pmip3:wg:p2f:methods
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Last revision Both sides next revision | ||
|
pmip3:wg:p2f:methods [2013/09/11 03:46] jules [Overview of papers] |
pmip3:wg:p2f:methods [2015/07/30 09:23] jules |
||
|---|---|---|---|
| Line 2: | Line 2: | ||
| More details: https://www.dokuwiki.org/plugin:discussion */ | More details: https://www.dokuwiki.org/plugin:discussion */ | ||
| ~~DISCUSSION~~ | ~~DISCUSSION~~ | ||
| - | Contact --- //[[jules@jamstec.go.jp|Julia Hargreaves]] 2013/04/26 06:53// to contribute to this page, or leave a comment in the discussion box. | + | Contact --- //[[jules@blueskiesresearch.org.uk|Julia Hargreaves]] 2013/04/26 06:53// to contribute to this page, or leave a comment in the discussion box. |
| /* This is a comment | /* This is a comment | ||
| Line 59: | Line 59: | ||
| To aid comprehension of the following overview we have defined a number of ‘keywords’ that characterise current research on P2F. | To aid comprehension of the following overview we have defined a number of ‘keywords’ that characterise current research on P2F. | ||
| - | _ ensemble : refers to an article focused to the analysis of a series of experiments. The current literature sometimes ‘ensembles of opportunity’, that is, a series of experiments that have not been designed with the idea of being analysed ‘as en ensemble’, as opposed to ensemble of experiments designed with a carefully chosen sampling scheme (latin hypercube etc. ) | + | * **Ensemble** : refers to an article focused to the analysis of a series of experiments. The current literature sometimes //ensembles of opportunity//, that is, a series of experiments that have not been designed with the idea of being analysed //as en ensemble//, as opposed to ensemble of experiments designed with a carefully chosen sampling scheme (latin hypercube etc. ) |
| - | _ Model ensemble : article making explicit use of several ‘structurally distinct’ climate simulators (as opposed to one simulator with various parameter configurations) | + | * **Single-model ensemble**, **Multi-model ensemble** : article making explicit use of one (for single-model) or several //structurally distinct// (for multi-model) climate models (as opposed to one model with various parameter configurations) |
| - | _ Bayesian : refers to an article featuring an inference process based on the Bayesian paradigm, with explicit references to a prior, a likelihood and a posterior | + | * **Bayesian** : refers to an article featuring an inference process based on the Bayesian paradigm, with explicit references to a prior, a likelihood and a posterior |
| - | _ Evaluation : a fairly broad concept referring to the use of model performance indicators, either presented as quantitative metrics, or yes/no pass tests, the main idea being that models which compare well with data for past climates may be more reliable for predicting future climate change. | + | * **Evaluation** : a fairly broad concept referring to the use of model performance indicators, either presented as quantitative metrics, or yes/no pass tests, the main idea being that models which compare well with data for past climates may be more reliable for predicting future climate change. |
| - | _ Emulator : statistical technique consisting in calibrating a statistical model (generally a Gaussian process) for use as as surrogate to an actual climate simulator, in order to sample efficiently large input spaces, generally in the context of Bayesian inference or global sensitivity analysis | + | * **Emulator** : statistical technique consisting in calibrating a statistical model (generally a Gaussian process) for use as as surrogate to an actual climate simulator (more commonly known as "a climate model"), in order to sample efficiently large input spaces, generally in the context of Bayesian inference or global sensitivity analysis |
| - | _ climate sensitivity : papers with attempting to contribute to the quantification off ‘climate sensitivity’ defined as change in the global average of surface air temperature in response to a doubling in CO2 concentration for pre-industrial. | + | * **Climate sensitivity** : papers with attempting to contribute to the quantification off //climate sensitivity// defined as change in the global average of surface air temperature in response to a doubling in CO2 concentration for pre-industrial. |
| - | _ review / prospective : explicit enough. | + | * **Review / prospective** : explicit enough. |
| - | _ LGM, mid-Holocene, Eocene, Past Millennia, Arctic, past century, modern : epoch tags | + | * **LGM, mid-Holocene, Eocene, Past Millennia, Arctic, past century, modern** : epoch tags |
| - | _ Europe, Global, Northern Hemisphere, Southern Hemisphere : regional tags | + | |
| - | _ Ocean, Atmosphere, Sea-ice, Monsoon, ... : climate process tag | + | |
| - | _ CMIP, PMIP : ‘Project’ tag | + | |
| - | _ detection - attribution : in the climate literature refers to the process of identifying and quantifying forcing agents based on an analysis of the spatio-temporal evolution of both model outputs and observations. A statistical model is generally explicitly defined. | + | * **Europe, Global, Northern Hemisphere, Southern Hemisphere ** : regional tags |
| + | |||
| + | * **Ocean, Atmosphere, Sea-ice, Monsoon, ...** : climate process tag | ||
| + | |||
| + | * **CMIP, PMIP** : //Project// tag | ||
| + | |||
| + | * **Detection - attribution** : in the climate literature refers to the process of identifying and quantifying forcing agents based on an analysis of the spatio-temporal evolution of both model outputs and observations. A statistical model is generally explicitly defined. | ||
| Line 85: | Line 88: | ||
| Chronological by publication date, most recent first: | Chronological by publication date, most recent first: | ||
| - | == Reducing spread in climate model projections of a September ice-free Arctic]] == | + | ==Introduction: Warm climates of the past—a lesson for the future?== |
| + | D. J. Lunt, H. Elderfield, R. Pancost, A. Ridgwell, G. L. Foster, A. Haywood, J. Kiehl, N. Sagoo, C. Shields, E. J. Stone, and P. Valdes, Phil. Trans. R. Soc. A. 2013 371 20130146; doi:10.1098/rsta.2013.0146 (published 16 September 2013) [[http://rsta.royalsocietypublishing.org/content/371/2001/20130146.full.pdf+html|open access]] | ||
| + | |||
| + | ''An introduction to a special issue related to the Discussion Meeting ‘Warm climates of the past—a lesson for the future?’ compiled and edited by Daniel J. Lunt, Harry Elderfield, Richard Pancost and Andy Ridgwell. It is focussed towards emphasising the potential usefulness of the warm climates of the past. Most of the papers seem (I can't read most of them, as only a few are open access and it seems that even mighty JAMSTEC does not subscribe to Phil Trans) focussed towards understanding the past, but there is also one on climate sensitivity by J. Hansen et al, [[http://rsta.royalsocietypublishing.org/content/371/2001/20120294.full.pdf+html|open access]]'' | ||
| + | |||
| + | == Reducing spread in climate model projections of a September ice-free Arctic == | ||
| Jiping Liu, Mirong Song, Radley M. Horton, and Yongyun Hu PNAS, 10.1073/pnas.1219716110/-/DCSupplemental, [[http://www.pnas.org/content/110/31/12571.short|paywall]], 2013. | Jiping Liu, Mirong Song, Radley M. Horton, and Yongyun Hu PNAS, 10.1073/pnas.1219716110/-/DCSupplemental, [[http://www.pnas.org/content/110/31/12571.short|paywall]], 2013. | ||
| Line 131: | Line 139: | ||
| ''Using the PMIP2 models and a reconstruction of LGM temperatures (Annan and Hargreaves 2013), to provide a constraint on climate sensitivity. Two different methods for constraining the ensemble were compared, which relied on an apparent correlation between tropical LGM temperature anomaly, and equilibrium climate sensitivity. '' | ''Using the PMIP2 models and a reconstruction of LGM temperatures (Annan and Hargreaves 2013), to provide a constraint on climate sensitivity. Two different methods for constraining the ensemble were compared, which relied on an apparent correlation between tropical LGM temperature anomaly, and equilibrium climate sensitivity. '' | ||
| - | ==Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 1: Theory== | + | ==Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium == |
| - | Sundberg, R., A. Moberg and A. Hind, Clim. Past, 8, 1339-1353, [[http://www.clim-past.net/8/1355/2012/cp-8-1355-2012.html|open access]], doi:10.5194/cp-8-1339-2012, 2012. and **Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 2: A pseudo-proxy study addressing the amplitude of solar forcing** A. Hind, A. Moberg, and R. Sundberg, Clim. Past, 8, 1355–1365, [[http://www.clim-past.net/8/1355/2012/, doi:10.5194/cp-8-1355-2012, 2012 |open access]] | + | |
| + | **Part 1: Theory**, Sundberg, R., A. Moberg and A. Hind, Clim. Past, 8, 1339-1353, [[http://www.clim-past.net/8/1355/2012/cp-8-1355-2012.html|open access]], doi:10.5194/cp-8-1339-2012, 2012. | ||
| + | |||
| + | **Part 2: A pseudo-proxy study addressing the amplitude of solar forcing** A. Hind, A. Moberg, and R. Sundberg, Clim. Past, 8, 1355–1365, [[http://www.clim-past.net/8/1355/2012/, doi:10.5194/cp-8-1355-2012, 2012 |open access]] | ||
| //keywords : last millennium, test statistics, evaluation, detection / attribution// | //keywords : last millennium, test statistics, evaluation, detection / attribution// | ||
| Line 151: | Line 162: | ||
| ''Finds a relationship between interannual variability and change in extremes of tropical precipitation under global warming in models. Uses satellite observations to estimate the response of the tropical extremes to global warming. '' | ''Finds a relationship between interannual variability and change in extremes of tropical precipitation under global warming in models. Uses satellite observations to estimate the response of the tropical extremes to global warming. '' | ||
| + | |||
| + | ==Climate Sensitivity Estimated from Temperature Reconstructions of the Last Glacial Maximum== | ||
| + | Schmittner, A., Urban N. M., Shakun, J. D., Mahowald, N. M., Clark, P. U., Bartlein, P. J., Mix, A. C., and Rosell-Mele, A., Science, 334, 1385-1388, [[http://www.sciencemag.org/content/334/6061/1385.abstract?keytype=ref&siteid=sci&ijkey=jI1RklqVcZeJ6|paywall]], doi: 10.1126/science.1203513, 2011 | ||
| + | |||
| + | //keywords: single-model ensemble, LGM, Climate Sensitivity// | ||
| + | |||
| + | ''Abstract:Assessing the impact of future anthropogenic carbon emissions is currently impeded by uncertainties in our knowledge of equilibrium climate sensitivity to atmospheric carbon dioxide doubling. Previous studies suggest 3 kelvin (K) as the best estimate, 2 to 4.5 K as the 66% probability range, and nonzero probabilities for much higher values, the latter implying a small chance of high-impact climate changes that would be difficult to avoid. Here, combining extensive sea and land surface temperature reconstructions from the Last Glacial Maximum with climate model simulations, we estimate a lower median (2.3 K) and reduced uncertainty (1.7 to 2.6 K as the 66% probability range, which can be widened using alternate assumptions or data subsets). Assuming that paleoclimatic constraints apply to the future, as predicted by our model, these results imply a lower probability of imminent extreme climatic change than previously thought.'' The data, but not the paper may be downlaoded for free from [[http://people.oregonstate.edu/~schmita2/#y2011|Andreas' website]]. | ||
| + | |||
| ==Skill and reliability of climate model ensembles at the Last Glacial Maximum and mid-Holocene== | ==Skill and reliability of climate model ensembles at the Last Glacial Maximum and mid-Holocene== | ||
| J. C. Hargreaves, J. D. Annan1, R. Ohgaito, A. Paul, and A. Abe-Ouchi, Clim. Past, 9, 811–823, [[http://www.clim-past.net/9/811/2013/|open access]] doi:10.5194/cp-9-811-20132013. and **Are paleoclimate model ensembles consistent with the MARGO data synthesis?** J. C. Hargreaves, A. Paul, R. Ohgaito, A. Abe-Ouchi, and J. D. Annan Clim. Past, 7, 917–933, [[http://www.clim-past.net/7/917/2011/|open access]] doi:10.5194/cp-7-917-2011, 2011 | J. C. Hargreaves, J. D. Annan1, R. Ohgaito, A. Paul, and A. Abe-Ouchi, Clim. Past, 9, 811–823, [[http://www.clim-past.net/9/811/2013/|open access]] doi:10.5194/cp-9-811-20132013. and **Are paleoclimate model ensembles consistent with the MARGO data synthesis?** J. C. Hargreaves, A. Paul, R. Ohgaito, A. Abe-Ouchi, and J. D. Annan Clim. Past, 7, 917–933, [[http://www.clim-past.net/7/917/2011/|open access]] doi:10.5194/cp-7-917-2011, 2011 | ||
| - | //keywords: PMIP, LGM, evaluation, ocean (SST)// | + | //keywords: PMIP, LGM, evaluation, temperature (SAT over land, SST for ocean)// |
| ''Show that PMIP2 and available PMIP3 models are reliable and have skill for air and surface ocean temperatures on broad scales, for the LGM. On the other hand, the MIROC single model ensemble is under-dispersive (a result common for single model ensembles - see Yokohata et al 2010). Additionally the models have no skill and are not reliable for the mid-Holocene interval. '' | ''Show that PMIP2 and available PMIP3 models are reliable and have skill for air and surface ocean temperatures on broad scales, for the LGM. On the other hand, the MIROC single model ensemble is under-dispersive (a result common for single model ensembles - see Yokohata et al 2010). Additionally the models have no skill and are not reliable for the mid-Holocene interval. '' | ||
| Line 232: | Line 251: | ||
| ''In this case, estimates of tropical SST taken from the literature were used to constrain a since model ensemble with varied parameters of the MIROC GCM. This MIROC ensemble has now been shown to be of much lower dispersion than the multi-model ensemble (Hargreaves et al above, and Yokohata et al 2010). Indeed it was found impossible to produce a run with this model climate sensitivity less than 4C, while the data constraint for the LGM data suggested a lower value was entirely plausible.'' | ''In this case, estimates of tropical SST taken from the literature were used to constrain a since model ensemble with varied parameters of the MIROC GCM. This MIROC ensemble has now been shown to be of much lower dispersion than the multi-model ensemble (Hargreaves et al above, and Yokohata et al 2010). Indeed it was found impossible to produce a run with this model climate sensitivity less than 4C, while the data constraint for the LGM data suggested a lower value was entirely plausible.'' | ||
| + | ====Authors==== | ||
| + | Contributors to this page: | ||
| + | |||
| + | James Annan, | ||
| + | Michel Crucifix, | ||
| + | Julia Hargreaves. | ||
| + | |||
| /* standard page footer */ | /* standard page footer */ | ||
pmip3/wg/p2f/methods.txt · Last modified: 2017/02/10 15:47 by jules
