scholarly journals Time Variations in Ocean Bottom Pressure from a Few Hours to Many Years: In Situ Data, Numerical Models, and GRACE Satellite Gravimetry

2018 ◽  
Vol 123 (8) ◽  
pp. 5612-5623 ◽  
Author(s):  
L. Poropat ◽  
H. Dobslaw ◽  
L. Zhang ◽  
A. Macrander ◽  
O. Boebel ◽  
...  
Keyword(s):  
Numerical Models ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Ocean Bottom Pressure ◽  
Satellite Gravimetry ◽  
In Situ Data ◽  
Grace Satellite Gravimetry ◽  
Time Variations ◽  
Grace Satellite

Monitoring the AMOC with GRACE/GRACE-FO - How far can we push the spatial resolution?

2020 ◽  
Author(s):  
Andreas Kvas ◽  
Katrin Bentel ◽  
Saniya Behzadpour ◽  
Torsten Mayer-Gürr
Keyword(s):  
Atlantic Ocean ◽  
Ocean Basin ◽  
Meridional Overturning Circulation ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Ocean Bottom Pressure ◽  
Satellite Gravimetry ◽  
Continental Hydrology ◽  
Geocenter Motion

<p>The Atlantic Meridional Overturning Circulation (AMOC) plays a key role in our global climate system and is the main mechanism of northward heat transport for a warm climate in Northern Europe. Despite its crucial role, the AMOC is only scarcely observed, as observations covering all of the Atlantic Ocean for extended time are difficult to obtain. Satellite gravimetry offers key advantages compared to existing in-situ data sources by providing ocean bottom pressure anomalies with global coverage, thus allowing the monitoring of the AMOC in the complete Atlantic Ocean basin. The Gravity Recovery And Climate Experiment (GRACE) satellite mission and its successor GRACE Follow-On have provided a nearly continuous time series of monthly gravity field snapshots since 2002. In contrast to in-situ measurements of ocean bottom pressure, which suffer from inherent drift problems, the temporally stable satellite observations allow investigations of the long-term AMOC behavior.</p><p>Preliminary studies have shown that monitoring changes in the AMOC is possible with observations from GRACE and GRACE Follow-On, however, it is pushing the limits of the current data products in resolution and accuracy. To fully exploit the information content in the gravity observations, we implemented a processing chain tailored to the Atlantic Ocean basin. Compared to existing approaches, we perform signal separation, that is the reduction of continental hydrology and glacial isostatic adjustment, on the satellite sensor data level. This has the key advantage that all background models are treated the same, thus are spectrally coherent. Geocenter motion is estimated in combination with an ocean model, as is the state-of-the-art for GRACE/GRACE-FO processing. Ocean bottom pressure anomalies are then computed through least squares collocation, which allows for point distributions tailored to the bathymetry. This consistently processed data record is then used to gauge the performance of satellite gravimetry for monitoring the AMOC.</p>

scholarly journals Ocean bottom pressure signals around Southern Africa from in situ measurements, satellite data, and modeling

2013 ◽  
Vol 118 (10) ◽  
pp. 4889-4898 ◽  
Author(s):  
Julian Kuhlmann ◽  
Henryk Dobslaw ◽  
Christof Petrick ◽  
Maik Thomas
Keyword(s):  
Satellite Data ◽  
Southern Africa ◽  
In Situ Measurements ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Ocean Bottom Pressure

Evaluation of GRACE RL06 analysis in the Southern Ocean

2021 ◽  
Author(s):  
Jens Schröter ◽  
Alexey Androsov ◽  
Christina Lück ◽  
Bernd Übbing ◽  
Roelof Rietbroek ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Mean Values ◽  
Annual Cycles ◽  
Ocean Bottom Pressure ◽  
Temporal Features ◽  
Depth Analysis ◽  
Circumpolar Current

<p>Space geodetic estimates of ocean bottom pressure (OBP) derived by several analysis centres are evaluated. To this end, an array of 14 in situ bottom pressure recorders has been deployed between South Africa and Antarctica. The continuous measurement period of four years (2011 to 2014) and a recorder spacing of roughly 2.8 degrees latitude allows an in-depth analysis of bottom pressure variability.</p><p>Our goal is to relate OBP from GRACE to in situ observations and detect which spatial and temporal features are reproduced. The recorders in the southern part of the transect generally tend to be in better agreement with GRACE and better reflect longer spatial scales of ocean bottom pressure. Over the vast expanse of the Antarctic Circumpolar Current annual and semi-annual cycles are weak (about 1cm equivalent water height (EWH)) and not reproduced well by GRACE. Variability in general amounts to a standard deviation of 2cm. This level is well captured and correlations on the order of 0.5 are found.</p><p>Mean values and trends of OBP cannot be identified due to the instrumental setup. Close to the Agulhas Retroflection, signals of up to 30cm EWH are found, which cannot be resolved by GRACE. Our  analysis reveals: GRACE OBP possesses longer space and time scales than in situ OBP and it misses eddy-scale signals. Filtering with DDK4 appears to be preferable to DDK6.</p><p> </p>

Consistency of observed sea surface height changes, bottom pressure changes and temperature, salinity variations in a South Atlantic transect of the Antarctic Circumpolar Current

2020 ◽  
Author(s):  
Alisa Yakhontova ◽  
Roelof Rietbroek ◽  
Jens Schröter ◽  
Nadja Jonas ◽  
Christina Lück ◽  
...  
Keyword(s):  
Antarctic Circumpolar Current ◽  
Sea Surface Height ◽  
South Atlantic ◽  
Sea Surface ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Satellite Gravimetry ◽  
Circumpolar Current ◽  
The Antarctic

<p>Improved estimates of temperature, salinity, and sea surface height changes are computed from radar altimetry, satellite gravimetry and Argo profiles, and validated by the in situ ocean bottom pressure measurements in a South Atlantic transect of the Antarctic Circumpolar current. Using satellite gravimetry and altimetry observations, separate contributions to the global sea level can be estimated, but a regional solution is more challenging. Furthermore, Argo derived steric sea level change suffers from spatio-temporal sampling problems, and some signals are not well captured, e.g. in the deeper ocean below 2000m, around the boundary currents, in the Arctic or in the shelf/coastal regions. Jointly processing radar altimetry, Argo and data from the Gravity Recovery and Climate Experiment (GRACE), would allow to correct the deficiencies of the individual datasets, and produce observation based estimates of consistent temperature, salinity and sea surface height changes. In order to pave the way for an advanced joint inversion scheme that additionally resolves for temperature and salinity, the observation equations are formulated which link the satellite observations to temperature and salinity at depth. Observations in the South Atlantic region are compared with simulations from the FESOM model in terms of variability and the model data is used to find the spatial coherence of the signals at the sites with the surrounding ocean. The experiment is performed in the Southern Atlantic Ocean, where the estimates can be validated using an array of in situ ocean bottom pressure observations.</p>

scholarly journals Validation of the EGSIEM GRACE Gravity Fields Using GNSS Coordinate Timeseries and In-Situ Ocean Bottom Pressure Records

2018 ◽  
Vol 10 (12) ◽  
pp. 1976 ◽  
Author(s):  
Qiang Chen ◽  
Lea Poropat ◽  
Liangjing Zhang ◽  
Henryk Dobslaw ◽  
Matthias Weigelt ◽  
...  
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Ocean Bottom Pressure ◽  
Global Gravity ◽  
Gravity Fields ◽  
Global Navigation Satellite

Over the 15 years of the Gravity Recovery and Climate Experiment (GRACE) mission, various data processing approaches were developed to derive time-series of global gravity fields based on sensor observations acquired from the two spacecrafts. In this paper, we compare GRACE-based mass anomalies provided by various processing groups against Global Navigation Satellite System (GNSS) station coordinate time-series and in-situ observations of ocean bottom pressure. In addition to the conventional GRACE-based global geopotential models from the main processing centers, we focus particularly on combined gravity field solutions generated within the Horizon2020 project European Gravity Service for Improved Emergency Management (EGSIEM). Although two validation techniques are fully independent from each other, it is demonstrated that they confirm each other to a large extent. Through the validation, we show that the EGSIEM combined long-term monthly solutions are comparable to CSR RL05 and ITSG2016, and better than the other three considered GRACE monthly solutions AIUB RL02, GFZ RL05a, and JPL RL05.1. Depending on the GNSS products, up to 25.6% mean Weighted Root-Mean-Square (WRMS) reduction is obtained when comparing GRACE to the ITRF2014 residuals over 236 GNSS stations. In addition, we also observe remarkable agreement at the annual period between GNSS and GRACE with up to 73% median WRMS reduction when comparing GRACE to the 312 EGSIEM-reprocessed GNSS time series. While the correspondence between GRACE and ocean bottom pressure data is overall much smaller due to lower signal to noise ratio over the oceans than over the continents, up to 50% agreement is found between them in some regions. The results fully confirm the conclusions found using GNSS.

Arctic Ocean bottom pressure variations from 2002 to 2020: merging GRACE with GRACE-FO

2020 ◽  
Author(s):  
Cecilia Peralta-Ferriz ◽  
James Morison ◽  
Jennifer Bonin
Keyword(s):  
Time Series ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
Ocean Bottom ◽  
Bottom Pressure ◽  
Ocean Bottom Pressure ◽  
The North ◽  
Circulation Patterns ◽  
Arctic Ocean Circulation

<p>Ocean bottom pressure (OBP) from the Gravity Recovery and Climate Experiment (GRACE) revealed Arctic Ocean circulation patterns and variability that were previously unknown (Morison et al., 2007; Morison et al., 2012; Peralta-Ferriz et al., 2014). OBP measurements from the GRACE Follow-On mission (GRACE-FO) are therefore increasingly important for monitoring Arctic Ocean variability, and critical for understanding and predicting the fate of the rapidly changing Arctic environment.</p> <p>In this work we use GRACE data from 2002 to 2017 jointly with a 10-year record of <em>in situ</em> OBP at the North Pole (2005-2015) complemented with <em>in situ</em> OBP in the Canada Basin (2015-2018), and wind reanalysis products, to create a proxy representation of the OBP anomalies that explains the largest possible fraction of the observed OBP variability in the Arctic Ocean and the Nordic Seas. We do this by performing a linear regression analysis, combined with maximum covariance analysis (MCA) – a technique that was tested prior to the decommission of GRACE and the launch of GRACE-FO (Peralta-Ferriz et al., 2016). Here, the first predictor time series is the <em>in situ</em> OBP record at the North Pole and Canada Basin; the second predictor time series is the expansion coefficients time series of the leading mode of MCA between the GRACE OBP coupled with the winds. We use this proxy OBP to merge GRACE with the first 2 years of available GRACE-FO OBP. We compare our merged OBP field with OBP output from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Preliminary results suggest a good agreement between the proxy and predicted OBP fields and both GRACE and GRACE-FO data, especially in the central Arctic, but also in the Nordic Seas. The OBP variations from the merged GRACE and GRACE-FO and from PIOMAS will be also explored.</p> <p><strong>References:</strong></p> <ul> <li>Morison, J. H., J. Wahr, R. Kwok and C. Peralta-Ferriz (2007), Recent trends in Arctic Ocean mass distribution revealed by GRACE, Res. Lett.,34, L07602, doi:10.1029/2006GL029016.</li> <li>Morison, J., R. Kwok, C. Peralta-Ferriz, M. Alkire, I. Rigor, R. Andersen and M. Steele (2012), Changing Arctic Ocean freshwater pathways. Nature, 481, 66-7</li> <li>Peralta-Ferriz, C., J. H. Morison, J. M. Wallace, J. Bonin and J. Zhang (2014), Arctic Ocean circulation patterns revealed by GRACE, of Climate, 27:1445–1468 doi:10.1175/JCLI-D-13-00013.1.</li> <li>Peralta-Ferriz, C., J. H. Morison and J. M. Wallace(2016), Proxy representation of Arctic ocean bottom pressure variability: Bridging gaps in GRACE observations,  Res. Lett., 43, 9183–9191, doi:10.1002/2016GL070137</li> </ul>

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