New CNES-CLS09 global mean dynamic topography computed from the combination of GRACE data, altimetry, and in situ measurements

Abstract. The Mean Dynamic Topography (MDT) is a key reference surface for altimetry. It is needed for the calculation of the ocean absolute dynamic topography, and under the geostrophic approximation, the estimation of surface currents. CNES-CLS Mean Dynamic Topography (MDT) solutions are calculated by merging information from altimeter data, GRACE and GOCE gravity field and oceanographic in-situ measurements (drifting buoy velocities, hydrological profiles). The objective of this paper is to present the newly updated CNES-CLS18 MDT. The main improvement compared to the previous CNES-CLS13 solution is the use of updated input datasets: the GOCO05S geoid model is used based on the complete GOCE mission (November 2009–October 2013) and 10.5 years of GRACE data, together with all drifting buoy velocities (SVP-type and Argo floats) and hydrological profiles (CORA database) available from 1993–2017 (instead of 1993–2012). The new solution also benefits from improved data processing – in particular a new wind-driven current model has been developed to extract the geostrophic component from the buoy velocities; and methodology – in particular the computation of the medium scale GOCE-based MDT first guess and the correlation scales used for the multivariate mapping have been revised. An evaluation of the new solution compared to the previous version and to other existing MDT show significant improvements both in strong currents and coastal areas.

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The new CNES-CLS18 global mean dynamic topography

Ocean Science ◽

10.5194/os-17-789-2021 ◽

2021 ◽

Vol 17 (3) ◽

pp. 789-808

Author(s):

Sandrine Mulet ◽

Marie-Hélène Rio ◽

Hélène Etienne ◽

Camilia Artana ◽

Mathilde Cancet ◽

...

Keyword(s):

Current Model ◽

Altimeter Data ◽

Dynamic Topography ◽

Geoid Model ◽

Mean Dynamic Topography ◽

Drifting Buoy ◽

Grace Data ◽

The Mean ◽

Global Mean

Abstract. The mean dynamic topography (MDT) is a key reference surface for altimetry. It is needed for the calculation of the ocean absolute dynamic topography, and under the geostrophic approximation, the estimation of surface currents. CNES-CLS mean dynamic topography (MDT) solutions are calculated by merging information from altimeter data, GRACE, and GOCE gravity field and oceanographic in situ measurements (drifting buoy velocities, hydrological profiles). The objective of this paper is to present the newly updated CNES-CLS18 MDT. The main improvement compared to the previous CNES-CLS13 solution is the use of updated input datasets: the GOCO05S geoid model is used based on the complete GOCE mission (November 2009–October 2013) and 10.5 years of GRACE data, together with all drifting buoy velocities (SVP-type and Argo floats) and hydrological profiles (CORA database) available from 1993 to 2017 (instead of 1993–2012). The new solution also benefits from improved data processing (in particular a new wind-driven current model has been developed to extract the geostrophic component from the buoy velocities) and methodology (in particular the computation of the medium-scale GOCE-based MDT first guess has been revised). An evaluation of the new solution compared to the previous version and to other existing MDT solutions show significant improvements in both strong currents and coastal areas.

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A mean dynamic topography computed over the world ocean from altimetry, in situ measurements, and a geoid model

Journal of Geophysical Research Atmospheres ◽

10.1029/2003jc002226 ◽

2004 ◽

Vol 109 (C12) ◽

Cited By ~ 342

Author(s):

M.-H. Rio

Keyword(s):

World Ocean ◽

In Situ Measurements ◽

Dynamic Topography ◽

Geoid Model ◽

Mean Dynamic Topography ◽

The World

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A Mean Dynamic Topography of the Mediterranean Sea computed from altimetric data, in-situ measurements and a general circulation model

Journal of Marine Systems ◽

10.1016/j.jmarsys.2005.02.006 ◽

2007 ◽

Vol 65 (1-4) ◽

pp. 484-508 ◽

Cited By ~ 118

Author(s):

M.-H. Rio ◽

P.-M. Poulain ◽

A. Pascual ◽

E. Mauri ◽

G. Larnicol ◽

...

Keyword(s):

Mediterranean Sea ◽

General Circulation Model ◽

General Circulation ◽

Circulation Model ◽

In Situ Measurements ◽

Dynamic Topography ◽

Mean Dynamic Topography ◽

Altimetric Data ◽

The Mediterranean

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Integration of HF Radar Observations for an Enhanced Coastal Mean Dynamic Topography

Frontiers in Marine Science ◽

10.3389/fmars.2020.588713 ◽

2020 ◽

Vol 7 ◽

Author(s):

Ainhoa Caballero ◽

Sandrine Mulet ◽

Nadia Ayoub ◽

Ivan Manso-Narvarte ◽

Xabier Davila ◽

...

Keyword(s):

High Resolution ◽

Sea Level ◽

Satellite Data ◽

Coastal Areas ◽

Hf Radar ◽

Global Ocean ◽

Dynamic Topography ◽

Mean Dynamic Topography ◽

Radar Measurements

Satellite altimeters provide continuous information of the sea level variability and mesoscale processes for the global ocean. For estimating the sea level above the geoid and monitoring the full ocean dynamics from altimeters measurements, a key reference surface is needed: The Mean Dynamic Topography (MDT). However, in coastal areas, where, in situ measurements are sparse and the typical scales of the motion are generally smaller than in the deep ocean, the global MDT solutions are less accurate than in the open ocean, even if significant improvement has been done in the past years. An opportunity to fill in this gap has arisen with the growing availability of long time-series of high-resolution HF radar surface velocity measurements in some areas, such as the south-eastern Bay of Biscay. The prerequisite for the computation of a coastal MDT, using the newly available data of surface velocities, was to obtain a robust methodology to remove the ageostrophic signal from the HF radar measurements, in coherence with the scales resolved by the altimetry. To that end, we first filtered out the tidal and inertial motions, and then, we developed and tested a method that removed the Ekman component and the remaining divergent part of the flow. A regional high-resolution hindcast simulation was used to assess the method. Then, the processed HF radar geostrophic velocities were used in synergy with additional in situ data, altimetry, and gravimetry to compute a new coastal MDT, which shows significant improvement compared with the global MDT. This study showcases the benefit of combining satellite data with continuous, high-frequency, and synoptic in situ velocity data from coastal radar measurements; taking advantage of the different scales resolved by each of the measuring systems. The integrated analysis of in situ observations, satellite data, and numerical simulations has provided a further step in the understanding of the local ocean processes, and the new MDT a basis for more reliable monitoring of the study area. Recommendations for the replicability of the methodology in other coastal areas are also provided. Finally, the methods developed in this study and the more accurate regional MDT could benefit present and future high-resolution altimetric missions.

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Comparison of GRACE Level-3 Data with Super Conducting Gravimeters in Europe By Means of Signal Decomposition Analysis

10.5194/gstm2020-60 ◽

2020 ◽

Author(s):

Miguel Angel Izquierdo Perez ◽

Christian Voigt ◽

Elmas Sinem Ince ◽

Frank Flechtner

Keyword(s):

Decomposition Analysis ◽

Decomposition Methods ◽

Component Analysis ◽

In Situ Measurements ◽

Alternative Methods ◽

Earth Tides ◽

Grace Data ◽

The Individual ◽

The Impact

With the launch of the Gravity Recovery and Climate Experiment (GRACE) mission in 2002 and continued with GRACE Follow-on (GRACE-FO) since 2018, it is nowadays possible to monitor important mass variations in the Earth system. Nevertheless, validating these observations is a challenging task due to the lack of alternative methods to obtain directly comparable in-situ measurements. The most appropriate approach for this endeavor consists of comparing the GRACE derived Total Water Storage (TWS) residuals against Superconducting Gravimeter (SG) residuals, which provide long term stability. The in-situ data used for this project are the gravity residuals obtained after removing the effects of solid Earth tides and ocean tidal loading, atmospheric loading, instrumental drift, polar motion and length&#8208;of&#8208;day induced gravity changes, from nine SG stations between January 2010 and March 2017. Such residuals were then compared with GRACE retrieved TWS residuals obtained from the Gravity Information System (GravIS) portal (gravis.gfz-potsdam.de). In this project, three decomposition methods were used for the comparisons: Principal Component Analysis (PCA), Spatiotemporal Independent Component Analysis (stICA) and Multivariate Singular Spectral Analysis (MSSA). The main aim was to assess the impact of the GRACE data corrections applied by GravIS to the coefficient C20, the coefficients of degree/order one, and the Glacial Isostatic Adjustment (GIA) effect. Moreover, the Gaussian, DDK and VDK filtering techniques were evaluated as well. The tested methods proved to cope with the residual hydrological effects on SG measurements up to an extend that allows an objective evaluation of the data. The results obtained from this analysis indicate that the most optimal solution is achieved by correcting the C20 and degree/order 1 coefficients. The most effective filters are DDK1, VDK2 and Gaussian with a 500 km bandwidth, in that order. Furthermore, the GIA correction demonstrates to be relevant for northern locations like Onsala. Concerning the decomposition methods, MSSA demonstrates to be a powerful tool, synthesizing the most important common trends among the in-situ measurements of different stations, and displaying the local differences of the signals. The common signals extracted from PCA represent a good overview of the trends from the data but is not detailed at the individual locations. Finally, the stICA decomposition is not able to extract these common signals when the input data is significantly different across the individual variables for SG data. This is explained by the Blind Source Separation (BSS) nature of the methodology, which intends to identify differences among the signals, and is not useful in this case where the signals are affected by the local hydrology. The importance of this study lies in the versatility that the successfully tested methods show for the purpose of GRACE data comparison. Furthermore, the methodology applied in this project can be extended to analyze the current GRACE-FO mission as well other gravimetric satellite missions in the future.

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Impacts of mean dynamic topography on a regional ocean assimilation system

Ocean Science ◽

10.5194/os-11-829-2015 ◽

2015 ◽

Vol 11 (5) ◽

pp. 829-837 ◽

Cited By ~ 5

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.

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A global mean dynamic topography and ocean circulation estimation using a preliminary GOCE gravity model

Journal of Geodesy ◽

10.1007/s00190-011-0485-8 ◽

2011 ◽

Vol 85 (11) ◽

pp. 861-879 ◽

Cited By ~ 78

Author(s):

P. Knudsen ◽

R. Bingham ◽

O. Andersen ◽

Marie-Helene Rio

Keyword(s):

Gravity Model ◽

Ocean Circulation ◽

Dynamic Topography ◽

Mean Dynamic Topography ◽

Global Mean

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Seasonal and Interannual Variations in China’s Groundwater Based on GRACE Data and Multisource Hydrological Models

Remote Sensing ◽

10.3390/rs12050845 ◽

2020 ◽

Vol 12 (5) ◽

pp. 845

Author(s):

Jianxin Zhang ◽

Kai Liu ◽

Ming Wang

Keyword(s):

Correlation Coefficient ◽

Empirical Orthogonal Function ◽

Seasonal Fluctuation ◽

In Situ Measurements ◽

Orthogonal Function ◽

The North ◽

Function Decomposition ◽

Grace Data ◽

Land Data Assimilation System

In this study, we used in situ measurements for the first time to analyze the applicability and effectiveness of evaluating groundwater storage (GWS) changes across China using Gravity Recovery and Climate Experiment (GRACE) satellite products and hydrological data derived from the WaterGap Global Hydrological Model (WGHM), Global Land Data Assimilation System (GLDAS) and eartH2Observe (E2O). The results show that the GWS derived from GRACE JPL Mascons products combined with GLDAS Noah V2.1 data most accurately reflect the overall distribution of GWS changes in China and the correlation coefficient between the in situ measurements reaches 0.538. The empirical orthogonal function decomposition for GWS indicates clear interannual variation and seasonal variation in China. The trends of China’s GWS changes showed a clear regional characteristic from 2003 to 2016. The GWS in the northeast, central-south, and western junction of Xinjiang-Qinghai-Tibet had increased significantly, and the North China Plain (NCP) had a severe decline. The correlation coefficient between the annual trends of precipitation and GWS was 0.57, and it reached 0.73 when four provinces (Beijing, Tianjin, Shanxi, Hebei) that are wholly or partially located in the NCP were excluded. The seasonal variability of GWS in China was obvious and the volatilities in Jiangxi, Hunan and Fujian provinces were the highest, reaching 6.39 cm, 6.33 cm and 5.20 cm, respectively. The empirical orthogonal function decomposition for GWS and precipitation over China indicated seasonal consistency with a correlation coefficient of 0.76. The awareness of areas with significant depletion and large seasonal fluctuation of GWS help adaptations to manage local GWS situation.

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