The Experts below are selected from a list of 22800 Experts worldwide ranked by ideXlab platform
Pifsc Noaa - One of the best experts on this subject based on the ideXlab platform.
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Sea Surface Height: Long-term Mean
2014Co-Authors: Pifsc NoaaAbstract:Long-term average Sea Surface Height (meters) above reference spheroid, i.e., Sea Surface topography, derived from the HYCOM model, HYCOM + NCODA Global 1/12degree Analysis, all experiments aggregated. The climatology was built using tools in the Marine Geospatial Ecology Tools (http://code.env.duke.edu/projects/mget) and ArcGIS geoprocessing tools. For more information about HYCOM, see http://hycom.org/dataserver/glb-analysis/. Spatial Extent = Pacific Range, Min X = 110 E, Max X = 70 W, Min Y = 70 S, Max Y = 60 N; Temporal extent = 2004-2011; Spatial resolution =~1/12th degree; Temporal resolution = monthly; Spatial persistence = dynamic, km2; Temporal persistence = months, Seasons, interannual, decades
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Sea Surface Height: Seasonal (Oct-Dec) Maximum
2014Co-Authors: Pifsc NoaaAbstract:Seasonal (Oct-Dec) maximum Sea Surface Height (meters) above reference spheroid, i.e., Sea Surface topography, derived from the HYCOM model, HYCOM + NCODA Global 1/12degree Analysis, all experiments aggregated. The climatology was built using tools in the Marine Geospatial Ecology Tools (http://code.env.duke.edu/projects/mget) and ArcGIS geoprocessing tools. For more information about HYCOM, see http://hycom.org/dataserver/glb-analysis/. Spatial Extent = Pacific Range, Min X = 110 E, Max X = 70 W, Min Y = 70 S, Max Y = 60 N; Temporal extent = 2004-2011; Spatial resolution =~1/12th degree; Temporal resolution = monthly; Spatial persistence = dynamic, km2; Temporal persistence = months, Seasons, interannual, decades
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Sea Surface Height: Seasonal (Jul-Sep) Average Maximum
2014Co-Authors: Pifsc NoaaAbstract:Seasonal (Jul-Sep) average maximum Sea Surface Height (meters) above reference spheroid, i.e., Sea Surface topography, derived from the HYCOM model, HYCOM + NCODA Global 1/12degree Analysis, all experiments aggregated. The climatology was built using tools in the Marine Geospatial Ecology Tools (http://code.env.duke.edu/projects/mget) and ArcGIS geoprocessing tools. For more information about HYCOM, see http://hycom.org/dataserver/glb-analysis/. Spatial Extent = Pacific Range, Min X = 110 E, Max X = 70 W, Min Y = 70 S, Max Y = 60 N; Temporal extent = 2004-2011; Spatial resolution =~1/12th degree; Temporal resolution = monthly; Spatial persistence = dynamic, km2; Temporal persistence = months, Seasons, interannual, decades
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Sea Surface Height: Seasonal (Jul-Sep) Average Minimum
2014Co-Authors: Pifsc NoaaAbstract:Seasonal (Jul-Sep) average minimum Sea Surface Height (meters) above reference spheroid, i.e., Sea Surface topography, derived from the HYCOM model, HYCOM + NCODA Global 1/12degree Analysis, all experiments aggregated. The climatology was built using tools in the Marine Geospatial Ecology Tools (http://code.env.duke.edu/projects/mget) and ArcGIS geoprocessing tools. For more information about HYCOM, see http://hycom.org/dataserver/glb-analysis/. Spatial Extent = Pacific Range, Min X = 110 E, Max X = 70 W, Min Y = 70 S, Max Y = 60 N; Temporal extent = 2004-2011; Spatial resolution =~1/12th degree; Temporal resolution = monthly; Spatial persistence = dynamic, km2; Temporal persistence = months, Seasons, interannual, decades
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Sea Surface Height: Seasonal (Apr-Jun) Extreme Minimum
2014Co-Authors: Pifsc NoaaAbstract:Seasonal (Apr-Jun) extreme minimum Sea Surface Height (meters) above reference spheroid, i.e., Sea Surface topography, derived from the HYCOM model, HYCOM + NCODA Global 1/12degree Analysis, all experiments aggregated. The climatology was built using tools in the Marine Geospatial Ecology Tools (http://code.env.duke.edu/projects/mget) and ArcGIS geoprocessing tools. For more information about HYCOM, see http://hycom.org/dataserver/glb-analysis/. Spatial Extent = Pacific Range, Min X = 110 E, Max X = 70 W, Min Y = 70 S, Max Y = 60 N; Temporal extent = 2004-2011; Spatial resolution =~1/12th degree; Temporal resolution = monthly; Spatial persistence = dynamic, km2; Temporal persistence = months, Seasons, interannual, decades
Dudley B. Chelton - One of the best experts on this subject based on the ideXlab platform.
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aliased tidal errors in topex poseidon Sea Surface Height data
Journal of Geophysical Research, 1994Co-Authors: Michael G. Schlax, Dudley B. CheltonAbstract:Alias periods and wavelengths for the M2, S2, N2, K1, O1, and P1 tidal constituents are calculated for TOPEX/POSEIDON. Alias wavelengths calculated in previous studies are shown to be in error, and a correct method is presented. With the exception of the K1 constituent, all of these tidal aliases for TOPEX/POSEIDON have periods shorter than 90 days and are unlikely to be confounded with long-period Sea Surface Height signals associated with real ocean processes. In particular, the correspondence between the periods and wavelengths of the M2 alias and annual baroclinic Rossby waves that plagued Geosat Sea Surface Height data is avoided. The potential for aliasing residual tidal errors in smoothed estimates of Sea Surface Height is calculated for the six tidal constituents. The potential for aliasing the lunar tidal constituents M2, N2, and O1 fluctuates with latitude and is different for estimates made at the crossovers of ascending and descending ground tracks than for estimates at points midway between crossovers. The potential for aliasing the solar tidal constituents S2, K1, and P1 varies smoothly with latitude. S2 is strongly aliased for latitudes within 50 degrees of the equator, while K1 and P1 are only weakly aliased in that range. A weighted least squares method for estimating and removing residual tidal errors from TOPEX/POSEIDON Sea Surface Height data is presented. A clear understanding of the nature of aliased tidal error in TOPEX/POSEIDON data aids the unambiguous identification of real propagating Sea Surface Height signals. Unequivocal evidence of annual period, westward propagating waves in the North Atlantic is presented.
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Aliased tidal errors in TOPEX/POSEIDON Sea Surface Height data
Journal of Geophysical Research, 1994Co-Authors: Michael G. Schlax, Dudley B. CheltonAbstract:Alias periods and wavelengths for the M2, S2, N2, K1, O1, and P1 tidal constituents are calculated for TOPEX/POSEIDON. Alias wavelengths calculated in previous studies are shown to be in error, and a correct method is presented. With the exception of the K1 constituent, all of these tidal aliases for TOPEX/POSEIDON have periods shorter than 90 days and are unlikely to be confounded with long-period Sea Surface Height signals associated with real ocean processes. In particular, the correspondence between the periods and wavelengths of the M2 alias and annual baroclinic Rossby waves that plagued Geosat Sea Surface Height data is avoided. The potential for aliasing residual tidal errors in smoothed estimates of Sea Surface Height is calculated for the six tidal constituents. The potential for aliasing the lunar tidal constituents M2, N2, and O1 fluctuates with latitude and is different for estimates made at the crossovers of ascending and descending ground tracks than for estimates at points midway between crossovers. The potential for aliasing the solar tidal constituents S2, K1, and P1 varies smoothly with latitude. S2 is strongly aliased for latitudes within 50 degrees of the equator, while K1 and P1 are only weakly aliased in that range. A weighted least squares method for estimating and removing residual tidal errors from TOPEX/POSEIDON Sea Surface Height data is presented. A clear understanding of the nature of aliased tidal error in TOPEX/POSEIDON data aids the unambiguous identification of real propagating Sea Surface Height signals. Unequivocal evidence of annual period, westward propagating waves in the North Atlantic is presented.
Michael G. Schlax - One of the best experts on this subject based on the ideXlab platform.
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aliased tidal errors in topex poseidon Sea Surface Height data
Journal of Geophysical Research, 1994Co-Authors: Michael G. Schlax, Dudley B. CheltonAbstract:Alias periods and wavelengths for the M2, S2, N2, K1, O1, and P1 tidal constituents are calculated for TOPEX/POSEIDON. Alias wavelengths calculated in previous studies are shown to be in error, and a correct method is presented. With the exception of the K1 constituent, all of these tidal aliases for TOPEX/POSEIDON have periods shorter than 90 days and are unlikely to be confounded with long-period Sea Surface Height signals associated with real ocean processes. In particular, the correspondence between the periods and wavelengths of the M2 alias and annual baroclinic Rossby waves that plagued Geosat Sea Surface Height data is avoided. The potential for aliasing residual tidal errors in smoothed estimates of Sea Surface Height is calculated for the six tidal constituents. The potential for aliasing the lunar tidal constituents M2, N2, and O1 fluctuates with latitude and is different for estimates made at the crossovers of ascending and descending ground tracks than for estimates at points midway between crossovers. The potential for aliasing the solar tidal constituents S2, K1, and P1 varies smoothly with latitude. S2 is strongly aliased for latitudes within 50 degrees of the equator, while K1 and P1 are only weakly aliased in that range. A weighted least squares method for estimating and removing residual tidal errors from TOPEX/POSEIDON Sea Surface Height data is presented. A clear understanding of the nature of aliased tidal error in TOPEX/POSEIDON data aids the unambiguous identification of real propagating Sea Surface Height signals. Unequivocal evidence of annual period, westward propagating waves in the North Atlantic is presented.
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Aliased tidal errors in TOPEX/POSEIDON Sea Surface Height data
Journal of Geophysical Research, 1994Co-Authors: Michael G. Schlax, Dudley B. CheltonAbstract:Alias periods and wavelengths for the M2, S2, N2, K1, O1, and P1 tidal constituents are calculated for TOPEX/POSEIDON. Alias wavelengths calculated in previous studies are shown to be in error, and a correct method is presented. With the exception of the K1 constituent, all of these tidal aliases for TOPEX/POSEIDON have periods shorter than 90 days and are unlikely to be confounded with long-period Sea Surface Height signals associated with real ocean processes. In particular, the correspondence between the periods and wavelengths of the M2 alias and annual baroclinic Rossby waves that plagued Geosat Sea Surface Height data is avoided. The potential for aliasing residual tidal errors in smoothed estimates of Sea Surface Height is calculated for the six tidal constituents. The potential for aliasing the lunar tidal constituents M2, N2, and O1 fluctuates with latitude and is different for estimates made at the crossovers of ascending and descending ground tracks than for estimates at points midway between crossovers. The potential for aliasing the solar tidal constituents S2, K1, and P1 varies smoothly with latitude. S2 is strongly aliased for latitudes within 50 degrees of the equator, while K1 and P1 are only weakly aliased in that range. A weighted least squares method for estimating and removing residual tidal errors from TOPEX/POSEIDON Sea Surface Height data is presented. A clear understanding of the nature of aliased tidal error in TOPEX/POSEIDON data aids the unambiguous identification of real propagating Sea Surface Height signals. Unequivocal evidence of annual period, westward propagating waves in the North Atlantic is presented.
Jens Schröter - One of the best experts on this subject based on the ideXlab platform.
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Can Sea Surface Height be used to estimate oceanic transport variability
Geophysical Research Letters, 2011Co-Authors: Vladimir Ivchenko, Dmitry Sidorenko, Sergey Danilov, Martin Losch, Jens SchröterAbstract:The relation between the Sea Surface Height and the meridional transport across a zonal section at 26.5°N in the North Atlantic is studied by using an eddy resolving ocean state estimate simulated with the Massachusetts Institute of Technology general circulation model. It is shown that the correlation between the zonal Sea Surface Height difference and transport can be substantially increased if the steric Height contribution from the Seasonal thermocline is removed. The latter explains a substantial part of Sea Surface Height variability, but its effect on transport is weak. It is also found that the zonal steric Height difference correlates well with the transport after the contribution of the Seasonal thermocline has been removed. There is a similar agreement (with correlation coefficient of 0.63 for the full signal and 0.89 for the mean Seasonal cycle) between the meridional transport and steric Height based on observations from the Rapid Climate Change (RAPID) project.
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Estimating a Mean Ocean State from Hydrography and Sea-Surface Height Data with a Nonlinear Inverse Section Model: Twin Experiments with a Synthetic Dataset
Journal of Physical Oceanography, 2002Co-Authors: Martin Losch, René Redler, Jens SchröterAbstract:The recovery of the oceanic flow field from in situ data is one of the oldest problems of modern oceanography. In this study, a stationary, nonlinear inverse model is used to estimate a mean geostrophic flow field from hydrographic data along a hydrographic section. The model is augmented to improve these estimates with measurements of the absolute Sea-Surface Height by satellite altimetry. Measurements of the absolute Sea-Surface Height include estimates of an equipotential Surface, the geoid. Compared to oceanographic measurements, the geoid is known only to low accuracy and spatial resolution, which restricts the use of Sea-Surface Height data to applications of large-scale phenomena of the circulation. Dedicated satellite missions that are designed for high precision, high-resolution geoid models are planned and/or in preparation. This study, which relies on twin experiments, assesses the important contribution of improved geoid models to estimating the mean flow field along a hydrographic section. When the Sea-Surface Height data are weighted according to the error estimates of the future highly accurate geoid models GRACE (Gravity Recovery And Climate Experiment) and GOCE (Gravity Field and Steady-State Ocean Circulation Explorer), integrated fluxes of mass and temperature can be determined with an accuracy that is improved over the case with no Sea-Surface Height data by up to 55%. With the error estimates of the currently best geoid model EGM96, the reduction of the estimated flux errors does not exceed 18%.
Martin Losch - One of the best experts on this subject based on the ideXlab platform.
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Can Sea Surface Height be used to estimate oceanic transport variability
Geophysical Research Letters, 2011Co-Authors: Vladimir Ivchenko, Dmitry Sidorenko, Sergey Danilov, Martin Losch, Jens SchröterAbstract:The relation between the Sea Surface Height and the meridional transport across a zonal section at 26.5°N in the North Atlantic is studied by using an eddy resolving ocean state estimate simulated with the Massachusetts Institute of Technology general circulation model. It is shown that the correlation between the zonal Sea Surface Height difference and transport can be substantially increased if the steric Height contribution from the Seasonal thermocline is removed. The latter explains a substantial part of Sea Surface Height variability, but its effect on transport is weak. It is also found that the zonal steric Height difference correlates well with the transport after the contribution of the Seasonal thermocline has been removed. There is a similar agreement (with correlation coefficient of 0.63 for the full signal and 0.89 for the mean Seasonal cycle) between the meridional transport and steric Height based on observations from the Rapid Climate Change (RAPID) project.
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Estimating a Mean Ocean State from Hydrography and Sea-Surface Height Data with a Nonlinear Inverse Section Model: Twin Experiments with a Synthetic Dataset
Journal of Physical Oceanography, 2002Co-Authors: Martin Losch, René Redler, Jens SchröterAbstract:The recovery of the oceanic flow field from in situ data is one of the oldest problems of modern oceanography. In this study, a stationary, nonlinear inverse model is used to estimate a mean geostrophic flow field from hydrographic data along a hydrographic section. The model is augmented to improve these estimates with measurements of the absolute Sea-Surface Height by satellite altimetry. Measurements of the absolute Sea-Surface Height include estimates of an equipotential Surface, the geoid. Compared to oceanographic measurements, the geoid is known only to low accuracy and spatial resolution, which restricts the use of Sea-Surface Height data to applications of large-scale phenomena of the circulation. Dedicated satellite missions that are designed for high precision, high-resolution geoid models are planned and/or in preparation. This study, which relies on twin experiments, assesses the important contribution of improved geoid models to estimating the mean flow field along a hydrographic section. When the Sea-Surface Height data are weighted according to the error estimates of the future highly accurate geoid models GRACE (Gravity Recovery And Climate Experiment) and GOCE (Gravity Field and Steady-State Ocean Circulation Explorer), integrated fluxes of mass and temperature can be determined with an accuracy that is improved over the case with no Sea-Surface Height data by up to 55%. With the error estimates of the currently best geoid model EGM96, the reduction of the estimated flux errors does not exceed 18%.
