
Wolfgang Keller
Keyword(s):  
Sea Surface ◽  
Mean Sea Surface ◽  
The Mean

scholarly journals Impacts of mean dynamic topography on a regional ocean assimilation system

Ocean Science ◽  
2015 ◽  
Vol 11 (5) ◽  
pp. 829-837 ◽  
Author(s):  
C. Yan ◽  
J. Zhu ◽  
C. A. S. Tanajura
Keyword(s):  
Data Assimilation ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Dynamic Topography ◽  
Altimetry Data ◽  
Mean Dynamic Topography ◽  
Mean Sea Surface ◽  
The Mean

Abstract. An ocean data assimilation system was developed for the Pacific–Indian oceans with the aim of assimilating altimetry data, sea surface temperature, and in situ measurements from Argo (Array for Real-time Geostrophic Oceanography), XBT (expendable bathythermographs), CTD (conductivity temperature depth), and TAO (Tropical Atmosphere Ocean). The altimetry data assimilation requires the addition of the mean dynamic topography to the altimetric sea level anomaly to match the model sea surface height. The mean dynamic topography is usually computed from the model long-term mean sea surface height, and is also available from gravimetric satellite data. In this study, the impact of different mean dynamic topographies on the sea level anomaly assimilation is examined. Results show that impacts of the mean dynamic topography cannot be neglected. The mean dynamic topography from the model long-term mean sea surface height without assimilating in situ observations results in worsened subsurface temperature and salinity estimates. Even if all available observations including in situ measurements, sea surface temperature measurements, and altimetry data are assimilated, the estimates are still not improved. This proves the significant impact of the MDT (mean dynamic topography) on the analysis system, as the other types of observations do not compensate for the shortcoming due to the altimetry data assimilation. The gravimeter-based mean dynamic topography results in a good estimate compared with that of the experiment without assimilation. The mean dynamic topography computed from the model long-term mean sea surface height after assimilating in situ observations presents better results.

scholarly journals A study of the chilean vertical network through global geopotential models and the cnes cls 2011 global mean sea surface

2014 ◽  
Vol 20 (2) ◽  
pp. 300-316 ◽  
Author(s):  
Henry Montecino Castro ◽  
Aharon Cuevas Cordero ◽  
Sílvio Rogério Correia de Freitas
Keyword(s):  
Vertical Component ◽  
Sea Surface ◽  
Tide Gauges ◽  
Satellite Mission ◽  
Geopotential Models ◽  
Mean Sea Surface ◽  
The Mean ◽  
Combining Information ◽  
Global Mean ◽  
Goce Satellite

Most aspects related to the horizontal component of the Geocentric Reference System for the Americas (SIRGAS) have been solved. However, in the case of the vertical component there are still aspects of definition, national realizations and continental unification still not accomplished. Chile is no exception; due to its particular geographic characteristics, a number of tide gauges (TG) had to be installed in the coast from which the leveling lines that compose the Chilean Vertical Network (CHVN) were established. This study explored the offsets of the CHVN by two different approaches; one geodetic and one oceanographic. In the first approach, the offsets were obtained in relation to the following Global Geopotential Models (GGM): the satellite-only model (unbiased) GO_CONS_gcf_2_tim_r3 derived from GOCE satellite mission; EGM2008 (combined-biased); and GOEGM08, combining information from the GO_CONS_gcf_2_tim_r3 in long wavelengths (n max~200) with the mean/short wavelengths of EGM2008 (n>200). In the oceanographic method, we used the CNES CLS 2011 Global Mean Sea surface and EIGEN_GRACE_5C GGM to obtain the values of MDT at the different TG. We also evaluated the CHVN in relation to different GGMs. The results showed consistency between the values obtained by the two methods at the TG of Valparaíso and Puerto Chacabuco. In terms of the evaluation of the GGM, GOEGM08 produced the best results.

scholarly journals Impacts of mean dynamic topography on a regional ocean assimilation system

2015 ◽  
Vol 12 (3) ◽  
pp. 1083-1105
Author(s):  
C. Yan ◽  
J. Zhu ◽  
C. A. S. Tanajura
Keyword(s):  
Sea Surface Height ◽  
Sea Surface ◽  
Dynamic Topography ◽  
Altimetry Data ◽  
Mean Dynamic Topography ◽  
Mean Sea Surface ◽  
In Situ Observations ◽  
The Mean

Abstract. An ocean assimilation system was developed for the Pacific-Indian oceans with the aim of assimilating altimetry data, sea surface temperature, and in-situ measurements from ARGO, XBT, CTD, and TAO. The altimetry data assimilation requires the addition of the mean dynamic topography to the altimetric sea level anomaly to match the model sea surface height. The mean dynamic topography is usually computed from the model long-term mean sea surface height, and is also available from gravimeteric satellite data. In this study, different mean dynamic topographies are used to examine their impacts on the sea level anomaly assimilation. Results show that impacts of the mean dynamic topography cannot be neglected. The mean dynamic topography from the model long-term mean sea surface height without assimilating in-situ observations results in worsened subsurface temperature and salinity estimates. The gravimeter-based mean dynamic topography results in an even worse estimate. Even if all available observations including in-situ measurements, sea surface temperature measurements, and altimetry data are assimilated, the estimates are still not improved. This further indicates that the other types of observations do not compensate for the shortcoming due to the altimetry data assimilation. The mean dynamic topography computed from the model's long-term mean sea surface height after assimilating in-situ observations presents better results.

The mean sea surface height and geoid along the Geosat subtrack from Bermuda to Cape Cod

1991 ◽  
Vol 96 (C7) ◽  
pp. 12699 ◽  
Author(s):  
Kathryn A. Kelly ◽  
Terrence M. Joyce ◽  
David M. Schubert ◽  
Michael J. Caruso
Keyword(s):  
Sea Surface Height ◽  
Sea Surface ◽  
Cape Cod ◽  
Mean Sea Surface ◽  
The Mean

scholarly journals Quality Controlling Surf Zone Acoustic Doppler Velocimeter Observations to Estimate the Turbulent Dissipation Rate

2010 ◽  
Vol 27 (12) ◽  
pp. 2039-2055 ◽  
Author(s):  
Falk Feddersen
Keyword(s):  
Dissipation Rate ◽  
Wave Amplitude ◽  
Surf Zone ◽  
Sea Surface ◽  
Acoustic Doppler Velocimeter ◽  
Turbulent Dissipation ◽  
Mean Sea Surface ◽  
Data Points ◽  
The Mean ◽  
Velocity Spectra

Abstract High-quality measurements of the turbulent dissipation rate ε are required to diagnose field surf-zone turbulence budgets. Quality control (QC) methods are presented for estimating surf zone ε with acoustic Doppler velocimeter (ADV) data. Bad ADV velocity data points are diagnosed with both the ADV signal strength (SS) and correlation (CORR). The fraction of bad SS data points (δSS) depends inversely upon the wave-amplitude-normalized transducer distance below the mean sea surface. The fraction of bad CORR data points δCORR can be elevated when δSS is low. The δCORR depends inversely upon the wave-amplitude-normalized sensing volume distance below the mean sea surface, and also increases with increased wave breaking, consistent with turbulence- and bubble-induced Doppler noise. Velocity spectra derived from both “patched” and “interpolated” time series are used to estimate ε. Two QC tests, based upon the properties of a turbulent inertial subrange, are used to reject bad ε data runs. The first test checks that the vertical velocity spectrum’s power-law exponent is near . The second test checks that a ratio R of horizontal and vertical velocity spectra is near 1. Over all δCORR, 70% of the patched and interpolated data runs pass these tests. However, for larger δCORR > 0.1 (locations higher in the water column), 50% more patched than interpolated data runs pass the QC tests. Previous QC methods designed for wave studies are not appropriate for ε QC. The results suggest that ε can be consistently estimated over the lower 60% of the water column and >0.1 m above the bed within a saturated surf zone.

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