13 research outputs found
A commentary on “how to interpret expert judgment assessments of twenty-first century sea-level rise” by Hylke de Vries and Roderik SW van de Wal
No full textWe clarify key aspects of the evaluation, by de Vries and van de Wal (2015), of our expert elicitation paper on the contributions of ice sheet melting to sea level rise due to future global temperature rise scenarios (Bamber and Aspinall 2013), and extend the conversation with further analysis of their proposed approach for combining expert uncertainty judgments. We thank de Vries and van de Wal (2015: [VW15]) for their detailed consideration of Bamber and Aspinall (2013: [BA13]), and welcome this opportunity to clarify the work presented in BA13 and extend the analysis of VW15. The problem of finding a science-based quantification of uncertainty for poorly constrained physical models with large societal impacts deserves high priority in the climate community. This entails crossing discipline boundaries and will take that community outside its usual scientific comfort zone. We therefore salute the authors of VW13 for venturing into this alien terrain and welcome the opportunity to address some of the issues they raise. The present commentary discusses certain important and unique attributes of BA13’s expert weighting scheme that are misinterpreted in VW15, then addresses the Bconsensus distribution^ of VW15, their Blevel of consensus^, and the issue of lognormal fitting elicited data
Transient climate simulation of the past 4.5 million years based on the coupled intermediate complexity model iLOVECLIM
No full textThe Earth experienced dramatic climate changes during the past million years, including a long-term gradual cooling from the Pliocene (5.3-2.6 million years ago; Ma) to the Pleistocene (2.6-0.011 Ma) and an abrupt transition from 41-kyr to 100-kyr glacial-interglacial cycles at ca. 1.2-0.8 Ma (i.e., the Mid-Pleistocene transition). Investigating the mechanisms that triggered these climatic responses requires long-term transient climate simulations which can be used to quantify the sensitivity of the Earth&#8217;s climate to different external and internal forcings. However, few such simulations exist and therefore, key questions regarding the long-term evolution of the earth system remain unanswered.Here, we used iLOVECLIM, a coupled Earth system numerical climate model of intermediate complexity, to generate a 4.5 Ma transient climate simulation, the longest to date. iLOVECLIM is ideally suited for this task as it requires substantially less computational resources and time to perform transient climate simulations compared to fully coupled general circulation models. We performed the simulations with interactive atmosphere, ocean and vegetation components and used the methodology of previous long-term transient simulations. Briefly, we applied an acceleration factor of five to the external forcings (orbital parameters, greenhouse gases concentration and ice-sheets) and split the 4.5 Ma simulation into 44 chunks run in parallel to reduce the computing time from several years to a couple of months. Each chunk was initialized from an interglacial period, covers at least one glacial-interglacial cycle and has an overlap period of 20,000 years in order to compensate for issues related to spin-up effects and initial conditions. The complete simulation is a composite of all the individual chunks and time-sliding linear interpolation performed on the overlap intervals.While the simulations are still ongoing, preliminary results demonstrate that our new model set-up and experimental design are able to produce reasonable outputs. When it is completed, the final simulation will be evaluated against available paleoclimate data and existing transient climate simulations. Apart from running a simulation with all the external forcings combined, we also plan to run subsequent simulations with each individual forcing alone to evaluate the climate responses associated with each. This unique long transient simulation will provide a better mechanistic understanding of the major climate reorganizations that occurred during the Plio-Pleistocene and will be useful for future data-model comparisons and data assimilation endeavours.</jats:p
Reconstructing large scale differential subsidence in the Netherlands using a spatio-temporal 3D paleo-groundwater level interpolation
No full textSubsidence is a land use problem in the western and northern Netherlands, especially where both shallow soft soil subsidence and deeper subsidence components, including glacio-isostatic adjustment (GIA), add up. The aim of this study is to improve the estimation of the GIA component within the total subsidence signal across the Netherlands during the Holocene, using coastal plain paleo-water level markers. Throughout the Holocene, the GIA induced subsidence in the Netherlands has been spatially and temporally variant, as shown by previous studies that used GIA modelling and geological relative sea-level rise reconstructions. From the latter work, many field data points are available based on radiocarbon dated coastal basal peats of different age and vertical position. These reveal Holocene relative sea-level rise to have been strongest in the Wadden Sea in the Northern Netherlands. This matches post-glacial GIA subsidence (forebulge collapse) as modelled for the Southern North Sea, being located in the near-field of Scandinavian and British former ice masses. In this study, geological data analysis of RSL and other paleo-water level data available from the Dutch coastal plain for the Holocene period is considered in addition. The analysis takes the form of designing and executing a 3D interpolation (kriging with a trend: KT), where paleo-water level Z(x,y,age) is predicted and the field-data points are the observations (Age, X, Y and Z as knowns). We use a spatio-temporal 3D grid that covers the Dutch coastal plain, and reproduces and unifies earlier constructed sea level curves and high-resolution sampled individual sites (e.g. Rotterdam). The function describing the trend part of the interpolation separates linear and non-linear components of relative water level rise, i.e.: long-term background subsidence and shorter-term GIA subsidence signal and postglacial water level rise. The kriging part then processes remaining subregional patterns. The combined reconstruction thus yields a spatially continuous parameterization of regional trends that (i) allows to separate subsidence from water level rise terms, and (ii) is produced independently of GIA modelling to enable cross-comparison. Results are presented for the coastal plain of the Netherlands ([SW] Zeeland – Rotterdam – Holland – Wadden Sea – Groningen [NE]). The percentage of the total coastal-prism accommodation space that appears due to subsidence, from the south to the north of the study area increases by 20%. Holocene-averaged subsidence rates from the first analysis ranged from ca. 0.1 m/kyr (Zeeland) to 0.4 m/kyr (Groningen), which is 5-10 times larger than present-day GPS/GNSS-measured rates
Dataset for "The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6"
No full textThis data set provides processed model output of ISMIP6 Greenland projections as documented and analysed in the following publication:
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319
About the data:
- The results are based on model output regridded conservatively to a 5x5 km regular ISMIP6 grid unless this is already the native grid.
- The results are calculated over the ice-covered area of Greenland, map projection error corrected, ice sheet model specific densities taken into account.
- The contribution of peripheral glaciers and ice caps has been removed, by considering their area-coverage in each grid cell.
- The results for the projections 'exp*' are all calculated as differences to the control experiment ctrl_proj (suffix cr in filename for control removed).
- Results for ctrl_proj and historical are un-corrected (no suffix cr in filename).
Directory structure:
versionid
groupname1
modelname1
expid
scalars_mm_cr_GIS_groupname1_modelname1_expid.nc
scalars_rm_cr_GIS_groupname1_modelname1_expid.nc
scalars_zm_cr_GIS_groupname1_modelname1_expid.nc
...
Variables per file:
scalars_mm_cr_GIS ----------------- Greenland wide numbers
oarea - assumed ocean area [m2]
rhof - model specific freshwater density [kg m-3]
rhoi - model specific ice density [kg m-3]
rhow - model specific ocean water density [kg m-3]
time - time, typically in days since X
iarea - Fraction of grid cell covered by land ice [1]
iareagr - Fraction of grid cell covered by grounded ice sheet
iareafl - Fraction of grid cell covered by ice sheet flowing over seawater
ivol - ice volume [m3]
ivolgr - grounded ice volume [m3]
ivolfl - floating ice volume [m3]
ivaf - ice volume above flotation [m3]
lim - ice mass [kg]
limgr - grounded ice mass [kg]
limfl - floating ice mass [kg]
limaf - ice mass above flotation [kg]
sle - sea-level equivalent mass [m] !! decreases with mass loss !!
smb - spatially integrated surface mass balance anomaly [kg s-1]
scalars_rm_cr_GIS ----------------- IMBIE2-Rignot basins xx=[no,ne,se,sw,cw,nw]
oarea - assumed ocean area [m2]
rhof - model specific freshwater density [kg m-3]
rhoi - model specific ice density [kg m-3]
rhow - model specific ocean water density [kg m-3]
time - time, typically in days since X
ivaf_xx - ice volume above flotation [m3]
smb_xx - spatially integrated surface mass balance anomaly [kg s-1]
limaf_xx - ice mass above flotation [kg]
sle_xx - sea-level equivalent mass [m] !! decreases with mass loss !!
scalars_zm_cr_GIS ----------------- IMBIE2-Zwally basins xx=[z11,z12,z13,z14,z21,z22,z31,z32,z33,z41,z42,z43,z50,z61,z62,z71,z72,z81,z82]
oarea - assumed ocean area [m2]
rhof - model specific freshwater density [kg m-3]
rhoi - model specific ice density [kg m-3]
rhow - model specific ocean water density [kg m-3]
time - time, typically in days since X
ivaf_xx - ice volume above flotation [m3]
smb_xx - spatially integrated surface mass balance anomaly [kg s-1]
limaf_xx - ice mass above flotation [kg]
sle_xx - sea-level equivalent mass [m] !! decreases with mass loss !!
Data usage notice:
If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below.
“We thank the Climate and Cryosphere (CliC) effort, which provided support for ISMIP6 through sponsoring of workshops, hosting the ISMIP6 website and wiki, and promoted ISMIP6. We acknowledge the World Climate Research Programme, which, through it's Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6."
You should also refer to and cite the following papers:
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319
Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020
Reconstructing large scale differential subsidence in the Netherlands using a spatio-temporal 3D paleo-groundwater level interpolation
No full textSubsidence is a land use problem in the western and northern Netherlands, especially where both shallow soft soil subsidence and deeper subsidence components, including glacio-isostatic adjustment (GIA), add up. The aim of this study is to improve the estimation of the GIA component within the total subsidence signal across the Netherlands during the Holocene, using coastal plain paleo-water level markers. Throughout the Holocene, the GIA induced subsidence in the Netherlands has been spatially and temporally variant, as shown by previous studies that used GIA modelling and geological relative sea-level rise reconstructions. From the latter work, many field data points are available based on radiocarbon dated coastal basal peats of different age and vertical position. These reveal Holocene relative sea-level rise to have been strongest in the Wadden Sea in the Northern Netherlands. This matches post-glacial GIA subsidence (forebulge collapse) as modelled for the Southern North Sea, being located in the near-field of Scandinavian and British former ice masses. In this study, geological data analysis of RSL and other paleo-water level data available from the Dutch coastal plain for the Holocene period is considered in addition. The analysis takes the form of designing and executing a 3D interpolation (kriging with a trend: KT), where paleo-water level Z(x,y,age) is predicted and the field-data points are the observations (Age, X, Y and Z as knowns). We use a spatio-temporal 3D grid that covers the Dutch coastal plain, and reproduces and unifies earlier constructed sea level curves and high-resolution sampled individual sites (e.g. Rotterdam). The function describing the trend part of the interpolation separates linear and non-linear components of relative water level rise, i.e.: long-term background subsidence and shorter-term GIA subsidence signal and postglacial water level rise. The kriging part then processes remaining subregional patterns. The combined reconstruction thus yields a spatially continuous parameterization of regional trends that (i) allows to separate subsidence from water level rise terms, and (ii) is produced independently of GIA modelling to enable cross-comparison. Results are presented for the coastal plain of the Netherlands ([SW] Zeeland – Rotterdam – Holland – Wadden Sea – Groningen [NE]). The percentage of the total coastal-prism accommodation space that appears due to subsidence, from the south to the north of the study area increases by 20%. Holocene-averaged subsidence rates from the first analysis ranged from ca. 0.1 m/kyr (Zeeland) to 0.4 m/kyr (Groningen), which is 5-10 times larger than present-day GPS/GNSS-measured rates
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Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes
No full textUncertainties in Representative Concentration Pathway (RCP) scenarios and Antarctic Ice Sheet (AIS) melt propagate into uncertainties in projected mean sea-level (MSL) changes and extreme sea-level (ESL) events. Here we quantify the impact of RCP scenarios and AIS contributions on 21st-century ESL changes at tide-gauge sites across the globe using extreme-value statistics. We find that even under RCP2.6, almost half of the sites could be exposed annually to a present-day 100-year ESL event by 2050. Most tropical sites face large increases in ESL events earlier and for scenarios with smaller MSL changes than extratropical sites. Strong emission reductions lower the probability of large ESL changes but due to AIS uncertainties, cannot fully eliminate the probability that large increases in frequencies of ESL events will occur. Under RCP8.5 and rapid AIS mass loss, many tropical sites, including low-lying islands face a MSL rise by 2100 that exceeds the present-day 100-year event level
Antarctic ice sheet response to sudden and sustained ice-shelf collapse (ABUMIP)
No full textAbstract Antarctica's ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their ‘buttressing’ effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttressing by investigating the ‘end-member’ scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1–12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91–5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong function of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
Projecting Antarctica's contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)
No full textThe sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4 mm of global sea level rise, with a standard deviation of 3.7 mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 ∘C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles. We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade
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Lessons on climate sensitivity from past climate changes
No full textOver the last decade, our understanding of climate sensitivity has improved considerably. The climate system shows variability on many timescales, is subject to non-stationary forcing and it is most likely out of equilibrium with the changes in the radiative forcing. Slow and fast feedbacks complicate the interpretation of geological records as feedback strengths vary over time. In the geological past, the forcing timescales were different than at present, suggesting that the response may have behaved differently. Do these insights constrain the climate sensitivity relevant for the present day? In this paper, we review the progress made in theoretical understanding of climate sensitivity and on the estimation of climate sensitivity from proxy records. Particular focus lies on the background state dependence of feedback processes and on the impact of tipping points on the climate system. We suggest how to further use palaeo data to advance our understanding of the currently ongoing climate change
