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
You can have make you own analysis and plots by going here
| Simulation Name as in Paper | Simulation name on web pages |
|---|---|
| 0ka | xmlsb |
| 21k | xmlsd |
These are HadGEM2-ES atmosphere-only simualtions including the internal leaf CO2 partial pressure as an output.
| Name | Hopcroft and Valdes |
|---|---|
| Brief Description | These are HadGEM2-ES atmosphere-only simualtions including the internal leaf CO2 partial pressure as an output. |
| Full Author List | Peter O. Hopcroft, Paul J. Valdes and Jed Kaplan |
| Title | Bayesian Analysis of the Glacial-Interglacial Methane Increase Constrained by Stable Isotopes and Earth System Modelling |
| Year | 2018 |
| Journal | Geophysical Research Letters |
| Volume | |
| Issue | |
| Pages | |
| DOI | 10.1029/2018GL077382. |
| Contact's Name | Peter O. Hopcroft |
| Contact's email | p.hopcroft@bham.ac.uk |
| Abstract | The observed rise in atmospheric methane (CH4) from 375 ppbv during the Last Glacial Maximum (LGM: 21,000 years ago) to 680 ppbv during the late preindustrial era is not well understood. Atmospheric chemistry considerations implicate an increase in CH4 sources, but process‐based estimates fail to reproduce the required amplitude. CH4 stable isotopes provide complementary information that can help constrain the underlying causes of the increase. We combine Earth System model simulations of the late preindustrial and LGM CH4 cycles, including process‐based estimates of the isotopic discrimination of vegetation, in a box model of atmospheric CH4 and its isotopes. Using a Bayesian approach, we show how model‐based constraints and ice core observations may be combined in a consistent probabilistic framework. The resultant posterior distributions point to a strong reduction in wetland and other biogenic CH4 emissions during the LGM, with a modest increase in the geological source, or potentially natural or anthropogenic fires, accounting for the observed enrichment of δ13CH4. |