User Tools

Site Tools


pmip3:wg:p2f:paperseval

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
pmip3:wg:p2f:paperseval [2017/02/13 17:55]
jules
pmip3:wg:p2f:paperseval [2017/02/13 18:09] (current)
jules
Line 14: Line 14:
  
 from the abstract: ''​Here,​ we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4xCO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.''​ from the abstract: ''​Here,​ we describe and evaluate a method for applying GCM-derived shortwave and longwave cloud feedbacks from 4xCO2 and Last Glacial Maximum experiments to the University of Victoria Earth System Climate Model. The method generally captures the spread in top-of-the-atmosphere radiative feedbacks between the original GCMs, which impacts the magnitude and spatial distribution of surface temperature changes and climate sensitivity. These results suggest that the method is suitable to incorporate multi-model cloud feedback uncertainties in ensemble simulations with a single intermediate complexity model.''​
- 
-==== Nonlinear climate sensitivity and its implications for future greenhouse warming ==== 
-Tobias Friedrich, Axel Timmermann, Michelle Tigchelaar, Oliver Elison Timm and Andrey Ganopolski, Science Advances ​ 09 Nov 2016, Vol. 2, no. 11, e1501923, DOI: 10.1126/​sciadv.1501923 http://​advances.sciencemag.org/​content/​2/​11/​e1501923.full ​ 
- 
-abstract: ''​Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,​000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore,​ we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.''​ 
- 
-==== Could the Pliocene constrain the equilibrium climate sensitivity?​ ==== 
-J. C. Hargreaves and J. D. Annan, Clim. Past, 12, 1591-1599, 2016 
-doi:​10.5194/​cp-12-1591-2016,​ http://​www.clim-past.net/​12/​1591/​2016/​ (open access) 
- 
-Short summary ''​The mid-Pliocene Warm Period, 3 million years ago, was the most recent interval with high greenhouse gases. By modelling the period with the same models used for future projections,​ we can link the past and future climates. Here we use data from the mid-Pliocene to produce a tentative result for equilibrium climate sensitivity. We show that there are considerable uncertainties that strongly influence the result, but we are optimistic that these may be reduced in the next few years.''​ 
  
 ==== Terrestrial biosphere changes over the last 120 kyr. ==== ==== Terrestrial biosphere changes over the last 120 kyr. ====
Line 45: Line 34:
  
 excerpts from conclusions:​ ''​Since LGM wind stress, closure of Bering Strait [Hu et al., 2010], and increased tidal mixing [Schmittner et al., 2015] all tend to increase the strength and depth of the AMOC, a countering effect has to be invoked to reproduce observations of a weaker and shallower overturning during the LGM.” … “It will be an important task for future work to resolve the apparent inconsistency between PMIP models’ LGM circulation and reconstructions.This inconsistency casts doubt on future AMOC projections with these models [e.g., Weaver et al., 2012]. One possible explanation may be that not all PMIP3 models were in equilibrium [Zhang et al., 2013].''​ excerpts from conclusions:​ ''​Since LGM wind stress, closure of Bering Strait [Hu et al., 2010], and increased tidal mixing [Schmittner et al., 2015] all tend to increase the strength and depth of the AMOC, a countering effect has to be invoked to reproduce observations of a weaker and shallower overturning during the LGM.” … “It will be an important task for future work to resolve the apparent inconsistency between PMIP models’ LGM circulation and reconstructions.This inconsistency casts doubt on future AMOC projections with these models [e.g., Weaver et al., 2012]. One possible explanation may be that not all PMIP3 models were in equilibrium [Zhang et al., 2013].''​
- 
-==== Interglacial analogues of the Holocene and its natural near future. ==== 
-Yin Q.Z. and Berger A., 2015.  Quaternary Science Reviews, 120, 28-46, http://​www.sciencedirect.com/​science/​article/​pii/​S027737911500150X 
- 
-Highlights: 
-''​•Five warm interglacials are intercompared with both snapshot and transient simulations. 
-•Relationships between astronomical parameters and temperature and precipitation of different latitudes are examined. 
-•Contributions of insolation and CO2 to the intensity and duration of the five interglacials are discussed. 
-•Analogue of the Holocene and its natural future is looked for from the past interglacials.''​ 
- 
-==== Energy-balance mechanisms underlying consistent large-scale temperature responses in warm and cold climates. ==== 
-Izumi, K., Bartlein, P.J. and Harrison, S.P., 2015.  Climate Dynamics 44: 3111 DOI 10.1007/​s00382-014-2189-2,​ http://​link.springer.com/​article/​10.1007/​s00382-014-2189-2 (open access) 
- 
-''​Climate simulations show consistent large-scale temperature responses including amplified land–ocean contrast, high-latitude/​low-latitude contrast, and changes in seasonality in response to year-round forcing, in both warm and cold climates, and these responses are proportional and nearly linear across multiple climate states. We examine the possibility that a small set of common mechanisms controls these large-scale responses using a simple energy-balance model to decompose the temperature changes shown in multiple lgm and abrupt4 × CO2 simulations from the CMIP5 archive. Changes in the individual components of the energy balance are broadly consistent across the models. Although several components are involved in the overall temperature responses, surface downward clear-sky longwave radiation is the most important component driving land–ocean contrast and high-latitude amplification in both warm and cold climates. Surface albedo also plays a significant role in promoting high-latitude amplification in both climates and in intensifying the land–ocean contrast in the warm climate case. The change in seasonality is a consequence of the changes in land–ocean and high-latitude/​low-latitude contrasts rather than an independent temperature response. This is borne out by the fact that no single component stands out as being the major cause of the change in seasonality,​ and the relative importance of individual components is different in cold and warm climates.''​ 
- 
-==== On the state dependency of fast feedback processes in (paleo) climate sensitivity ==== 
-A. S. von der Heydt, P. Köhler, R. S. W. van de Wal, H. A. Dijkstra 
-GRL, Volume 41, Issue 18, pages 6484–6492,​ 28 September 2014, DOI: 10.1002/​2014GL061121,​ http://​onlinelibrary.wiley.com/​doi/​10.1002/​2014GL061121/​abstract ​ 
- 
-from abstract ''​Here we assess the dependency of the fast feedback processes on the background climate state using data of the last 800 kyr and a box model of the climate system for interpretation. Applying a new method to account for background state dependency, we find Sa=0.61±0.07 K (W m−2)−1(±1σ) using a reconstruction of Last Glacial Maximum (LGM) cooling of −4.0 K and significantly lower climate sensitivity during glacial climates. Due to uncertainties in reconstructing the LGM temperature anomaly, Sa is estimated in the range Sa = 0.54–0.95 K (W m−2)−1.''​ 
  
 ==== Model benchmarking with glacial and mid-Holocene climates. ==== ==== Model benchmarking with glacial and mid-Holocene climates. ====
Line 70: Line 39:
  
 ''​We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene,​ models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.''​ ''​We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene,​ models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.''​
- 
-==== Consistent large-scale temperature responses in warm and cold climates. ==== 
-Izumi, K., Bartlein, P.J. and Harrison, S.P., 2013. , Geophysical Research Letters 40: 1817-1823, doi:​10.1002/​grl.50350,​ http://​onlinelibrary.wiley.com/​doi/​10.1002/​grl.50350/​full 
- 
-Abstract: 
-''​Climate-model simulations of the large-scale temperature responses to increased radiative forcing include enhanced land-sea contrast, stronger response at higher latitudes than in the tropics, and differential responses in warm and cool season climates to uniform forcing. Here we show that these patterns are also characteristic of model simulations of past climates. The differences in the responses over land as opposed to over the ocean, between high and low latitudes, and between summer and winter are remarkably consistent (proportional and nearly linear) across simulations of both cold and warm climates. Similar patterns also appear in historical observations and paleoclimatic reconstructions,​ implying that such responses are characteristic features of the climate system and not simple model artifacts, thereby increasing our confidence in the ability of climate models to correctly simulate different climatic states.''​ 
- 
-==== Making sense of palaeoclimate sensitivity ==== 
-PALAEOSENS Project Members 
-Nature 491, 683–691 (29 November 2012) doi:​10.1038/​nature11574,​ http://​www.nature.com/​nature/​journal/​v491/​n7426/​abs/​nature11574.html ​ 
- 
-from abstract: ''​…to improve intercomparison of palaeoclimate sensitivity estimates in a manner compatible with equilibrium projections for future climate change. Over the past 65 million years, this reveals a climate sensitivity (in K W−1 m2) of 0.3–1.9 or 0.6–1.3 at 95% or 68% probability,​ respectively. The latter implies a warming of 2.2–4.8 K per doubling of atmospheric CO2, which agrees with IPCC estimates.''​ 
- 
  
 ====Introduction:​ Warm climates of the past—a lesson for the future?==== ====Introduction:​ Warm climates of the past—a lesson for the future?====
Line 88: Line 44:
  
 ''​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]]''​ ''​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. 
- 
-//keywords: CMIP, model ensemble, Arctic, Benchmark, past century// 
- 
-''​In CMIP3, all sea-ice trends were less than observed. In CMIP5 there are models with both greater and lesser trends. Thus the result obtained by Liu et al is less far from the (new) ensemble mean than was the case for Boé et al 2009.  
- 
-From the abstract: "Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to ∼1.7 million km2 in the mid 2040s and reach the ice-free state (defined as 1 million km2) in 2054–2058. Under a medium-mitigation scenario, both approaches project a decrease to ∼1.7 million km2 in the early 2060s, followed by a leveling off in the ice extent."​ ''​ 
  
 ====Precipitation scaling with temperature in warm and cold climates: an analysis of CMIP5 simulations.==== ​ ====Precipitation scaling with temperature in warm and cold climates: an analysis of CMIP5 simulations.==== ​
Line 105: Line 52:
 ''​Abstract,​ "We investigate the scaling between precipitation and temperature changes in warm and cold climates using six models that have simulated the response to both increased CO2 and Last Glacial Maximum (LGM) boundary conditions. Globally, precipitation increases in warm and decreases in cold climates by between 1.5 to 3%/ ̊C. Precipitation sensitivity to temperature changes are lower over land than ocean and lower over tropical land compared to extratropical land, reflecting the constraint of water availability. The wet tropics get wetter in warm and drier in cold climates, but the changes in dry areas differ among models. Seasonal changes of tropical precipitation in a warmer world also reflect this “rich get richer” syndrome. Precipitation seasonality is decreased in the cold-climate state. The simulated changes in precipitation per degree temperature change are comparable to the observed changes in both the historical period and the LGM." ''​Abstract,​ "We investigate the scaling between precipitation and temperature changes in warm and cold climates using six models that have simulated the response to both increased CO2 and Last Glacial Maximum (LGM) boundary conditions. Globally, precipitation increases in warm and decreases in cold climates by between 1.5 to 3%/ ̊C. Precipitation sensitivity to temperature changes are lower over land than ocean and lower over tropical land compared to extratropical land, reflecting the constraint of water availability. The wet tropics get wetter in warm and drier in cold climates, but the changes in dry areas differ among models. Seasonal changes of tropical precipitation in a warmer world also reflect this “rich get richer” syndrome. Precipitation seasonality is decreased in the cold-climate state. The simulated changes in precipitation per degree temperature change are comparable to the observed changes in both the historical period and the LGM."
 ''​ ''​
- 
-====Using paleo-climate comparisons to constrain future projections in CMIP5==== 
-G. A. Schmidt, J. D. Annan, P. J. Bartlein, B. I. Cook, E. Guilyardi, J. C. Hargreaves, S. P. Harrison, M. Kageyama, A. N. LeGrande, B. Konecky, S. Lovejoy, M. E. Mann, V. Masson-Delmotte,​ C. Risi, D. Thompson13, A. Timmermann, L.-B. Tremblay, and P. Yiou, Clim. Past Discuss., 9, 775-835, ​ [[http://​www.clim-past-discuss.net/​9/​775/​2013/​|open access]], doi:​10.5194/​cpd-9-775-2013,​ 2013 
- 
-//keywords: review/​prospective,​ evaluation, PMIP, CMIP// 
- 
-''​A 2013 discussion of recent progress in the field. Overview of general methods, and some examples, which  include direct constraint of the multi-model ensemble as well slightly more qualitative examples, for example, looking at common patterns of precipitation changes in the models for past and future. ​ 
- 
-Recommendations for ways to tackle the problem are also included, 
-"These examples illustrate some general points that should be required in any attempts to use the paleo-climate simulations to constrain future projections:''​ 
- 
-  * The chosen metrics should be robust to uncertainties in external forcing, 
-  * They should not be overly sensitive to the model representation of key phenomena, and are within the scope of the modelled system. 
-  * A spatially diverse and, preferably multi-proxy,​ paleo-data synthesis is available for comparison. 
-  * The relationship between metrics and targets in the past and future must be examined, and not simply assumed."​ 
- 
-====Quantifying future climate change==== ​ 
-Collins, M., Chandler, R. E., Cox, P. M., Huthnance, J. M., Rougier, J., & Stephenson, D. B. Nature Climate Change, 2(6), 403–409. doi:​10.1038/​nclimate1414,​ [[http://​www.nature.com/​nclimate/​journal/​v2/​n6/​full/​nclimate1414.html|paywall]],​ 2012. 
- 
-//keywords: prospective/​review,​ Bayesian, evaluation//​ 
- 
-''​Some background with links to other papers on probabilistic prediction, single model ensembles, metrics and the like.''​ 
- 
-====Can the Last Glacial Maximum constrain climate sensitivity?​==== ​ 
-J. C. Hargreaves, J. D. Annan, M. Yoshimori, and A. Abe-Ouchi, GEOPHYSICAL RESEARCH LETTERS, VOL. 39, L24702, doi:​10.1029/​2012GL053872,​ [[http://​onlinelibrary.wiley.com/​doi/​10.1029/​2012GL053872/​full|open access]], 2012. 
- 
-//keywords: PMIP, climate sensitiivity,​ model ensemble// 
- 
-''​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 ==== ====Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium ====
Line 151: Line 69:
  
 ''​Review paper focused on PMIP efforts, displaying relationships between (a) land temperature change and ocean temperature change and (b) global and regional changes and elaborating on how carefullyevaluation ofmodelling of past climates may provide insights / constraints on future climate change. ''​ ''​Review paper focused on PMIP efforts, displaying relationships between (a) land temperature change and ocean temperature change and (b) global and regional changes and elaborating on how carefullyevaluation ofmodelling of past climates may provide insights / constraints on future climate change. ''​
- 
-====Sensitivity of tropical precipitation extremes to climate change====  ​ 
-O'​Gorman,​ P. A., Nature Geosci, 5(10), 697–700, [[http://​www.nature.com/​ngeo/​journal/​v5/​n10/​full/​ngeo1568.html|paywall]],​ doi:​doi:​10.1038/​ngeo1568,​ 2012. 
- 
-//keywords: model ensemble, CMIP3, modern, precipitation//​ 
- 
-''​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==== ​
Line 173: Line 76:
  
 ''​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. ''​
- 
-====A probabilistic calibration of climate sensitivity and terrestrial carbon change in GENIE-1==== ​ 
-Philip B. Holden, N. R. Edwards, K. I. C. Oliver, T. M. Lenton & R. D. Wilkinson ​ 
-Clim Dyn [[http://​oro.open.ac.uk/​19191/​2/​|free PDF at Open University repository]] or [[http://​link.springer.com/​article/​10.1007%2Fs00382-009-0630-8#​page-1|journal website]], DOI 10.1007/​s00382-009-0630-8,​ 2010. 
- 
-//keywords: Bayesian, emulator, terrestrial carbon, LGM// 
- 
-''​Using an emulator of multiple varied parameters in the GENIE model. The emulated LGM ensemble is constrained with tropical SST data to produce a probabilistic estimate of climate sensitivity. ''​ 
- 
-====September sea-ice cover in the Arctic Ocean projected to vanish by 2100==== ​ 
-Julien Boé, Alex Hall and Xin Qu, Nature Geoscience 2, 341, [[http://​www.atmos.ucla.edu/​csrl/​publications/​Hall/​boe_et_al_2009a.pdf|free PDF at author'​s homepage]] or [[http://​www.nature.com/​ngeo/​journal/​v2/​n5/​abs/​ngeo467.html|paywall]],​ doi:​10.1038/​ngeo467,​ 2009. 
- 
-//keywords : model ensemble, past century, sea-ice, Arctic// 
- 
-''​From the abstract: "Here we analyse the simulated trends in past sea-ice cover in 18 state-of-art-climate models and find a direct relationship between the simulated evolution of September sea-ice cover over the twenty-first century and the magnitude of past trends in sea-ice cover. Using this relationship together with observed trends, we project the evolution of September sea-ice cover over the twenty-first century."''​ 
- 
-====Correlation between Inter-Model Similarities in Spatial Pattern for Present and Projected Future Mean Climate==== ​ 
-Manabu Abe, Hideo Shiogama, Julia C. Hargreaves, James D. Annan, Toru Nozawa, and Seita Emori, SOLA, Vol. 5, 133‒136, [[https://​www.jstage.jst.go.jp/​article/​sola/​5/​0/​5_0_133/​_article|open access]], doi:​10.2151/​sola.2009‒034 133 1, 3, 2009. 
- 
-//keywords: evaluation, past century, CMIP3, model ensemble // 
- 
-''​ One of several papers from around 2007-2009, looking for "​metrics"​ that relate to future performance. The idea was that if a relationship may be found in the multi-model ensemble between a measurable quantity in the present and a feature of the climate in the future projections,​ then this may in principle be use to constrain the ensemble. In this study the globe was split into broad latitude bands. The metric used is a measure of model similarity. Significant correlations for this metric between present and future were found mostly for precipitation,​ some also for temperature and none for sea level pressure.''​ 
- 
-====Information on the early Holocene climate constrains the summer sea ice projections for the 21st century==== ​ 
-H. Goosse, E. Driesschaert,​ T. Fichefet,​ and M.-F. Loutre, ​ Clim. Past, 3, 683-692, [[http://​www.clim-past.net/​3/​683/​2007/​cp-3-683-2007.html|open access]], doi:​10.5194/​cp-3-683-2007,​ 2007 
- 
-//keywords: parameter ensemble, Holocene, sea-ice// 
- 
-''​Abstract. The summer sea ice extent strongly decreased in the Arctic over the last decades. This decline is very likely to continue in the future but uncertainty of projections is very large. An ensemble of experiments with the climate model LOVECLIM using 5 different parameter sets has been performed to show that summer sea ice changes during the early Holocene (8 kyr BP) and the 21st century are strongly linked, allowing for the reduction of this uncertainty. Using the limited number of records presently available for the early Holocene, simulations presenting very large changes over the 21st century could reasonably be rejected. On the other hand, simulations displaying low to moderate changes during the second half of the 20th century (and also over the 21st century) are not consistent with recent observations. Using this very complementary information based on observations during both the early Holocene and the last decades, the most realistic projection with LOVECLIM indicates a nearly disappearance of the sea ice in summer at the end of the 21st century for a moderate increase in atmospheric greenhouse gas concentrations. Our results thus strongly indicate that additional proxy records of the early Holocene sea ice changes, in particular in the central Arctic Basin, would help to improve our projections of summer sea ice evolution and that the simulation at 8 kyr BP should be considered as a standard test for models aiming at simulating those future summer sea ice changes in the Arctic.''​ 
  
 ====Assessment of the use of current climate patterns to evaluate regional enhanced greenhouse response patterns of climate models==== ​ ====Assessment of the use of current climate patterns to evaluate regional enhanced greenhouse response patterns of climate models==== ​
Line 210: Line 84:
 ''​One of several papers from around 2007-2009, looking for "​metrics"​. The idea was that if a relationship may be found in the multi-model ensemble between a measurable quantity in the present and a feature of the climate in the future projections,​ then this may in principle be use to constrain the ensemble. In this study the globe was split into the land-based "​Giorgi regions"​. The metric is a measure of model similarity. Combining temperature,​ precipitation and sea level pressure seems to provide the best correlations for future performance both regionally and globally.''​ ''​One of several papers from around 2007-2009, looking for "​metrics"​. The idea was that if a relationship may be found in the multi-model ensemble between a measurable quantity in the present and a feature of the climate in the future projections,​ then this may in principle be use to constrain the ensemble. In this study the globe was split into the land-based "​Giorgi regions"​. The metric is a measure of model similarity. Combining temperature,​ precipitation and sea level pressure seems to provide the best correlations for future performance both regionally and globally.''​
  
-====Does the Last Glacial Maximum constrain climate sensitivity?​==== ​ 
-M Crucifix, GRL, doi:​10.1029/​2006GL027137,​ [[http://​onlinelibrary.wiley.com/​doi/​10.1029/​2006GL027137/​abstract|paywall]],​ 2006. 
- 
-//keywords: PMIP, climate sensitivity,​ (small) model ensemble// 
- 
-''​Finds no clear relationship past and future in the (then) small PMIP2 ensemble, and argues as a result that the LGM can only weakly constrain climate sensitivity,​ with the caveat, though, that the range of sensitivities covered by PMIP2 was at the time fairly narrow. ''​ 
- 
-====Using the past to constrain the future: how the palaeorecord can improve estimates of global warming==== ​ 
-Tamsin L. Edwards, Michel Crucifix and Sandy P. Harrison 
-Progress in Physical Geography; 31; 481 [[http://​www.st-andrews.ac.uk/​~rjsw/​papers/​Edwardsetal2007.pdf|free PDF at Uni of St Andrews]] or [[http://​ppg.sagepub.com/​content/​31/​5/​481|paywall]],​ DOI: 10.1177/​0309133307083295. 2007. 
- 
-//keywords: review/​prospective,​ climate sensitivity,​ Bayesian// 
- 
-''​A 2007 overview of efforts to use models to constrain climate sensitivity. Figure 4 is the most enduring result from this paper. It shows that model ensembles derived from different single models do not always overlap. If the multi-model ensemble is a good representation of uncertainty,​ then the single model ensemble members may be considered to be lacking in diversity.'' ​ 
- 
-====Using the current seasonal cycle to constrain snow albedo feedback in future climate change==== ​ 
-Hall, A., & Qu, X.  Geophysical Research Letters, 33(3), L03502, [[http://​www.atmos.ucla.edu/​csrl/​publications/​Hall/​Hall_Qu_2006.pdf|free PDF at author'​s website]] or [[http://​onlinelibrary.wiley.com/​doi/​10.1029/​2005GL025127/​abstract|paywall]],​ doi:​10.1029/​2005GL025127,​ 2006 
- 
-//keywords: Northern hemisphere, PMIP, modern, model ensemble// 
- 
-''​From the abstract: 
-"Large intermodel variations in feedback strength in climate change are nearly perfectly correlated with comparably large intermodel variations in feedback strength in the context of the seasonal cycle. Moreover, the feedback strength in the real seasonal cycle can be measured and compared to simulated values. These mostly fall outside the range of the observed estimate, suggesting many models have an unrealistic snow albedo feedback in the seasonal cycle context. Because of the tight correlation between simulated feedback strength in the seasonal cycle and climate change, eliminating the model errors in the seasonal cycle will lead directly to a reduction in the spread of feedback strength in climate change. Though this comparison to observations may put the models in an unduly harsh light because of uncertainties in the observed estimate that are difficult to quantify, our results map out a clear strategy for targeted observation of the seasonal cycle to reduce divergence in simulations of climate sensitivity."​ ''​ 
- 
-====Climate sensitivity estimated from ensemble simulations of glacial climate==== ​ 
-Thomas Schneider von Deimling, Hermann Held, Andrey Ganopolski & Stefan Rahmstorf, Climate Dynamics, [[http://​www.pik-potsdam.de/​~stefan/​Publications/​Journals/​Schneider_etal_ClimDyn_2006.pdf|free PDF at author'​s website]] or [[http://​link.springer.com/​article/​10.1007%2Fs00382-006-0126-8|paywall]],​ DOI 10.1007/​s00382-006-0126-8,​ 2006 
- 
-//keywords: parameter ensemble, climate sensitivity,​ LGM, dust// 
- 
-''​Possibly the first attempt to use information derived from data for the LGM to directly constrain a model ensemble and provide a constrained prediction of a variable related to future climate (climate sensitivity in this case). A single model ensemble of the EMIC, CLIMBER was used, with the ensemble constrained with estimates of Tropical Atlantic SST for the LGM (GLAMAP). The influence of dust forcing, not included in most model configurations for the LGM climate, was shown to potentially cause a significant bias in the results.''​ 
- 
- 
-====Efficiently Constraining Climate Sensitivity with Ensembles of Paleoclimate Simulations==== ​ 
-J. D. Annan, J. C. Hargreaves, R. Ohgaito, A. Abe-Ouchi and S. Emori, SOLA, Vol. 1, 181‒184, [[https://​www.jstage.jst.go.jp/​article/​sola/​1/​0/​1_0_181/​_article|open access]], doi: 10.2151/​sola. 2005‒047 181, 2005. 
- 
-//keywords: parameter ensemble, climate sensitivity,​ LGM, Bayesian// 
- 
-''​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.''​ 
  
 /* standard page footer */ /* standard page footer */
pmip3/wg/p2f/paperseval.txt · Last modified: 2017/02/13 18:09 by jules