Feasibility, and Contribution to Ocean Circulation Studies, of Ocean Bottom Pressure Determination

Author(s):  
Chris W. Hughes ◽  
Vladimir Stepanov
2020 ◽  
Author(s):  
Cecilia Peralta-Ferriz ◽  
James Morison ◽  
Jennifer Bonin

<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>


2020 ◽  
Author(s):  
Volker Klemann ◽  
Henryk Dobslaw ◽  
Meike Bagge ◽  
Robert Dill ◽  
Maik Thomas ◽  
...  

<p>Temporal variations in the total ocean mass representing the barystatic part of present-day global mean sea-level rise can be unambiguously inferred from time-series of global gravity fields as provided by the GRACE and GRACE-FO missions. A spatial integration over all ocean regions, however, largely underestimates present-day rates as long as the effects of spatial leakage along the coasts of in particular Antarctica, Greenland, and the various islands of the Canadian Archipelago are not properly considered.</p><p>Based on the recent release 06 of monthly gravity fields processed at GFZ, we quantify (and subsequently correct) the contribution of spatial leakage to the post-processed mass anomalies of continental water storage and ocean bottom pressure. Utilising the sea level equation allows to predict spatially variable ocean mass trends out of the (leakage-corrected) terrestrial mass distributions from GRACE and GRACE-FO. Consistent results for the global mean barystatic sea-level rise are obtained also from spatial integrations over ocean masks with different coastal buffer zones ranging from 400 to 1000 km, thereby confirming the robustness of our method. Residual month-to-month variations in ocean bottom pressure are indicative for errors in the monthly-mean estimates of the applied de-aliasing model AOD1B RL06 and will be thus contrasted against very recent MPIOM experiments considered for AOD1B RL07. The in this way improved leakage correction will be implemented in future GravIS versions (http://gravis.gfz-potsdam.de).</p>


2021 ◽  
Vol 13 (7) ◽  
pp. 1242
Author(s):  
Hakan S. Kutoglu ◽  
Kazimierz Becek

The Mediterranean Ridge accretionary complex (MAC) is a product of the convergence of Africa–Europe–Aegean plates. As a result, the region exhibits a continuous mass change (horizontal/vertical movements) that generates earthquakes. Over the last 50 years, approximately 430 earthquakes with M ≥ 5, including 36 M ≥ 6 earthquakes, have been recorded in the region. This study aims to link the ocean bottom deformations manifested through ocean bottom pressure variations with the earthquakes’ time series. To this end, we investigated the time series of the ocean bottom pressure (OBP) anomalies derived from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite missions. The OBP time series comprises a decreasing trend in addition to 1.02, 1.52, 4.27, and 10.66-year periodic components, which can be explained by atmosphere, oceans, and hydrosphere (AOH) processes, the Earth’s pole movement, solar activity, and core–mantle coupling. It can be inferred from the results that the OBP anomalies time series/mass change is linked to a rising trend and periods in the earthquakes’ energy time series. Based on this preliminary work, ocean-bottom pressure variation appears to be a promising lead for further research.


Author(s):  
Hiroaki Tsushima ◽  
Ryota Hino ◽  
Hiromi Fujimoto ◽  
Yuichiro Tanioka ◽  
Fumihiko Imamura

2019 ◽  
Vol 46 (1) ◽  
pp. 303-310 ◽  
Author(s):  
Tomoya Muramoto ◽  
Yoshihiro Ito ◽  
Daisuke Inazu ◽  
Laura M. Wallace ◽  
Ryota Hino ◽  
...  

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