scholarly journals Ocean-only FAFMIP: Understanding Regional Patterns of Ocean Heat Content and Dynamic Sea Level Change

Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Jonathan Gregory

<p>A rise in global mean sea level is a robust feature of projected anthropogenic climate change using state-of-the-art atmosphere-ocean general circulation models (AOGCMs). However, there is considerable disagreement over the more policy-relevant regional patterns of sea level rise. The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to improve our understanding of the mechanisms controlling regional and dynamic sea level change. In FAFMIP, identical air-sea buoyancy and momentum flux perturbations are applied to an ensemble of different AOGCMs, to sample the uncertainty associated with model structure and physical processes. Our novel implementation applies FAFMIP perturbations to an ensemble of OGCMs. This framework enables an estimate of the unknown atmosphere-ocean feedbacks, by comparing the coupled and ocean-only response to surface flux perturbations.</p><p>Comparing the response to idealised FAFMIP forcing with more realistic, increasing CO2 forcing, much of the spread in regional sea level projections for the North Atlantic and Southern Ocean arises from ocean model structural differences. Ocean-only simulations indicate that only a small proportion of this spread is due to differences in the atmosphere-ocean feedback. Novel tendency diagnostics indicate the relative effect of resolved advection, parametrised eddies, and dianeutral mixing on regional and dynamic sea level change. This study helps to reduce uncertainty in regional sea level projections by refining our estimates of atmosphere-ocean feedbacks and developing our understanding of the physical processes controlling sea level change.</p>

2020 ◽  
Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Matthew Couldrey ◽  
Jonathan M. Gregory ◽  
Quran Wu ◽  
...  

Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Matthew Couldrey ◽  
Jonathan Gregory ◽  
Quran Wu ◽  
...  

2007 ◽  
Vol 20 (24) ◽  
pp. 5889-5911 ◽  
Author(s):  
Carl Wunsch ◽  
Rui M. Ponte ◽  
Patrick Heimbach

Abstract Estimates of regional patterns of global sea level change are obtained from a 1° horizontal resolution general circulation model constrained by least squares to about 100 million ocean observations and many more meteorological estimates during the period 1993–2004. The data include not only altimetric variability, but most of the modern hydrography, Argo float profiles, sea surface temperature, and other observations. Spatial-mean trends in altimetric data are explicitly suppressed to isolate global average long-term changes required by the in situ data alone. On large scales, some regions display strong signals although few individual points have statistically significant trends. In the regional patterns, thermal, salinity, and mass redistribution contributions are all important, showing that regional sea level change is tied directly to the general circulation. Contributions below about 900 m are significant, but not dominant, and are expected to grow with time as the abyssal ocean shifts. Estimates made here produce a global mean of about 1.6 mm yr−1, or about 60% of the pure altimetric estimate, of which about 70% is from the addition of freshwater. Interannual global variations may be dominated by the freshwater changes rather than by heating changes. The widely quoted altimetric global average values may well be correct, but the accuracies being inferred in the literature are not testable by existing in situ observations. Useful estimation of the global averages is extremely difficult given the realities of space–time sampling and model approximations. Systematic errors are likely to dominate most estimates of global average change: published values and error bars should be used very cautiously.


2020 ◽  
Author(s):  
Bramha Dutt Vishwakarma ◽  
Sam Royston ◽  
Ricardo E. M. Riva ◽  
Richard M. Westaway ◽  
Jonathan L. Bamber

<p>The sea level budget (SLB) equates changes in sea surface height (SSH) to the sum of various geo-physical processes that contribute to sea level change. Currently, it is a common practice to explain a change in SSH as a sum of ocean mass and steric change, assuming that solid-Earth motion is corrected for and completely explained by secular visco-elastic relaxation of mantle, due to the process of glacial isostatic adjustment. Yet, since the Solid Earth also responds elastically to changes in present day mass load near the surface of the Earth, we can expect the ocean bottom to respond to ongoing ocean mass changes. This elastic ocean bottom deformation (OBD) has been ignored until very recently because the contribution of ocean mass to sea level rise was thought to be smaller than the steric contribution and the resulting OBD was within observation system uncertainties. However, ocean mass change has increased rapidly in the last 2 decades. Therefore, OBD is no longer negligible and recent studies have shown that its magnitude is similar to that of the deep steric sea level contribution: a global mean of about 0.1 mm/yr but regional changes at some places can be more than 10 times the global mean. Although now an important part of the SLB, especially for regional sea level, OBD is considered by only a few budget studies and they treat it as a spatially uniform correction. This is due to lack of a mathematical framework that defines the contribution of OBD to the SLB. Here, we use a mass-volume framework to derive, for the first time, a SLB equation that partitions SSH change into its component parts accurately and it includes OBD as a physical response of the Earth system. This updated SLB equation is important for various disciplines of Earth Sciences that use the SLB equation: as a constraint to assess the quality of observational time-series; as a means to quantify the importance of each component of sea level change; and, to adequately include all processes in global and regional sea level projections. We recommend using the updated SLB equation for sea level budget studies. We also revisit the contemporary SLB with the updated SLB equation using satellite altimetry data, GRACE data, and ARGO data.</p>


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jinping Wang ◽  
John A. Church ◽  
Xuebin Zhang ◽  
Xianyao Chen

AbstractThe ability of climate models to simulate 20th century global mean sea level (GMSL) and regional sea-level change has been demonstrated. However, the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) sea-level projections have not been rigorously evaluated with observed GMSL and coastal sea level from a global network of tide gauges as the short overlapping period (2007–2018) and natural variability make the detection of trends and accelerations challenging. Here, we critically evaluate these projections with satellite and tide-gauge observations. The observed trends from GMSL and the regional weighted mean at tide-gauge stations confirm the projections under three Representative Concentration Pathway (RCP) scenarios within 90% confidence level during 2007–2018. The central values of the observed GMSL (1993–2018) and regional weighted mean (1970–2018) accelerations are larger than projections for RCP2.6 and lie between (or even above) those for RCP4.5 and RCP8.5 over 2007–2032, but are not yet statistically different from any scenario. While the confirmation of the projection trends gives us confidence in current understanding of near future sea-level change, it leaves open questions concerning late 21st century non-linear accelerations from ice-sheet contributions.


2015 ◽  
Vol 120 (8) ◽  
pp. 5749-5765 ◽  
Author(s):  
Oleg A. Saenko ◽  
Duo Yang ◽  
Jonathan M. Gregory ◽  
Paul Spence ◽  
Paul G. Myers

2020 ◽  
Vol 58 (3) ◽  
Author(s):  
Benjamin D. Hamlington ◽  
Alex S. Gardner ◽  
Erik Ivins ◽  
Jan T. M. Lenaerts ◽  
J. T. Reager ◽  
...  

2018 ◽  
Vol 121 ◽  
pp. 139-146
Author(s):  
Lei He ◽  
◽  
Jilong Chen ◽  
Yue Zhang ◽  
Tengjiao Guo ◽  
...  

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