scholarly journals Decadal Trends in Sea Level Patterns: 1993–2004

2007 ◽  
Vol 20 (24) ◽  
pp. 5889-5911 ◽  
Author(s):  
Carl Wunsch ◽  
Rui M. Ponte ◽  
Patrick Heimbach
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Level Change ◽  
Horizontal Resolution ◽  
Regional Patterns ◽  
Global Average ◽  
Level Change ◽  
In Situ Data

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.

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

2020 ◽  
Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Jonathan Gregory
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Heat Content ◽  
Sea Level Change ◽  
General Circulation Models ◽  
Physical Processes ◽  
Regional Patterns ◽  
Level Change ◽  
Regional Sea Level ◽  
Dynamic Sea Level

<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>

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

2020 ◽  
Author(s):  
Alexander Todd ◽  
Laure Zanna ◽  
Matthew Couldrey ◽  
Jonathan M. Gregory ◽  
Quran Wu ◽  
...  
Keyword(s):  
Sea Level ◽  
Heat Content ◽  
Sea Level Change ◽  
Ocean Heat Content ◽  
Regional Patterns ◽  
Level Change ◽  
Dynamic Sea Level

scholarly journals Comparing tide gauge observations to regional patterns of sea-level change (1961–2003)

2014 ◽  
Vol 5 (1) ◽  
pp. 169-201 ◽  
Author(s):  
A. B. A. Slangen ◽  
R. S. W. van de Wal ◽  
Y. Wada ◽  
L. L. A. Vermeersen
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Linear Trend ◽  
Regional Scale ◽  
Sea Level Change ◽  
Small Scale ◽  
Regional Patterns ◽  
Dynamic Component ◽  
Uncertainty Range ◽  
Level Change

Abstract. Although the global mean sea-level budget for the 20th century can now be closed, the understanding of sea-level change on a regional scale is still limited. In this study we compare observations from tide gauges to regional patterns from various contributions to sea-level change to see how much of the regional measurements can be explained. Processes that are included are land ice mass changes and terrestrial storage changes with associated gravitational, rotational and deformational effects, steric/dynamic changes, atmospheric pressure loading and Glacial Isostatic Adjustment (GIA). The study focuses on the mean linear trend between 1961 and 2003. It is found that on a regional level the explained variance of the observed trend is 0.87 with a regression coefficient of 1.08. The observations and models overlap within the 1σ uncertainty range in all regions. The leading processes in explaining the variability in the observations appear to be the steric/dynamic component and the GIA. Local observations prove to be more difficult to explain because they show larger spatial variations, and therefore require more information on small-scale processes.

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data

2006 ◽  
Vol 19 (2) ◽  
pp. 153-192 ◽  
Author(s):  
Gavin A. Schmidt ◽  
Reto Ruedy ◽  
James E. Hansen ◽  
Igor Aleinov ◽  
Nadine Bell ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Full Description ◽  
Marine Stratocumulus ◽  
Sea Level Pressure ◽  
In Situ Data ◽  
Basic Physics ◽  
Goddard Institute

Abstract A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

Coastal Sea Level Change from in the North Eastern Atlantic

2020 ◽  
Author(s):  
Luciana Fenoglio-Marc ◽  
Bernd Uebbing ◽  
Jürgen Kusche ◽  
Salvatore Dinardo
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Level Change ◽  
Altimeter Data ◽  
Level Change ◽  
The North ◽  
North Eastern ◽  
Coastal Sea

<p>A significant part of the World population lives in the coastal zone, which is affected by coastal sea level rise and extreme events. Our hypothesis is that the most accurate sea level height measurements are derived from the Synthetic Aperture Altimetry (SAR) mode. This study analyses the output of dedicated processing and assesses their impacts on the sea level change of the North-Eastern Atlantic. </p><p>It will be shown that SAR altimetry reduces the minimum usable distance from five to three kilometres when the dedicated coastal retrackers SAMOSA+ and SAMOSA++ are applied to data processed in SAR mode. A similar performance is achieved with altimeter data processed in pseudo low resolution mode (PLRM) when the Spatio-Temporal Altimeter sub-waveform Retracker (STAR) is used. Instead the Adaptive Leading Edge Sub-waveform retracker (TALES) applied to PLRM is less performant. SAR processed altimetry can recover the sea level heights with 4 cm accuracy up to 3-4 km distance to coast. Thanks to the low noise of SAR mode data, the instantaneous SAR and in-situ data have the highest agreement, with the smallest standard deviation of differences and the highest correlation. A co-location of the altimeter data near the tide gauge is the best choice for merging in-situ and altimeter data. The r.m.s. (root mean squared) differences between altimetry and in-situ heights remain large in estuaries and in coastal zone with high tidal regimes, which are still challenging regions. The geophysical parameters derived from CryoSat-2 and Sentinel-3A measurements have similar accuracy, but the different repeat cycle of the two missions locally affects the constructed time-series.</p><p>The impact of these new SAR observations in climate change studies is assessed by evaluating regional and local time series of sea level. At distances to coast smaller than 10 Kilometers the sea level change derived from SAR and LRM data is in good agreement. The long-term sea level variability derived from monthly time-series of LRM altimetry and of land motion-corrected tide gauges agrees within 1 mm/yr for half of in-situ German stations. The long-term sea level variability derived from SAR data show a similar behaviour with increasing length of the time series.</p><p> </p>

scholarly journals Comparing tide gauge observations to regional patterns of sea-level change (1961–2003)

2014 ◽  
Vol 5 (1) ◽  
pp. 243-255 ◽  
Author(s):  
A. B. A. Slangen ◽  
R. S. W. van de Wal ◽  
Y. Wada ◽  
L. L. A. Vermeersen
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Linear Trend ◽  
Regional Scale ◽  
Sea Level Change ◽  
Small Scale ◽  
Regional Patterns ◽  
Dynamic Component ◽  
Uncertainty Range ◽  
Level Change

Abstract. Although the global mean sea-level budget for the 20th century can now be closed, the understanding of sea-level change on a regional scale is still limited. In this study we compare observations from tide gauges to regional patterns from various contributions to sea-level change to see how much of the regional measurements can be explained. Processes that are included are land ice mass changes and terrestrial storage changes with associated gravitational, rotational and deformational effects, steric/dynamic changes, atmospheric pressure loading and glacial isostatic adjustment (GIA). The study focuses on the mean linear trend of regional sea-level rise between 1961 and 2003. It is found that on a regional level the explained variance of the observed trend is 0.87 with a regression coefficient of 1.07. The observations and models overlap within the 1σ uncertainty range in all regions. The main processes explaining the variability in the observations appear to be the steric/dynamic component and the GIA. Local observations prove to be more difficult to explain because they show larger spatial variations, and therefore require more information on small-scale processes.

scholarly journals Past and future sea-level change from the surface mass balance of glaciers

2012 ◽  
Vol 6 (6) ◽  
pp. 1295-1322 ◽  
Author(s):  
B. Marzeion ◽  
A. H. Jarosch ◽  
M. Hofer
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Sea Level ◽  
General Circulation ◽  
Sea Level Change ◽  
Surface Mass Balance ◽  
Monthly Precipitation ◽  
Surface Mass ◽  
Level Change ◽  
The World

Abstract. We present estimates of sea-level change caused by the global surface mass balance of glaciers, based on the reconstruction and projection of the surface mass balance of all the individual glaciers of the world, excluding the ice sheets in Greenland and Antarctica. The model is validated using a leave-one-glacier-out cross-validation scheme against 3997 observed surface mass balances of 255 glaciers, and against 756 geodetically observed, temporally integrated volume and surface area changes of 341 glaciers. When forced with observed monthly precipitation and temperature data, the glaciers of the world are reconstructed to have lost mass corresponding to 114 ± 5 mm sea-level equivalent (SLE) between 1902 and 2009. Using projected temperature and precipitation anomalies from 15 coupled general circulation models from the Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble, they are projected to lose an additional 148 ± 35 mm SLE (scenario RCP26), 166 ± 42 mm SLE (scenario RCP45), 175 ± 40 mm SLE (scenario RCP60), or 217 ± 47 mm SLE (scenario RCP85) during the 21st century. Based on the extended RCP scenarios, glaciers are projected to approach a new equilibrium towards the end of the 23rd century, after having lost either 248 ± 66 mm SLE (scenario RCP26), 313 ± 50 mm SLE (scenario RCP45), or 424 ± 46 mm SLE (scenario RCP85). Up until approximately 2100, ensemble uncertainty within each scenario is the biggest source of uncertainty for the future glacier mass loss; after that, the difference between the scenarios takes over as the biggest source of uncertainty. Ice mass loss rates are projected to peak 2040 ∼ 2050 (RCP26), 2050 ∼ 2060 (RCP45), 2070 ∼ 2090 (RCP60), or 2070 ∼ 2100 (RCP85).

scholarly journals Estimating the contribution of Arctic glaciers to sea-level change in the next 100 years

2005 ◽  
Vol 42 ◽  
pp. 230-236 ◽  
Author(s):  
J. Oerlemans ◽  
R.P. Bassford ◽  
W. Chapman ◽  
J.A. Dowdeswell ◽  
A.F. Glazovsky ◽  
...  
Keyword(s):  
Sea Level ◽  
Climate Models ◽  
Ice Sheet ◽  
Canadian Arctic ◽  
Greenland Ice Sheet ◽  
Sea Level Change ◽  
The Arctic ◽  
Climate Change Scenarios ◽  
Regional Patterns ◽  
Level Change

AbstractIn this paper, we report on an approach to estimate the contribution of Arctic glaciers to sea-level change. In our calculation we assume that a static approach is feasible. We only calculate changes in the surface balance from modelled sensitivities. These sensitivities, summarized in the seasonal sensitivity characteristic, can be used to calculate the change in the surface mass budget for given anomalies of monthly temperature and precipitation. We have based our calculations on a subdivision of all Arctic ice into 13 regions: four sectors of the Greenland ice sheet; the Canadian Arctic >74˚N; the Canadian Arctic <74˚N; Alaska, USA; Iceland; Svalbard; Zemlya Frantsa Iosifa, Russia; Novaya Zemlya, Russia; Severnaya Zemlya, Russia; and Norway/Sweden >60˚N. As forcing for the calculations, we have used the output from five climate models, for the period 2000–2100. These models were forced by the same greenhouse-gas scenario (IPCC-B2). The calculated contributions to sea-level rise in the year 2100 vary from almost zero to about 6 cm. The differences among the models stem first of all from differences in the precipitation. The largest contribution to sea-level change comes from the Greenland ice sheet. The glaciers in Alaska also make a large contribution, not because of the area they cover, but because they are more sensitive than other glaciers in the Arctic. The climate models do not agree on regional patterns. The runoff from Svalbard glaciers, for instance, increases for two models and decreases for the three other models. We conclude that the uncertainty due to a simple representation of the glaciological processes is probably smaller than the uncertainty induced by the differences in the climate-change scenarios produced by the models.

Sign in / Sign up

Export Citation Format

Share Document