For a fuller description of the paper itself, go to the end of this web page.
Each simulation published in this paper corresponds to a unique 5 or 6 character code on the web pages.
The following table lists the name of the simulation as used in the paper, and the corresponding code name
The webpage gives you the ability to examine the published simulations, but you can also download the raw (netcdf) files to perform your own analysis. Detailed instructions on how to use the webpages and access the data can be found here: Using_BRIDGE_webpages.pdf
There are a lot of simulations going into this paper but they are grouped around two sequences, one using orbital and greenhouse gas forcing and the second also including ice sheets and land sea changes.
You can have make you own analysis and plots by going here
| Simulation Name as in Paper | Simulation name on web pages |
|---|---|
| Pre-Industrial HadCM3 control simulation | tcnpd |
| 130ka, modern Greenland ice sheet | tctaa |
| 130ka, partial Greenland ice sheet | tctao |
| 130ka, no Greenland ice sheet | tctae |
| 125ka, modern Greenland ice sheet | tctam |
| 125ka, partial Greenland ice sheet | tctap |
| 125ka, no Greenland ice sheet | tctan |
| 120ka, modern Greenland ice sheet | tctac |
| 120ka, partial Greenland ice sheet | tctaq |
| 120ka, no Greenland ice sheet | tctag |
This paper uses pre-industrial and Last Integlacial (130, 125, 120ka) HadCM3 climates pseudo-coupled to an ice sheet model (Glimmer) to probabilistically estimate the Greenland ice sheet contribution to the Last Interglacial sea level highstand and implicates Antarctica to fully account for this sea level rise
| Name | Stone et al |
|---|---|
| Brief Description | This paper uses pre-industrial and Last Integlacial (130, 125, 120ka) HadCM3 climates pseudo-coupled to an ice sheet model (Glimmer) to probabilistically estimate the Greenland ice sheet contribution to the Last Interglacial sea level highstand and implicates Antarctica to fully account for this sea level rise |
| Full Author List | E. J. Stone, D. J. Lunt,J. D. Annan, J. C. Hargreaves |
| Title | Quantification of the Greenland ice sheet contribution to Last Interglacial sea level rise |
| Year | 2013 |
| Journal | Climate of the Past |
| Volume | 9 |
| Issue | 3-4 |
| Pages | 621-639 |
| DOI | 10.5194/cp-9-621-2013 |
| Contact's Name | Emma J Stone |
| Contact's email | Emma.j.stone@bristol.ac.uk |
| Abstract | During the Last Interglacial period (~130 - 115 thousand years ago) the Arctic climate was warmer than today, and global mean sea level was probably more than 6.6m higher. However, there are large discrepancies in the estimated contributions to this sea level change from various sources (the Greenland and Antarctic ice sheets and smaller ice caps). Here, we determine probabilistically the likely contribution of Greenland ice sheet melt to Last Interglacial sea level rise, taking into account ice sheet model parametric uncertainty. We perform an ensemble of 500 Glimmer ice sheet model simulations forced with climatologies from the climate model HadCM3, and constrain the results with palaeodata from Greenland ice cores. Our results suggest a 90% probability that Greenland ice melt contributed at least 0.6 m, but less than 10% probability that it exceeded 3.5 m, a value which is lower than several recent estimates. Many of these previous estimates, however, did not include a full general circulation climate model that can capture atmospheric circulation and precipitation changes in response to changes in insolation forcing and orographic height. Our combined modelling and palaeodata approach suggests that the Greenland ice sheet is less sensitive to orbital forcing than previously thought, and it implicates Antarctic melt as providing a substantial contribution to Last Interglacial sea level rise. Future work should assess additional uncertainty due to inclusion of basal sliding and the direct effect of insolation on surface melt. In addition, the effect of uncertainty arising from climate model structural design should be taken into account by performing a multi-climate-model comparison. |