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AbruptSLR

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Re: Modelling the Anthropocene
« Reply #50 on: March 12, 2016, 10:39:28 PM »
The linked (open access) reference takes into account the implications of the Paris Pact, and also uses ESLD assumptions about climate sensitivity; nevertheless, it projects radiative forcing scenarios that will likely result a commitment to eventually reach a 1.5C GMST rise by 2020 and a commitment to reach a 2C GMST rise by 2030:

Wagner L, Ross I, Foster J, Hankamer B (2016), "Trading Off Global Fuel Supply, CO2 Emissions and Sustainable Development", PLoS ONE 11(3): e0149406, doi:10.1371/journal.pone.0149406


http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149406


Abstract: "The United Nations Conference on Climate Change (Paris 2015) reached an international agreement to keep the rise in global average temperature ‘well below 2°C’ and to ‘aim to limit the increase to 1.5°C’. These reductions will have to be made in the face of rising global energy demand. Here a thoroughly validated dynamic econometric model (Eq 1) is used to forecast global energy demand growth (International Energy Agency and BP), which is driven by an increase of the global population (UN), energy use per person and real GDP (World Bank and Maddison). Even relatively conservative assumptions put a severe upward pressure on forecast global energy demand and highlight three areas of concern. First, is the potential for an exponential increase of fossil fuel consumption, if renewable energy systems are not rapidly scaled up. Second, implementation of internationally mandated CO2 emission controls are forecast to place serious constraints on fossil fuel use from ~2030 onward, raising energy security implications. Third is the challenge of maintaining the international ‘pro-growth’ strategy being used to meet poverty alleviation targets, while reducing CO2 emissions. Our findings place global economists and environmentalists on the same side as they indicate that the scale up of CO2 neutral renewable energy systems is not only important to protect against climate change, but to enhance global energy security by reducing our dependence of fossil fuels and to provide a sustainable basis for economic development and poverty alleviation. Very hard choices will have to be made to achieve ‘sustainable development’ goals."
« Last Edit: March 12, 2016, 11:13:08 PM by AbruptSLR »
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AbruptSLR

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Re: Modelling the Anthropocene
« Reply #51 on: March 15, 2016, 09:04:26 PM »
The linked presentation (see two images from the presentation) discusses the present challenges facing ESM groups:

Jean-François Lamarque (2016), "Balancing processes, resolution and ensembles in Earth system models"

 http://cpo.noaa.gov/sites/cpo/MAPP/Webinars/2016/01-29-16/Lamarque.pdf

Abstract: "Using recent simulation results and model developments, this talk will discuss the present challenges that Earth System modeling group are facing in creating and using the next generation of Earth system models, in particular in the light of the upcoming CMIP6."

See also:
http://cpo.noaa.gov/ClimatePrograms/ModelingAnalysisPredictionsandProjections/MAPPNewsEvents/TabId/506/artmid/1256/articleid/445201/Default.aspx

“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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AbruptSLR

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Re: Modelling the Anthropocene
« Reply #52 on: March 23, 2016, 05:37:05 PM »
Per the linked peer-reviewed reference, it looks like any future modeling radiative forcing scenarios may well need to increase the contribution from food production due both to unexpectedly high population growth projections and increasingly rich food demands per capita:

Mario Herrero, Benjamin Henderson, Petr Havlík, Philip K. Thornton, Richard T. Conant, Pete Smith, Stefan Wirsenius, Alexander N. Hristov, Pierre Gerber, Margaret Gill, Klaus Butterbach-Bahl, Hugo Valin, Tara Garnett & Elke Stehfest (2016), "Greenhouse gas mitigation potentials in the livestock sector" Nature Climate Change, doi:10.1038/nclimate2925


http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2925.html

Abstract: "The livestock sector supports about 1.3 billion producers and retailers, and contributes 40–50% of agricultural GDP. We estimated that between 1995 and 2005, the livestock sector was responsible for greenhouse gas emissions of 5.6–7.5 GtCO2e yr−1. Livestock accounts for up to half of the technical mitigation potential of the agriculture, forestry and land-use sectors, through management options that sustainably intensify livestock production, promote carbon sequestration in rangelands and reduce emissions from manures, and through reductions in the demand for livestock products. The economic potential of these management alternatives is less than 10% of what is technically possible because of adoption constraints, costs and numerous trade-offs. The mitigation potential of reductions in livestock product consumption is large, but their economic potential is unknown at present. More research and investment are needed to increase the affordability and adoption of mitigation practices, to moderate consumption of livestock products where appropriate, and to avoid negative impacts on livelihoods, economic activities and the environment."


See also:
http://www.carbonbrief.org/guest-post-failure-to-tackle-food-demand-could-make-1-point-5-c-limit-unachievable

Extract: "The emissions pathway we’d need to follow for a 66% chance of staying within 1.5C suggests that food-related emissions at current levels would take up our entire greenhouse gas budget in 2050.
That means unless things change – radically – our demand for food could leave no space for emissions from any of the other services we require to live our daily lives.
In short, our demand for food alone could virtually guarantee that the Paris aspirations are unachievable.
There are three possible ways we could respond to this sobering conclusion:
- We carry on as we are and miss the Paris targets, and therefore perhaps lock us into 4-5C of global warming by the end of the century;
- We rely on research and innovation to find ways to significantly increase yields to reduce the rate of land conversion and develop carbon capture and storage, or
- We recognise that demand for food is driving emissions and work to change that to meet the supply-side improvements halfway.  "
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #53 on: March 23, 2016, 05:41:50 PM »
Per the linked reference it appears that previously under-appreciated inactions between multiple climate change tipping points; means that the climate consequences for any given assumed forcing scenario is likely worse than previously appreciated by mainstream scientists and policy makers.  The authors call for more aggressive reductions in future GHG emissions.

Yongyang Cai, Timothy M. Lenton & Thomas S. Lontzek (2016), "Risk of multiple interacting tipping points should encourage rapid CO2 emission reduction", Nature Climate Change, doi:10.1038/nclimate2964


http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2964.html


Abstract: "Evidence suggests that several elements of the climate system could be tipped into a different state by global warming, causing irreversible economic damages. To address their policy implications, we incorporated five interacting climate tipping points into a stochastic-dynamic integrated assessment model, calibrating their likelihoods and interactions on results from an existing expert elicitation. Here we show that combining realistic assumptions about policymakers’ preferences under uncertainty, with the prospect of multiple future interacting climate tipping points, increases the present social cost of carbon in the model nearly eightfold from US$15 per tCO2 to US$116 per tCO2. Furthermore, passing some tipping points increases the likelihood of other tipping points occurring to such an extent that it abruptly increases the social cost of carbon. The corresponding optimal policy involves an immediate, massive effort to control CO2 emissions, which are stopped by mid-century, leading to climate stabilization at <1.5 °C above pre-industrial levels."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #54 on: March 23, 2016, 06:29:19 PM »
The linked reference indicates that the largest reason for the methane emissions plateau from 1999 to 2006 was the collapse of the USSR; while the most likely reason for the recent surge in methane emissions is food production in South, East, and Southeast Asia.  The authors are also concerned to further global warming could trigger other sources of methane emissions.  This information can be used to better calibrate both models and radiative forcing scenarios for AR6:


H. Schaefer, Sara E. Mikaloff Fletcher, Cordelia Veidt, Keith R. Lassey, Gordon W. Brailsford, Tony M. Bromley, Edward J. Dlugokencky, Sylvia E. Michel, John B. Miller, Ingeborg Levin, Dave C. Lowe, Ross J. Martin, Bruce H. Vaughn & James W. C. White (2016), "A 21st century shift from fossil-fuel to biogenic methane emissions indicated by 13CH4", Science  DOI: 10.1126/science.aad2705


http://science.sciencemag.org/content/early/2016/03/09/science.aad2705

Abstract: "Between 1999 and 2006, a plateau interrupted the otherwise continuous increase of atmospheric methane concentration [CH4] since pre-industrial times. Causes could be sink variability or a temporary reduction in industrial or climate sensitive sources. We reconstruct the global history of [CH4] and its stable carbon isotopes from ice cores, archived air and a global network of monitoring stations. A box-model analysis suggests that diminishing thermogenic emissions, probably from the fossil-fuel industry, and/or variations in the hydroxyl CH4-sink caused the [CH4]-plateau. Thermogenic emissions didn’t resume to cause the renewed [CH4]-rise after 2006, which contradicts emission inventories. Post-2006 source increases are predominantly biogenic, outside the Arctic, and arguably more consistent with agriculture than wetlands. If so, mitigating CH4-emissions must be balanced with the need for food production."

See also:
http://www.sciencemag.org/news/2016/03/soviet-collapse-might-explain-mysterious-trend-global-methane-emissions
&
http://phys.org/news/2016-03-scientists-attribute-methane-agriculture.html

“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #55 on: March 23, 2016, 06:42:03 PM »
The following is a re-post from the "UN Climate Agreement - Paris 2015" thread:

The linked reference uses empirically informed levels of strategic reasoning to calibrate model simulations of international negotiations on climate change.  First, the research shows that when a tipping point threshold has been clearly identified then it is easier to achieve an international agree such as the Paris Pact; thus using inversion the fact that the Paris Pact was achieved is an indication that clear evidence of an impending tipping point was presented to the negotiators at CoP21.  Second, the research shows that "policy elites" (like those in the EU & the USA) often use higher degrees of strategic reasoning to try to beggar their neighbors when negotiating national emission levels within such agreements; which indicates that it will likely be extremely difficult to ratchet-up additional emission restriction; which increases the probability for climate catastrophe this century:

Vilhelm Verendel, Daniel J. A. Johansson & Kristian Lindgren (2016), "Strategic reasoning and bargaining in catastrophic climate change games", Nature Climate Change, Volume: 6, Pages: 265–268, doi:10.1038/nclimate2849

http://www.nature.com/nclimate/journal/v6/n3/full/nclimate2849.html

Abstract: "Two decades of international negotiations show that agreeing on emission levels for climate change mitigation is a hard challenge. However, if early warning signals were to show an upcoming tipping point with catastrophic damage, theory and experiments suggest this could simplify collective action to reduce greenhouse gas emissions. At the actual threshold, no country would have a free-ride incentive to increase emissions over the tipping point, but it remains for countries to negotiate their emission levels to reach these agreements. We model agents bargaining for emission levels using strategic reasoning to predict emission bids by others and ask how this affects the possibility of reaching agreements that avoid catastrophic damage. It is known that policy elites often use a higher degree of strategic reasoning, and in our model this increases the risk for climate catastrophe. Moreover, some forms of higher strategic reasoning make agreements to reduce greenhouse gases unstable. We use empirically informed levels of strategic reasoning when simulating the model."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

sidd

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Re: Modelling the Anthropocene
« Reply #56 on: March 23, 2016, 06:46:27 PM »
That Cai paper has an interesting figure on change in social cost of carbon as various (interacting) tipping points are reached, each of whinch may induce other tipping points to be exceeded. I have attached Fig 3. I am suspicious of integrated assessment models, but i do like this paper.

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #57 on: March 23, 2016, 09:00:14 PM »
That Cai paper has an interesting figure on change in social cost of carbon as various (interacting) tipping points are reached, each of whinch may induce other tipping points to be exceeded. I have attached Fig 3. I am suspicious of integrated assessment models, but i do like this paper.

While I like the methodology used by the authors, I disagree with the timing and sequencing of the tipping points that they evaluate, & I draw particular attention to the risk of the WAIS beginning to collapse rapidly by 2050.  It seems to me that Cai et al (2016) would benefit from reading Hansen et al (2016), with regards to the risks associated with both WAIS collapse and combined WAIS & GIS collapse.  Furthermore, due to wildfires and deforestation, I think that the Amazon Basin in much closer to collapse than the authors indicate.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #58 on: April 01, 2016, 06:31:13 PM »
The linked reference discusses how the latent energy transport of atmospheric planetary waves contributes to Arctic Amplification:

Rune G. Graversen and Mattias Burtu (2016), "Arctic amplification enhanced by latent energy transport of atmospheric planetary waves", Quarterly Journal of the Royal Meteorological Society, DOI: 10.1002/qj.2802


http://onlinelibrary.wiley.com/doi/10.1002/qj.2802/abstract

Abstract: "The atmospheric northward energy transport plays a crucial role for the Arctic climate; this transport brings to the Arctic an amount of energy comparable to that provided directly by the sun. The transport is accomplished by atmospheric waves – for instance large-scale planetary waves and meso-scale cyclones – and the zonal-mean circulation. These different components of the energy transport impact the Arctic climate differently.
A split of the transport into stationary and transient waves constitutes a traditional way of decomposing the transport. However this procedure does not take into account the transport accomplished separately by the planetary and synoptic-scale waves. Here a Fourier decomposition is applied, which decomposes the transport with respect to zonal wave numbers. Reanalysis and model data reveal that the planetary waves impact Arctic temperatures much more than do synoptic-scale waves. In addition the latent transport by these waves affects the Arctic climate more than does the dry-static part. Finally, the EC-Earth model suggests that changes of the energy transport over the 21 st century will contribute to Arctic warming, despite the fact that in this model the total energy transport to the Arctic will decrease. This apparent contradicting result is due to the cooling induced by a decrease of the dry-static transport by planetary waves being more than compensated for by a warming caused by the latent counterpart."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #59 on: April 04, 2016, 10:39:51 AM »
The linked reference discusses state-of-the-art work to model trends in the ocean carbon sink; however, they found that it is still too early to make clear projections as to whether this critical sink will increase, or decrease, with continued global warming:

Galen A. McKinley, Darren J. Pilcher, Amanda R. Fay, Keith Lindsay, Matthew C. Long & Nicole S. Lovenduski (25 February 2016), "Timescales for detection of trends in the ocean carbon sink", Nature, Volume: 530, Pages: 469–472, doi:10.1038/nature16958


http://www.nature.com/nature/journal/v530/n7591/full/nature16958.html


Abstract: "The ocean has absorbed 41 per cent of all anthropogenic carbon emitted as a result of fossil fuel burning and cement manufacture. The magnitude and the large-scale distribution of the ocean carbon sink is well quantified for recent decades. In contrast, temporal changes in the oceanic carbon sink remain poorly understood. It has proved difficult to distinguish between air-to-sea carbon flux trends that are due to anthropogenic climate change and those due to internal climate variability. Here we use a modelling approach that allows for this separation, revealing how the ocean carbon sink may be expected to change throughout this century in different oceanic regions. Our findings suggest that, owing to large internal climate variability, it is unlikely that changes in the rate of anthropogenic carbon uptake can be directly observed in most oceanic regions at present, but that this may become possible between 2020 and 2050 in some regions."

See also:
http://phys.org/news/2016-02-climate-ocean-carbon.html

Extract: "The researchers also checked the model against actual ocean observations. "What we find is that observations today are not sufficient to be able to see change in the ocean-carbon sink," McKinley explains. "We can see that there is a sink, but at any one location, we don't have enough data to say that the sink is increasing or decreasing.""
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #60 on: May 19, 2016, 08:56:20 PM »
Per the linked article, ACME Version 1 is on schedule and ready to lock & load (see attached image from the atmosphere module):


https://climatechangescience.ornl.gov/content/acme%E2%80%94scaling-heights

Extract: "More important, the team, which consists of eight national laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company, is on schedule for release of Version 1 of the ACME model in June 2016.
The major activity this past year was completion of Version 1 of the model, based on the Community Earth System Model or CESM. The team has been running tests on the model since late last year. After the release in June, the team will start a series of science experiments, in the works for 2 years, that will run from July 2016 through July 2017."
...
On the land model side, the most significant advance made this past year was integrating the phosphorus cycle. In the past, Thornton points out, CESM was unique in the community of global ESMs for including both a nitrogen cycle and a carbon cycle. No Earth system model to date, however, has included phosphorus. ACME Version 1 will include carbon, nitrogen, and phosphorus cycles, based on work by Xiaojuan Yang, a CCSI early career scientist. “This is world class new science that no other coupled model has, and it will have an important impact on predictions of future climate,” says Thornton. “We’re really excited about that.”

Another innovation the team has introduced is what’s called “reactive transport modeling capability.” This is a new, more sophisticated way to solve the coupled hydrology-temperature (freeze-thaw) dynamics and biogeochemistry reactions in the soil and between the soil and vegetation. Thornton says the approach more consistently integrates the mass, energy, and biological components of the model, including the phosphorus cycle work.
...
Daniel M. Ricciuto from CCSI’s Integrative Ecosystem Science group (formerly known as the Terrestrial Ecosystem and Carbon Cycle Science group) works on the uncertainty quantification (UQ) component of the ACME project. Thornton says it’s a formal framework to estimate the uncertainty associated with some of the model parameters to optimize model predictions. That same framework is used to estimate parameter values for the model to optimize the metrics of model performance against other independent observations such as those from satellites. Tuning parameters in the model that are uncertain based on actual measurements will facilitate model optimization.
...
Achievements by the ACME Atmospheric Model team have been no less impressive, but perhaps the most exciting have been in the area of high-resolution simulation. Most global models today don’t represent the impacts of climate change on water resources very well in mountainous regions or other regions with complex terrain. To address this, the team has developed a topography-based subgrid system based on high-resolution global elevation data from various sources. This results in a greater number of subgrid units over regions of complex terrain, such as mountains, leading to better representation of precipitation and surface water flow in such regions. For consistency, the same high-resolution subgrid system is also being used for the ACME Land Model.
...
Pat Worley is leading the performance evaluation effort, both for ORNL aspects of the project and for the project as a whole. Up to this point, that’s mainly been a matter of ensuring all the subcomponents of the system run as quickly as possible on Titan and other leadership computing resources and then ensuring that when they are coupled they continue to run quickly. The performance target they are aiming for is 5 simulation years per day for the highest resolution simulations.

One of the goals of the ACME project is to optimize model performance for future leadership computing architectures, and Thornton says that the Performance Task Team is already preparing for the next generation of computers, due in 2017 (the “mid-machines” before exascale such as ORNL’s Summit). As part of this preparation, the team submitted a successful proposal to the Oak Ridge Leadership Computing Facility’s Center for Accelerated Application Readiness or CAAR program. Through CAAR, the ACME team will gain early access to Summit’s hybrid CPU–GPU architecture and technical support for software development. And of course, Worley and the team are already looking at model development and needs for the exascale model.
...
Workflow is the final piece being worked on in CCSI. The goal is to have a robust system that domain scientists can use efficiently and effectively without a lot of tedious work up front. The workflow tool under construction is really a set of tools operating under a web-based user interface that will be in place when Version 1 is rolled out in June—available to the whole world. Not having a workflow tool such as the one being designed restricts the science that can be done and the use of the model to that very small population of computer programmers/modelers/software engineers who are also domain scientists. “So by looking at workflow, we really hope to open it up to a larger community,” Thornton says."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

theoldinsane

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Re: Modelling the Anthropocene
« Reply #61 on: May 20, 2016, 12:06:18 AM »
"Per the linked article, ACME Version 1 is on schedule and ready to lock & load (see attached image from the atmosphere module):"

Thank you AbruptSLR. If I understand it right it will be a big step forward in Climate Change science and understanding?

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #62 on: May 20, 2016, 12:29:41 AM »
"Per the linked article, ACME Version 1 is on schedule and ready to lock & load (see attached image from the atmosphere module):"

Thank you AbruptSLR. If I understand it right it will be a big step forward in Climate Change science and understanding?

Yes, ACME will represent a big step forward, and you might also want to look at the thread on:

Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME:
http://forum.arctic-sea-ice.net/index.php/topic,1478.msg70074.html#msg70074


“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

theoldinsane

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Re: Modelling the Anthropocene
« Reply #63 on: May 20, 2016, 01:24:26 AM »
"Per the linked article, ACME Version 1 is on schedule and ready to lock & load (see attached image from the atmosphere module):"

Thank you AbruptSLR. If I understand it right it will be a big step forward in Climate Change science and understanding?

Yes, ACME will represent a big step forward, and you might also want to look at the thread on:

Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME:
http://forum.arctic-sea-ice.net/index.php/topic,1478.msg70074.html#msg70074

AbruptSLR, a few years ago I started to read some posts in this forum. Back then I was interested mostly in the melting of the Arctic sea ice and thought the Antarctic situation was not so important. But your continuous writings changed that. "Water erodes rock not by its power but by tenacity". That is what you have done with me. But now I think I have a much more holistic view of ongoing climate change and that is scary knowledge. Although I am old, still I see forward to learne more. Big thanks to you for your willingness to teach us about very difficult and scary issues.

Keep up the good work!

Back to lurking...
« Last Edit: May 20, 2016, 01:31:45 AM by theoldinsane »

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #64 on: May 22, 2016, 07:26:08 PM »
The linked article provides valuable discussion about using regional climate models compared to global models.  Such discussions help to better understand the approach being adopted by the ACME project:

http://www.realclimate.org/index.php/archives/2016/05/do-regional-climate-models-add-value-compared-to-global-models/#more-19412

Extract: "We need to apply downscaling to compute the local details. Downscaling may be done through empirical-statistical downscaling (ESD) or regional climate models (RCMs) with a much finer grid. Both take the crude (low-resolution) solution provided by the GCMs and include finer topographical details (boundary conditions) to calculate more detailed information. However, does more details translate to a better representation of the world?
The question of “added value” was an important topic at the International Conference on Regional Climate conference hosted by CORDEX of the World Climate Research Programme (WCRP). The take-home message was mixed on whether RCMs provide a better description of local climatic conditions than the coarser GCMs.
RCMs can add details such as the influence of lakes, sea breeze, mountain ranges, and sharper weather fronts. Systematic differences between results from RCMs and observations may not necessarily be less than those for GCMs, however."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #65 on: May 24, 2016, 11:25:28 PM »
The linked reference indicates society currently only looks at the impacts of climate of individual sectors (like agriculture) in isolation; which is likely to misrepresent the true impacts.  For example the Paris Pact does not limit carbon emissions from agriculture yet it is impossible to achieve its stated goals when considering the impacts of agriculture on the climate:

Paula A. Harrison et al. Climate change impact modelling needs to include cross-sectoral interactions, Nature Climate Change (2016). DOI: 10.1038/nclimate3039


http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3039.html

Abstract: "Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale."

See also:
http://phys.org/news/2016-05-full-picture-climate-impacts.html

Extract: "How can society plan for the future if we only look at individual issues in isolation? Climate change impact studies typically focus on a single sector such as agriculture, forestry or water, ignoring the implications of how different sectors interact. A new study, published in Nature Climate Change, suggests that an integrated, cross-sectoral approach to climate change assessment is needed to provide a more complete picture of impacts that enables better informed decisions about climate adaptation.


Using the CLIMSAVE Integrated Assessment Platform (IAP), which links models of agriculture, forestry, urban growth, land use, water resources, flooding and biodiversity, the new study compares single-sector and integrated modelling approaches and their outcomes.
The resulting discrepancies are particularly evident for indicators such as food production and water exploitation which are highly influenced by other sectors through changes in demand, land suitability and resource competition.
"This analysis has demonstrated quantitatively for the first time the uncertainty arising from a single sector perspective. This highlights the importance of developing adaptation plans that are robust to changes in climate and socio-economic pathways and that take account of cross-sectoral interactions", concludes Dr. Harrison."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #66 on: June 06, 2016, 07:49:35 PM »
The linked reference discusses the dominate role that atmospheric moisture transport plays in the onset of Arctic sea ice melting, and identifies an associate trend for earlier spring ice melting, during recent decades due to AGW:

Jonas Mortin,Gunilla Svensson, Rune G. Graversen, Marie-Luise Kapsch, Julienne C. Stroeve & Linette N. Boisvert (3 June 2016), "Melt onset over Arctic sea ice controlled by atmospheric moisture transport", Geophysical Research Letters, DOI: 10.1002/2016GL069330

http://onlinelibrary.wiley.com/doi/10.1002/2016GL069330/abstract

Abstract: "The timing of melt onset affects the surface energy uptake throughout the melt season. Yet the processes triggering melt and causing its large interannual variability are not well understood. Here, we show that melt onset over Arctic sea ice is initiated by positive anomalies of water vapor, clouds, and air temperatures that increase the downwelling longwave radiation (LWD) to the surface. The earlier melt onset occurs, the stronger are these anomalies. Downwelling shortwave radiation (SWD) is smaller than usual at melt onset, indicating that melt is not triggered by SWD. When melt occurs early, an anomalously opaque atmosphere with positive LWD anomalies preconditions the surface for weeks preceding melt. In contrast, when melt begins late, clearer than usual conditions are evident prior to melt. Hence, atmospheric processes are imperative for melt onset. It is also found that spring LWD increased during recent decades, consistent with trends towards an earlier melt onset."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

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Re: Modelling the Anthropocene
« Reply #67 on: June 13, 2016, 09:33:12 PM »
The linked reference uses CMIP5 RCP 8.5 projections to confirm that Arctic sea-ice concentration, SIC, loss serves as feedback mechanism for Arctic Amplification, with conclusions including: "In these models, the AA trend tends to increase until the mean SIC reaches a critical level (i.e., 20 ~ 30%), and the maximum AA trend is almost three to five times larger than the trend in the early stage of global warming (i.e., 50 ~ 60%, 60 ~ 70%). However, the AA trend tends to decrease after that."

Bo Young Yim, Hong Sik Min, Baek-Min Kim, Jee-Hoon Jeong & Jong-Seong Kug (11 June 2016), "Sensitivity of Arctic warming to sea-ice concentration", JGR Atmospheres, DOI: 10.1002/2015JD023953

http://onlinelibrary.wiley.com/doi/10.1002/2015JD023953/abstract

Abstract: "We examine the sensitivity of Arctic amplification (AA) to background sea-ice concentration (SIC) under greenhouse warming by analyzing the datasets of the historical and Representative Concentration Pathway 8.5 (RCP8.5) runs of the Coupled Model Intercomparison Project Phase 5 (CMIP5). To determine whether the sensitivity of AA for a given radiative forcing depends on background SIC state, we examine the relationship between the AA trend and mean SIC on moving 30-yr windows from 1960 to 2100. It is found that the annual mean AA trend varies depending on the mean SIC condition. In particular, some models show a highly variable AA trend in relation to the mean SIC clearly. In these models, the AA trend tends to increase until the mean SIC reaches a critical level (i.e., 20 ~ 30%), and the maximum AA trend is almost three to five times larger than the trend in the early stage of global warming (i.e., 50 ~ 60%, 60 ~ 70%). However, the AA trend tends to decrease after that. Further analysis shows that the sensitivity of AA trend to mean SIC condition is closely related to the feedback processes associated with summer surface albedo and winter turbulent heat flux in the Arctic Ocean."
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Re: Modelling the Anthropocene
« Reply #68 on: June 13, 2016, 09:50:23 PM »
The linked research discusses some recent efforts (& challenges) to try to better constraint the "… extremely large spread of effective climate sensitivity (ECS) ranging about 2.1–10.4 K":

Youichi Kamae, Hideo Shiogama, Masahiro Watanabe, Tomoo Ogura, Tokuta Yokohata, and Masahide Kimoto (6 June, 2016), "Lower tropospheric mixing as a constraint on cloud feedback in a Multi-Parameter Multi-Physics Ensemble", JCLI, DOI: http://dx.doi.org/10.1175/JCLI-D-16-0042.1


http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0042.1

Abstract: "Factors and possible constraints to extremely large spread of effective climate sensitivity (ECS) ranging about 2.1–10.4 K are examined by using a large-member ensemble of quadrupling CO2 experiments with an atmospheric general circulation model (AGCM). The ensemble, called Multi-Parameter Multi-Physics Ensemble (MPMPE), consists of both parametric and structural uncertainties in parameterizations of cloud, cumulus convection and turbulence based on two different versions of AGCM. Sum of low- and middle-cloud shortwave feedback explains most part of the ECS spread among the MPMPE members. Among half of perturbed physics ensembles (PPEs) in the MPMPE, variation in lower-tropospheric mixing intensity (LTMI) corresponds well with the ECS variation, while does not apply to the remainders. In the latter PPEs, large spread in optically-thick middle-cloud feedback over the equatorial ocean substantially affects the ECS, disrupts the LTMI–ECS relationship. Although observed LTMI can constrain uncertainty in the low-cloud feedback, total uncertainty of the ECS among the MPMPE cannot solely be explained by the LTMI, suggesting a limitation of single emergent constraint for the ECS."
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Re: Modelling the Anthropocene
« Reply #69 on: June 13, 2016, 10:00:57 PM »
The linked research uses computer simulations of the Last Interglacial, LIG, to evaluate the sensitivity of global warming to changes in the Greenland Ice Sheet, GIS:

Pfeiffer, M. and Lohmann, G.: Greenland Ice Sheet influence on Last Interglacial climate: global sensitivity studies performed with an atmosphere–ocean general circulation model, Clim. Past, 12, 1313-1338, doi:10.5194/cp-12-1313-2016, 2016.

http://www.clim-past.net/12/1313/2016/

Abstract. During the Last Interglacial (LIG, ∼130–115 kiloyears (kyr) before present (BP)), the northern high latitudes were characterized by higher temperatures than those of the late Holocene and a lower Greenland Ice Sheet (GIS). However, the impact of a reduced GIS on the global climate has not yet been well constrained. In this study, we quantify the contribution of the GIS to LIG warmth by performing various sensitivity studies based on equilibrium simulations, employing the Community Earth System Models (COSMOS), with a focus on height and extent of the GIS. We present the first study on the effects of a reduction in the GIS on the surface temperature (TS) on a global scale and separate the contribution of astronomical forcing and changes in GIS to LIG warmth. The strong Northern Hemisphere summer warming of approximately 2 °C (with respect to pre-industrial) is mainly caused by increased summer insolation. Reducing the height by  ∼ 1300 m and the extent of the GIS does not have a strong influence during summer, leading to an additional global warming of only +0.24 °C compared to the purely insolation-driven LIG. The effect of a reduction in the GIS is, however, strongest during local winter, with up to +5 °C regional warming and with an increase in global average temperature of +0.48 °C.

In order to evaluate the performance of our LIG simulations, we additionally compare the simulated TS anomalies with marine and terrestrial proxy-based LIG temperature anomalies derived from three different proxy data compilations. Our model results are in good agreement with proxy records with respect to the warming pattern but underestimate the magnitude of temperature change when compared to reconstructions, suggesting a potential misinterpretation of the proxy records or deficits in our model. However, we are able to partly reduce the mismatch between model and data by additionally taking into account the potential seasonal bias of the proxy record and/or the uncertainties in the dating of the proxy records for the LIG thermal maximum. The seasonal bias and the uncertainty of the timing are estimated from new transient model simulations covering the whole LIG. The model–data comparison improves for proxies that represent annual mean temperatures when the GIS is reduced and when we take the local thermal maximum during the LIG (130–120 kyr BP) into account. For proxy data that represent summer temperatures, changes in the GIS are of minor importance for sea surface temperatures. However, the annual mean and summer temperature change over Greenland in the reduced GIS simulations seems to be overestimated as compared to the local ice core data, which could be related to the interpretation of the recorder system and/or the assumptions of GIS reduction. Thus, the question regarding the real size of the GIS during the LIG has yet to be answered.
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Re: Modelling the Anthropocene
« Reply #70 on: June 18, 2016, 05:50:10 PM »
Lightning flashes are projected to increase with continued global warming & the linked reference indicates that this will result in a change in the ozone distribution in the upper atmosphere, which in turn will change future climate change model projections (once they adopt the appropriate lightning parametrization.

Finney, D. L., Doherty, R. M., Wild, O., and Abraham, N. L.: The impact of lightning on tropospheric ozone chemistry using a new global lightning parametrisation, Atmos. Chem. Phys., 16, 7507-7522, doi:10.5194/acp-16-7507-2016, 2016.

http://www.atmos-chem-phys.net/16/7507/2016/

Abstract. A lightning parametrisation based on upward cloud ice flux is implemented in a chemistry–climate model (CCM) for the first time. The UK Chemistry and Aerosols model is used to study the impact of these lightning nitric oxide (NO) emissions on ozone. Comparisons are then made between the new ice flux parametrisation and the commonly used, cloud-top height parametrisation. The ice flux approach improves the simulation of lightning and the temporal correlations with ozone sonde measurements in the middle and upper troposphere. Peak values of ozone in these regions are attributed to high lightning NO emissions. The ice flux approach reduces the overestimation of tropical lightning apparent in this CCM when using the cloud-top approach. This results in less NO emission in the tropical upper troposphere and more in the extratropics when using the ice flux scheme. In the tropical upper troposphere the reduction in ozone concentration is around 5–10 %. Surprisingly, there is only a small reduction in tropospheric ozone burden when using the ice flux approach. The greatest absolute change in ozone burden is found in the lower stratosphere, suggesting that much of the ozone produced in the upper troposphere is transported to higher altitudes. Major differences in the frequency distribution of flash rates for the two approaches are found. The cloud-top height scheme has lower maximum flash rates and more mid-range flash rates than the ice flux scheme. The initial Ox (odd oxygen species) production associated with the frequency distribution of continental lightning is analysed to show that higher flash rates are less efficient at producing Ox; low flash rates initially produce around 10 times more Ox per flash than high-end flash rates. We find that the newly implemented lightning scheme performs favourably compared to the cloud-top scheme with respect to simulation of lightning and tropospheric ozone. This alternative lightning scheme shows spatial and temporal differences in ozone chemistry which may have implications for comparison between models and observations, as well as for simulation of future changes in tropospheric ozone.

Edit: I note that increasing concentrations of ozone in the atmosphere will increase the near future GWP of methane.
« Last Edit: June 18, 2016, 06:50:18 PM by AbruptSLR »
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Re: Modelling the Anthropocene
« Reply #71 on: June 24, 2016, 05:44:28 PM »
The linked article is entitled: "Adapting Weather Forecasting Techniques to Paleoclimate Studies", and an improvement in understanding paleoclimate should eventually lead to improved model forecasts:


https://eos.org/research-spotlights/adapting-weather-forecasting-techniques-to-paleoclimate-studies

Extract: "First results of the Last Millennium Climate Reanalysis Project demonstrate the potential of the method to improve historical climate estimates by linking proxy data with climate models."
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Re: Modelling the Anthropocene
« Reply #72 on: June 30, 2016, 12:10:32 AM »
As ACME is scheduled to start production runs beginning next month, I thought that it would be useful to link the pdf for the October 21–22, 2015 Workshop report entitled: "Accelerated Climate Modeling for Energy (ACME) – Atmospheric Radiation Measurement (ARM) Climate Research Facility – Atmospheric System Research (ASR) Coordination Workshop":


http://science.energy.gov/~/media/ber/pdf/workshop%20reports/CESD_ACME_ARM_ASR_workshopreport_web.pdf

See also:
http://asr.science.energy.gov/science/

Edit: Also the linked PowerPoint presentation entitled: "Land-Ice and Atmospheric Modeling at Sandia: the Albany/FELIX and Aeras Solvers" is associated with the ACME project:

http://slideplayer.com/slide/9165307/

Edit2: "For a video of preliminary model results (released in Dec 2015) see also:



« Last Edit: June 30, 2016, 12:52:27 AM by AbruptSLR »
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Re: Modelling the Anthropocene
« Reply #73 on: June 30, 2016, 11:04:31 PM »
The linked reference on documenting human-induced greening of northern extratropical land surfaces will be valuable in calibrating state-of-the-art ESM projections, such as those to come from ACME:

Jiafu Mao, Aurélien Ribes, Binyan Yan, Xiaoying Shi, Peter E. Thornton, Roland Séférian, Philippe Ciais, Ranga B. Myneni, Hervé Douville, Shilong Piao, Zaichun Zhu, Robert E. Dickinson, Yongjiu Dai, Daniel M. Ricciuto, Mingzhou Jin, Forrest M. Hoffman, Bin Wang, Mengtian Huang & Xu Lian (2016), "Human-induced greening of the northern extratropical land surface", Nature Climate Change, doi:10.1038/nclimate3056


http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3056.html


Abstract: "Significant land greening in the northern extratropical latitudes (NEL) has been documented through satellite observations during the past three decades. This enhanced vegetation growth has broad implications for surface energy, water and carbon budgets, and ecosystem services across multiple scales. Discernible human impacts on the Earth’s climate system have been revealed by using statistical frameworks of detection–attribution. These impacts, however, were not previously identified on the NEL greening signal, owing to the lack of long-term observational records, possible bias of satellite data, different algorithms used to calculate vegetation greenness, and the lack of suitable simulations from coupled Earth system models (ESMs). Here we have overcome these challenges to attribute recent changes in NEL vegetation activity. We used two 30-year-long remote-sensing-based leaf area index (LAI) data sets, simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm. Our findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. These results provide the first clear evidence of a discernible human fingerprint on physiological vegetation changes other than phenology and range shifts."
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Re: Modelling the Anthropocene
« Reply #74 on: July 06, 2016, 11:48:38 PM »
The linked reference indicates that climate change Integrated Assessment Models need to include cross-sectoral interactions:

Paula A. Harrison, Robert W. Dunford, Ian P. Holman & Mark D. A. Rounsevell (2016), "Climate change impact modelling needs to include cross-sectoral interactions", Nature Climate Change, doi:10.1038/nclimate3039


http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3039.html

Abstract: "Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale."
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Re: Modelling the Anthropocene
« Reply #75 on: July 13, 2016, 12:33:04 AM »
The linked reference discusses modeling efforts towards quantifying the economic cost associated with climatic "tipping points".  While the reference has some value it discounts the risk of a WAIS collapse this century by noting that most climate change models cannot account for cliff failures and hydrofracturing, and proceeds to base its findings on models that are incapable of matching the DeConto & Pollard (2016) findings that the WAIS could collapse before the GMST departure reaches 2.7C above pre-industrial levels:

Robert E. Kopp, Rachael Shwom, Gernot Wagner & Jiacan Yuan (2016), "Tipping elements and climate-economic shocks: Pathways toward integrated assessment", Earth's Future, DOI: 10.1002/2016EF000362.
 
http://onlinelibrary.wiley.com/doi/10.1002/2016EF000362/abstract
&
http://onlinelibrary.wiley.com/doi/10.1002/2016EF000362/epdf

Abstract: "The literature on the costs of climate change often draws a link between climatic ‘tipping points’ and large economic shocks, frequently called ‘catastrophes’. The phrase ‘tipping points’ in this context can be misleading. In popular and social scientific discourse, ‘tipping points’ involve abrupt state changes. For some climatic ‘tipping points,’ the commitment to a state change may occur abruptly, but the change itself may be rate-limited and take centuries or longer to realize. Additionally, the connection between climatic ‘tipping points’ and economic losses is tenuous, though emerging empirical and process-model-based tools provide pathways for investigating it. We propose terminology to clarify the distinction between ‘tipping points’ in the popular sense, the critical thresholds exhibited by climatic and social ‘tipping elements,’ and ‘economic shocks’. The last may be associated with tipping elements, gradual climate change, or non-climatic triggers. We illustrate our proposed distinctions by surveying the literature on climatic tipping elements, climatically sensitive social tipping elements, and climate-economic shocks, and we propose a research agenda to advance the integrated assessment of all three."

Extract: "… most ice sheet models do not include ice cliff collapse and hydrofracturing, which destabilize ice shelves and may greatly increase the rate of ice sheet mass loss [Pollard et al., 2015; DeConto and Pollard, 2016]."
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Re: Modelling the Anthropocene
« Reply #76 on: July 25, 2016, 08:27:30 PM »
Improvements (as cited in the linked reference) for integrated assessment models is sorely needed; however, I am concerned that such efforts will simply ignore Hansen's ice-climate feedback mechanism as being too abrupt for them to address.  Thus I suspect that there will likely be very little advance notice for such a climate hazard (especially with regard to the possibility of the WAIS beginning to collapse this century).

Robert E. Kopp, Rachael Shwom, Gernot Wagner, Jiacan Yuan. Tipping elements and climate-economic shocks: Pathways toward integrated assessment. Earth's Future, 2016; DOI: 10.1002/2016EF000362

http://onlinelibrary.wiley.com/doi/10.1002/2016EF000362/abstract?systemMessage=Wiley+Online+Library+will+be+unavailable+on+Saturday+30th+July+2016+from+08:00-11:00+BST+/+03:00-06:00+EST+/+15:00-18:00+SGT+for+essential+maintenance.Apologies+for+the+inconvenience.

Abstract: "The literature on the costs of climate change often draws a link between climatic ‘tipping points’ and large economic shocks, frequently called ‘catastrophes’. The phrase ‘tipping points’ in this context can be misleading. In popular and social scientific discourse, ‘tipping points’ involve abrupt state changes. For some climatic ‘tipping points,’ the commitment to a state change may occur abruptly, but the change itself may be rate-limited and take centuries or longer to realize. Additionally, the connection between climatic ‘tipping points’ and economic losses is tenuous, though emerging empirical and process-model-based tools provide pathways for investigating it. We propose terminology to clarify the distinction between ‘tipping points’ in the popular sense, the critical thresholds exhibited by climatic and social ‘tipping elements,’ and ‘economic shocks’. The last may be associated with tipping elements, gradual climate change, or non-climatic triggers. We illustrate our proposed distinctions by surveying the literature on climatic tipping elements, climatically sensitive social tipping elements, and climate-economic shocks, and we propose a research agenda to advance the integrated assessment of all three."
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Re: Modelling the Anthropocene
« Reply #77 on: July 25, 2016, 10:14:16 PM »
The linked (open access) reference discusses CMIP6, which will run through 2020 per the attached image.  As a side note, it is my personal opinion that frequently the authors of the reference tend to err on the side of least drama:

Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937-1958, doi:10.5194/gmd-9-1937-2016, 2016

http://www.geosci-model-dev.net/9/1937/2016/gmd-9-1937-2016.pdf

Abstract: "By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions:

– How does the Earth system respond to forcing?

– What are the origins and consequences of systematic model biases?

– How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios?

This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs."

See also:

http://www.wcrp-climate.org/index.php/wgcm-cmip/wgcm-cmip6
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Re: Modelling the Anthropocene
« Reply #78 on: July 26, 2016, 01:01:39 AM »
The linked research indicates that future integrate assessment model projections should include the impact of armed-conflict triggered by climate-related disasters:

Carl-Friedrich Schleussner, Jonathan F. Donges, Reik V. Donner and Hans Joachim Schellnhuber (July 25, 2016), "Armed-conflict risks enhanced by climate-related disasters in ethnically fractionalized countries", PNAS, doi: 10.1073/pnas.1601611113

http://www.pnas.org/content/early/2016/07/20/1601611113

Significance: "Ethnic divides play a major role in many armed conflicts around the world and might serve as predetermined conflict lines following rapidly emerging societal tensions arising from disruptive events like natural disasters. We find evidence in global datasets that risk of armed-conflict outbreak is enhanced by climate-related disaster occurrence in ethnically fractionalized countries. Although we find no indications that environmental disasters directly trigger armed conflicts, our results imply that disasters might act as a threat multiplier in several of the world’s most conflict-prone regions."

Abstract: "Social and political tensions keep on fueling armed conflicts around the world. Although each conflict is the result of an individual context-specific mixture of interconnected factors, ethnicity appears to play a prominent and almost ubiquitous role in many of them. This overall state of affairs is likely to be exacerbated by anthropogenic climate change and in particular climate-related natural disasters. Ethnic divides might serve as predetermined conflict lines in case of rapidly emerging societal tensions arising from disruptive events like natural disasters. Here, we hypothesize that climate-related disaster occurrence enhances armed-conflict outbreak risk in ethnically fractionalized countries. Using event coincidence analysis, we test this hypothesis based on data on armed-conflict outbreaks and climate-related natural disasters for the period 1980–2010. Globally, we find a coincidence rate of 9% regarding armed-conflict outbreak and disaster occurrence such as heat waves or droughts. Our analysis also reveals that, during the period in question, about 23% of conflict outbreaks in ethnically highly fractionalized countries robustly coincide with climatic calamities. Although we do not report evidence that climate-related disasters act as direct triggers of armed conflicts, the disruptive nature of these events seems to play out in ethnically fractionalized societies in a particularly tragic way. This observation has important implications for future security policies as several of the world’s most conflict-prone regions, including North and Central Africa as well as Central Asia, are both exceptionally vulnerable to anthropogenic climate change and characterized by deep ethnic divides."


See also:
https://www.theguardian.com/environment/2016/jul/25/disasters-linked-to-climate-can-increase-risk-of-armed-conflict

Extract: "Research found that 23% of violent clashes in ethnically divided places were connected to climate disasters"

&
https://www.washingtonpost.com/news/energy-environment/wp/2016/07/25/how-climate-disasters-can-drive-violent-conflict-around-the-world/

Extract: "It’s increasingly clear that the consequences of climate change won’t stop at just heat waves and sea-level rise. Scientists expect numerous social issues to arise around the world as well, such as food shortages, decreased water quality and forced migrations. And many experts now say that violence, war and other forms of human conflict may be driven or worsened by the effects of climate change."
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Re: Modelling the Anthropocene
« Reply #79 on: August 09, 2016, 07:36:47 PM »
Many people become confused by the dynamics of energy flux and regional temperature changes due to AGW; and the linked reference provides insights (using an energy balance decomposition of temperature changes for CMIP5) including:
"The three most important terms for intermodel differences in warming are the changes in the clear-sky greenhouse effect, clouds, and the net surface energy flux, making the largest contribution to the standard deviation of annual mean temperature change in 34, 29 and 20 % of the world, respectively. Changes in atmospheric energy flux convergence mostly damp intermodel variations of temperature change especially over the oceans. However, the opposite is true for example in Greenland and Antarctica, where the warming appears to be substantially controlled by heat transport from the surrounding sea areas."
Jouni Räisänen (06 August 2016), "An energy balance perspective on regional CO2-induced temperature changes in CMIP5 models", Climate Dynamics, pp 1-14, DOI: 10.1007/s00382-016-3277-2

http://rd.springer.com/article/10.1007%2Fs00382-016-3277-2

Abstract: "An energy balance decomposition of temperature changes is conducted for idealized transient CO2-only simulations in the fifth phase of the Coupled Model Intercomparison Project. The multimodel global mean warming is dominated by enhanced clear-sky greenhouse effect due to increased CO2 and water vapour, but other components of the energy balance substantially modify the geographical and seasonal patterns of the change. Changes in the net surface energy flux are important over the oceans, being especially crucial for the muted warming over the northern North Atlantic and for the seasonal cycle of warming over the Arctic Ocean. Changes in atmospheric energy flux convergence tend to smooth the gradients of temperature change and reduce its land-sea contrast, but they also amplify the seasonal cycle of warming in northern North America and Eurasia. The three most important terms for intermodel differences in warming are the changes in the clear-sky greenhouse effect, clouds, and the net surface energy flux, making the largest contribution to the standard deviation of annual mean temperature change in 34, 29 and 20 % of the world, respectively. Changes in atmospheric energy flux convergence mostly damp intermodel variations of temperature change especially over the oceans. However, the opposite is true for example in Greenland and Antarctica, where the warming appears to be substantially controlled by heat transport from the surrounding sea areas."
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Re: Modelling the Anthropocene
« Reply #80 on: August 16, 2016, 08:33:13 PM »
The two linked Nature Geoscience references respectively discuss the influence of the IPO, and the NAO, (both superimposed on Anthropogenic forcing) on Earth Systems.  Hopefully, findings from such research will improve future climate change model forecasts:

Yu Kosaka & Shang-Ping Xie (2016), "The tropical Pacific as a key pacemaker of the variable rates of global warming", Nature Geoscience, doi:10.1038/ngeo2770

http://www.nature.com/ngeo/journal/vaop/ncurrent/full/ngeo2770.html

Abstract: "Global mean surface temperature change over the past 120 years resembles a rising staircase: the overall warming trend was interrupted by the mid-twentieth-century big hiatus and the warming slowdown since about 1998. The Interdecadal Pacific Oscillation has been implicated in modulations of global mean surface temperatures, but which part of the mode drives the variability in warming rates is unclear. Here we present a successful simulation of the global warming staircase since 1900 with a global ocean–atmosphere coupled model where tropical Pacific sea surface temperatures are forced to follow the observed evolution. Without prescribed tropical Pacific variability, the same model, on average, produces a continual warming trend that accelerates after the 1960s. We identify four events where the tropical Pacific decadal cooling markedly slowed down the warming trend. Matching the observed spatial and seasonal fingerprints we identify the tropical Pacific as a key pacemaker of the warming staircase, with radiative forcing driving the overall warming trend. Specifically, tropical Pacific variability amplifies the first warming epoch of the 1910s–1940s and determines the timing when the big hiatus starts and ends. Our method of removing internal variability from the observed record can be used for real-time monitoring of anthropogenic warming."


&


Thomas L. Delworth, Fanrong Zeng, Gabriel A. Vecchi, Xiaosong Yang, Liping Zhang & Rong Zhang (2016), "The North Atlantic Oscillation as a driver of rapid climate change in the Northern Hemisphere", Nature Geoscience, Volume: 9, Pages: 509–512, doi:10.1038/ngeo2738

http://www.nature.com/ngeo/journal/v9/n7/full/ngeo2738.html

Abstract: "Pronounced climate changes have occurred since the 1970s, including rapid loss of Arctic sea ice, large-scale warming and increased tropical storm activity in the Atlantic. Anthropogenic radiative forcing is likely to have played a major role in these changes, but the relative influence of anthropogenic forcing and natural variability is not well established. The above changes have also occurred during a period in which the North Atlantic Oscillation has shown marked multidecadal variations. Here we investigate the role of the North Atlantic Oscillation in these rapid changes through its influence on the Atlantic meridional overturning circulation and ocean heat transport. We use climate models to show that observed multidecadal variations of the North Atlantic Oscillation can induce multidecadal variations in the Atlantic meridional overturning circulation and poleward ocean heat transport in the Atlantic, extending to the Arctic. Our results suggest that these variations have contributed to the rapid loss of Arctic sea ice, Northern Hemisphere warming, and changing Atlantic tropical storm activity, especially in the late 1990s and early 2000s. These multidecadal variations are superimposed on long-term anthropogenic forcing trends that are the dominant factor in long-term Arctic sea ice loss and hemispheric warming."
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Re: Modelling the Anthropocene
« Reply #81 on: August 19, 2016, 06:22:55 PM »
The linked reference identifies the occurrence of atmospheric rivers extending from the Maritime Continent to the Bering Strait as one factor contributing to Arctic Amplification.  Hopefully, CMIP6 will use such findings to better calibrate their model runs so that AR6 will account for (rather than ignore) this positive feedback mechanism:

Cory Baggett, Sukyoung Lee & Steven Feldstein (12 August 2016), "An investigation of the presence of atmospheric rivers over the North Pacific during planetary-scale wave life cycles and their role in Arctic warming", Journal of the Atmospheric Sciences, DOI: http://dx.doi.org/10.1175/JAS-D-16-0033.1

http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-16-0033.1

Abstract: "Heretofore, the Tropically Excited Arctic warMing mechanism (TEAM) put forward that localized tropical convection amplifies planetary-scale waves which transport sensible and latent heat into the Arctic – leading to an enhancement of downward infrared radiation and Arctic surface warming. In this study, an investigation is made into the previously unexplored contribution of the synoptic-scale waves and their attendant atmospheric rivers to the TEAM mechanism.
Reanalysis data is used to conduct a suite of observational analyses, trajectory calculations, and idealized model simulations. It is shown that localized tropical convection over the Maritime Continent precedes the peak of the planetary-scale wave life cycle by ~10 to 14 days. The Rossby wave source induced by the tropical convection excites a Rossby wave train over the North Pacific that amplifies the climatological December-March stationary waves. These amplified planetary-scale waves are baroclinic and transport sensible and latent heat poleward. During the planetary-scale wave life cycle, synoptic-scale waves are diverted northward over the central North Pacific. The warm conveyor belts associated with the synoptic-scale waves channel moisture from the subtropics into atmospheric rivers which ascend as they move poleward and penetrate into the Arctic near the Bering Strait. At this time, the synoptic-scale waves undergo cyclonic Rossby wave breaking which further amplifies the planetary-scale waves. The planetary-scale wave life cycle ceases as ridging over Alaska retrogrades westward. The ridging blocks additional moisture transport into the Arctic. However, sensible and latent heat remain elevated over the Arctic which enhances downward infrared radiation and maintains warm surface temperatures."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #82 on: August 25, 2016, 10:17:57 AM »
The GMD now has a special issue devoted to CMIP6:

Coupled Model Intercomparison Project Phase 6 (CMIP6) Experimental Design and Organization
Editor(s): GMD topical editors | Coordinator: V. Eyring

http://www.geosci-model-dev.net/special_issue590.html
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Re: Modelling the Anthropocene
« Reply #83 on: September 22, 2016, 09:44:52 PM »
The linked (open access) three part reference provides information about the "The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared".  Such information is important for calibrating Earth System Models:

Sussmann, R., Reichert, A., and Rettinger, M.: The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared – Part 1: Setup, uncertainty analysis, and assessment of far-infrared water vapor continuum, Atmos. Chem. Phys., 16, 11649-11669, doi:10.5194/acp-16-11649-2016, 2016.

http://www.atmos-chem-phys.net/16/11649/2016/

Abstract. Quantitative knowledge of water vapor radiative processes in the atmosphere throughout the terrestrial and solar infrared spectrum is still incomplete even though this is crucial input to the radiation codes forming the core of both remote sensing methods and climate simulations. Beside laboratory spectroscopy, ground-based remote sensing field studies in the context of so-called radiative closure experiments are a powerful approach because this is the only way to quantify water absorption under cold atmospheric conditions. For this purpose, we have set up at the Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) a long-term radiative closure experiment designed to cover the infrared spectrum between 400 and 7800 cm−1 (1.28–25 µm). As a benefit for such experiments, the atmospheric states at the Zugspitze frequently comprise very low integrated water vapor (IWV; minimum  =  0.1 mm, median  =  2.3 mm) and very low aerosol optical depth (AOD  =  0.0024–0.0032 at 7800 cm−1 at air mass 1). All instruments for radiance measurements and atmospheric-state measurements are described along with their measurement uncertainties. Based on all parameter uncertainties and the corresponding radiance Jacobians, a systematic residual radiance uncertainty budget has been set up to characterize the sensitivity of the radiative closure over the whole infrared spectral range. The dominant uncertainty contribution in the spectral windows used for far-infrared (FIR) continuum quantification is from IWV uncertainties, while T profile uncertainties dominate in the mid-infrared (MIR). Uncertainty contributions to near-infrared (NIR) radiance residuals are dominated by water vapor line parameters in the vicinity of the strong water vapor bands. The window regions in between these bands are dominated by solar Fourier transform infrared (FTIR) calibration uncertainties at low NIR wavenumbers, while uncertainties due to AOD become an increasing and dominant contribution towards higher NIR wavenumbers. Exceptions are methane or nitrous oxide bands in the NIR, where the associated line parameter uncertainties dominate the overall uncertainty.

As a first demonstration of the Zugspitze closure experiment, a water vapor continuum quantification in the FIR spectral region (400–580 cm−1) has been performed. The resulting FIR foreign-continuum coefficients are consistent with the MT_CKD 2.5.2 continuum model and also agree with the most recent atmospheric closure study carried out in Antarctica. Results from the first determination of the NIR water vapor continuum in a field experiment are detailed in a companion paper (Reichert and Sussmann, 2016) while a novel NIR calibration scheme for the underlying FTIR measurements of incoming solar radiance is presented in another companion paper (Reichert et al., 2016).




Reichert, A., Rettinger, M., and Sussmann, R.: The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared – Part 2: Accurate calibration of high spectral-resolution infrared measurements of surface solar radiation, Atmos. Meas. Tech., 9, 4673-4686, doi:10.5194/amt-9-4673-2016, 2016.
http://www.atmos-meas-tech.net/9/4673/2016/

Abstract. Quantitative knowledge of water vapor absorption is crucial for accurate climate simulations. An open science question in this context concerns the strength of the water vapor continuum in the near infrared (NIR) at atmospheric temperatures, which is still to be quantified by measurements. This issue can be addressed with radiative closure experiments using solar absorption spectra. However, the spectra used for water vapor continuum quantification have to be radiometrically calibrated. We present for the first time a method that yields sufficient calibration accuracy for NIR water vapor continuum quantification in an atmospheric closure experiment. Our method combines the Langley method with spectral radiance measurements of a high-temperature blackbody calibration source (<  2000 K). The calibration scheme is demonstrated in the spectral range 2500 to 7800 cm−1, but minor modifications to the method enable calibration also throughout the remainder of the NIR spectral range. The resulting uncertainty (2σ) excluding the contribution due to inaccuracies in the extra-atmospheric solar spectrum (ESS) is below 1 % in window regions and up to 1.7 % within absorption bands. The overall radiometric accuracy of the calibration depends on the ESS uncertainty, on which at present no firm consensus has been reached in the NIR. However, as is shown in the companion publication Reichert and Sussmann (2016), ESS uncertainty is only of minor importance for the specific aim of this study, i.e., the quantification of the water vapor continuum in a closure experiment. The calibration uncertainty estimate is substantiated by the investigation of calibration self-consistency, which yields compatible results within the estimated errors for 91.1 % of the 2500 to 7800 cm−1 range. Additionally, a comparison of a set of calibrated spectra to radiative transfer model calculations yields consistent results within the estimated errors for 97.7 % of the spectral range.


Reichert, A. and Sussmann, R.: The Zugspitze radiative closure experiment for quantifying water vapor absorption over the terrestrial and solar infrared – Part 3: Quantification of the mid- and near-infrared water vapor continuum in the 2500 to 7800 cm−1 spectral range under atmospheric conditions, Atmos. Chem. Phys., 16, 11671-11686, doi:10.5194/acp-16-11671-2016, 2016.

http://www.atmos-chem-phys.net/16/11671/2016/

Abstract. We present a first quantification of the near-infrared (NIR) water vapor continuum absorption from an atmospheric radiative closure experiment carried out at the Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.). Continuum quantification is achieved via radiative closure using radiometrically calibrated solar Fourier transform infrared (FTIR) absorption spectra covering the 2500 to 7800 cm−1 spectral range. The dry atmospheric conditions at the Zugspitze site (IWV 1.4 to 3.3 mm) enable continuum quantification even within water vapor absorption bands, while upper limits for continuum absorption can be provided in the centers of window regions. Throughout 75 % of the 2500 to 7800 cm−1 spectral range, the Zugspitze results agree within our estimated uncertainty with the widely used MT_CKD 2.5.2 model (Mlawer et al., 2012). In the wings of water vapor absorption bands, our measurements indicate about 2–5 times stronger continuum absorption than MT_CKD, namely in the 2800 to 3000 cm−1 and 4100 to 4200 cm−1 spectral ranges. The measurements are consistent with the laboratory measurements of Mondelain et al. (2015), which rely on cavity ring-down spectroscopy (CDRS), and the calorimetric–interferometric measurements of Bicknell et al. (2006). Compared to the recent FTIR laboratory studies of Ptashnik et al. (2012, 2013), our measurements are consistent within the estimated errors throughout most of the spectral range. However, in the wings of water vapor absorption bands our measurements indicate typically 2–3 times weaker continuum absorption under atmospheric conditions, namely in the 3200 to 3400, 4050 to 4200, and 6950 to 7050 cm−1 spectral regions.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #84 on: September 28, 2016, 05:52:30 PM »
The devil is in the details, and the linked reference is entitled: "Characterizing And Understanding Systematic Biases In The Vertical Structure Of Clouds In CMIP5/CFMIP2 Models".  I suspect that when such systemic biases are corrected the net resulting contribution to feedback will be positive:

G. Cesana & D. E. Waliser (27 September 2016), "Characterizing And Understanding Systematic Biases In The Vertical Structure Of Clouds In CMIP5/CFMIP2 Models", Geophysical Research Letters, DOI: 10.1002/2016GL070515

http://onlinelibrary.wiley.com/doi/10.1002/2016GL070515/abstract

Abstract: "From a traditional low-, mid- and high-cloud “layered” perspective as well as a more detailed “level” perspective (40 levels), we compare the vertical distribution of clouds in twelve general circulation models (GCMs) against the GCM-Oriented Cloud-Aerosols Lidar and Infrared Pathfinder Satellite Observations Cloud Product (CALIPSO-GOCCP) using a satellite simulator approach. The “layered” perspective shows that models exhibit the similar regional biases: an overestimate (underestimate) of high-clouds over oceans (continents) in the tropics and a strong underestimate of low-clouds over stratocumulus regions. Although high-clouds are too infrequent on average, the “level” perspective reveals that high-level clouds fill too many upper levels of the column when present (geometrically too thick), suggesting an overestimation of the cloud overlap. Compositing by dynamical regimes and large-scale relative humidity shows that the models tend to have too many high-level clouds in moist environments, and too few boundary-layer clouds in dry environments regardless of dynamical regimes."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #85 on: September 30, 2016, 10:10:23 PM »
The linked reference indicates that changes in extratropical clouds associated with a reduction in high latitude albedo can impact atmospheric heat transport via changes in the Hadley cell:

Nicole Feldl, Simona Bordoni & Timothy M. Merlis (September 28 2016), "Coupled high-latitude climate feedbacks and their impact on atmospheric heat transport", Journal of Climate, DOI: http://dx.doi.org/10.1175/JCLI-D-16-0324.1


http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0324.1

Abstract: "The response of atmospheric heat transport to anthropogenic warming is determined by the anomalous meridional energy gradient. Feedback analysis offers a characterization of that gradient and hence reveals how uncertainty in physical processes may translate into uncertainty in the circulation response. However, individual feedbacks do not act in isolation. Anomalies associated with one feedback may be compensated by another, as is the case for the positive water vapor and negative lapse rate feedbacks in the tropics. Here we perform a set of idealized experiments in an aquaplanet model to evaluate the coupling between the surface albedo feedback and other feedbacks, including the impact on atmospheric heat transport. In the tropics, the dynamical response manifests as changes in the intensity and structure of the overturning Hadley circulation. Only half of the range of Hadley cell weakening exhibited in these experiments is found to be attributable to imposed, systematic variations in the surface albedo feedback. Changes in extratropical clouds that accompany the albedo changes explain the remaining spread. The feedback-driven circulation changes are compensated by eddy energy flux changes, which reduce the overall spread among experiments. These findings have implications for the efficiency with which the climate system, including tropical circulation and the hydrological cycle, adjusts to high latitude feedbacks, over climate states that range from perennial or seasonal ice to ice-free conditions in the Arctic."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #86 on: October 03, 2016, 03:43:07 PM »
The linked open access reference provides an excellent summary of cloud feedback processes and discusses means to further reduce uncertainties associated with this complex topic:

Gettelman, A. & Sherwood, S.C. (2016), "Processes Responsible for Cloud Feedback", Curr Clim Change Rep,  doi:10.1007/s40641-016-0052-8


http://rd.springer.com/article/10.1007%2Fs40641-016-0052-8?wt_mc=Affiliate.CommissionJunction.3.EPR1089.DeepLink

Abstract: "Cloud feedback on global climate is determined by the combined action of multiple processes that have different relevance in different cloud regimes. This review lays out the framework for cloud feedback and highlights recent advances and outstanding issues. A consensus is emerging on large-scale controls on cloud feedback. Recent work has made significant progress in the understanding and observationally constraining the local response of shallow clouds. But significant uncertainties remain in microphysical mechanisms for cloud feedback. Important microphysical mechanisms include cloud phase changes, precipitation processes and even aerosol distributions. The treatment of these processes varies across climate models and may contribute to greater spread in feedbacks across models as models advance. Future work will need to try to bound the range of possible cloud microphysical feedback mechanisms and seek observational constraints on them."

“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

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Re: Modelling the Anthropocene
« Reply #87 on: October 13, 2016, 05:36:22 PM »
The linked reference helps to quantify the role of cloud radiative heating with the atmosphere; which is not fully modeled in CMIP5; while this influence can of particular importance in regional areas like the Equatorial Pacific:

Bryce E. Harrop & Dennis L. Hartmann (31 August 2016), "The role of cloud radiative heating within the atmosphere on the high cloud amount and top-of-atmosphere cloud radiative effect", JAMES, DOI: 10.1002/2016MS000670


http://onlinelibrary.wiley.com/doi/10.1002/2016MS000670/full

Abstract: "The effect of cloud-radiation interactions on cloud properties is examined in the context of a limited-domain cloud-resolving model. The atmospheric cloud radiative effect (ACRE) influences the areal extent of tropical high clouds in two distinct ways. The first is through direct radiative destabilization of the elevated cloud layers, mostly as a result of longwave radiation heating the cloud bottom and cooling the cloud top. The second effect is radiative stabilization, whereby cloud radiative heating of the atmospheric column stabilizes the atmosphere to deep convection. In limited area domain simulations, the stabilizing (or indirect) effect is the dominant role of the cloud radiative heating, thus reducing the cloud cover in simulations where ACRE is included compared to those where it is removed. Direct cloud radiative heating increases high cloud fraction, decreases mean cloud optical depth, and increases cloud top temperature. The indirect cloud radiative heating decreases high cloud fraction, but also decreases mean cloud optical depth and increases cloud top temperature. The combination of these effects increases the top-of-atmosphere cloud radiative effect. In mock-Walker circulation experiments, the decrease in high cloud amount owing to radiative stabilization tends to cancel out the increase in high cloud amount owing to the destabilization within the cloud layer. The changes in cloud optical depth and cloud top pressure, however, are similar to those produced in the limited area domain simulations."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #88 on: October 13, 2016, 05:46:56 PM »
The linked reference discuss how as atmospheric moisture increases cloud radiative cooling can decrease in an unstable fashion (particularly in the tropics).  This research indicates a need to update current climate models to adequately model this effect:

Tom Beucler & Timothy W. Cronin (11 October 2016), "Moisture-radiative cooling instability", JAMES, DOI: 10.1002/2016MS000763

http://onlinelibrary.wiley.com/doi/10.1002/2016MS000763/full

Abstract: "Radiative-convective equilibrium (RCE)—the statistical equilibrium state of the atmosphere where convection and radiation interact in the absence of lateral transport—is widely used as a basic-state model of the tropical atmosphere. The possibility that RCE may be unstable to development of large-scale circulation has been raised by recent modeling, theoretical, and observational studies, and could have profound consequences for our understanding of tropical meteorology and climate. Here, we study the interaction between moisture and radiative cooling as a contributor to instability of RCE. We focus on whether the total atmospheric radiative cooling decreases with column water vapor; this condition, which we call moisture-radiative cooling instability (MRCI), provides the potential for unstable growth of moist or dry perturbations. Analytic solutions to the gray-gas radiative transfer equations show that MRCI is satisfied when the total column optical depth—linked to column water vapor—exceeds a critical threshold. Both the threshold and the growth rate of the instability depend strongly on the shape of the water vapor perturbation. Calculations with a realistic radiative transfer model confirm the existence of MRCI for typical tropical values of column water vapor, but show even stronger dependence on the vertical structure of water vapor perturbation. Finally, we analyze the sensitivity of atmospheric radiative cooling to variability in column water vapor in observed tropical soundings. We find that clear-sky MRCI is satisfied across a range of locations and seasons in the real tropical atmosphere, with a partial growth rate of ∼1 month."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #89 on: October 17, 2016, 05:14:31 PM »
It is my general feeling that so many climate change projections err on the side of least drama that it makes most risk assessments ineffective.  Nevertheless, I provide the following linked article that addresses how to build climate change risks into such assessments:

Coletti, A., De Nicola, A. & Villani, M.L. (2016), "Building climate change into risk assessments", Nat Hazards  84: 1307. doi:10.1007/s11069-016-2487-6


http://rd.springer.com/article/10.1007%2Fs11069-016-2487-6?wt_mc=Affiliate.CommissionJunction.3.EPR1089.DeepLink&utm_medium=affiliate&utm_source=commission_junction&utm_campaign=3_nsn6445_deeplink&utm_content=deeplink

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Re: Modelling the Anthropocene
« Reply #90 on: October 20, 2016, 05:19:55 PM »
The linked reference takes a large-scale "interplanetary" viewpoint on understanding the technosphere as an emergent new Earth system:

Bronislaw Szerszynski (October 19, 2016), "Viewing the technosphere in an interplanetary light", The Anthropocene Review 2053019616670676,  doi:10.1177/2053019616670676

http://anr.sagepub.com/content/early/2016/10/18/2053019616670676.abstract

Abstract: "I argue that discussion about the ‘technosphere’ as an emergent new Earth system needs to be situated within wider reflection about how technospheres might arise on other worlds. Engaging with astrobiological speculation about ‘exo-technospheres’ can help us to understand whether technospheres are likely, what their preconditions might be, and whether they endure. Engaging with science fiction can help us to avoid observer biases that encourage linear assumptions about the preconditions and emergence of technospheres. Exploring earlier major transitions in Earth’s evolution can shed light on the shifting distribution of metabolic and reproductive powers between the human and technological parts of the contemporary technosphere. The long-term evolution of technical objects also suggests that they have shown a tendency to pass through their own major transitions in their relation to animality. Such reflection can shed new light on the nature and likely future development of the Earth’s technosphere."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #91 on: December 14, 2016, 12:37:57 AM »
The linked reference discusses how the Pacific Northwest National Laboratory has an improved statistical representation of clouds in a climate model.

Mikhail Ovchinnikov et al. Vertical overlap of probability density functions of cloud and precipitation hydrometeors, Journal of Geophysical Research: Atmospheres (2016). DOI: 10.1002/2016JD025158

http://onlinelibrary.wiley.com/doi/10.1002/2016JD025158/abstract;jsessionid=E9709CEDF25DA1CFC3CDE8C5A584C95A.f04t02?systemMessage=Wiley+Online+Library+will+be+unavailable+on+Saturday+17th+December+2016+at+09%3A00+GMT%2F+04%3A00+EST%2F+17%3A00+SGT+for+4hrs+due+to+essential+maintenance.Apologies+for+the+inconvenience

Abstract: "Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When subcolumns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified by Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3-D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species—a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the subcolumn generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #92 on: January 07, 2017, 01:15:49 AM »
Currently consensus climate change model projections do not clearly identify the risk of meaningful abrupt climate change this century.  The linked reference discusses efforts to make progress to more clearly identify such potential risks:

Sebastian Bathiany, Henk Dijkstra, Michel Crucifix, Vasilis Dakos, Victor Brovkin, Mark S. Williamson, Timothy M. Lenton & Marten Scheffer (2016), "Beyond bifurcation – using complex models to understand and predict abrupt climate change", Dynamics and Statistics of the Climate System, DOI: https://doi.org/10.1093/climsys/dzw004

https://academic.oup.com/climatesystem/article/doi/10.1093/climsys/dzw004/2562885/Beyond-bifurcation-using-complex-models-to

or

http://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/climatesystem/PAP/10.1093_climsys_dzw004/2/dzw004.pdf?Expires=1484090692&Signature=OU5CJq40-BAF7TUuvDW7b~ze0Y3umsbKCcFMppiFuYltT1Sda8-W5CRFwC~DbJRM-PYs51uI2lS4kBO-AP0FsnvCS98OlekOoJrKQZftL1dwlFFCnqaNvTdCAqJDpkQX99YtDLm4FvNfCPn21SH2OdW0AneZAMCJLru-U3~D7IdFbJZr6rDrjkE5lB9HWkhGvCaecDmFGfklhzyDsH3MFvCcRgtqvQlNfwJL8HebsouM1A4eIszFr6Q4ZKDL9QzByPHhwRjOV7qt~Nn53lUiiEdunY8rXJdLXs78s09CBBJ2h3NT-E0QJY~jTRdBs4ogkFmXJqzpPoCIG6YbErjoWw__&Key-Pair-Id=APKAIUCZBIA4LVPAVW3Q

Abstract: "Research on the possibility of future abrupt climate change has been popularised under the term “tipping points”, and has often been motivated by using simple, low-dimensional, concepts. These include the iconic fold bifurcation, where abrupt change occurs when a stable equilibrium is lost, and early warning signals of such a destabilisation that can be derived based on a simple stochastic model approach. In this paper we review the challenges and limitations that are associated with this view, and we discuss promising research paths to explore the causes and the likelihood of abrupt changes in future climate.

We focus on several climate system components and ecosystems that have been proposed as candidates of tipping points, with an emphasis on ice sheets, the Atlantic Ocean circulation, vegetation in North Africa, and Arctic sea ice. In most example cases, multiple equilibria found in simple models do not appear in complex models or become more difficult to find, while the potential for abrupt change still remains. We also discuss how the low-dimensional logic of current methods to detect and interpret the existence of multiple equilibria can fail in complex models. Moreover, we highlight promising methods to detect abrupt shifts, and to obtain information about the mechanisms behind them. These methods include linear approaches such as statistical stability indicators and radiative feedback analysis, as well as non-linear approaches to detect dynamical transitions and infer the causality behind events.

Given the huge complexity of comprehensive process-based climate models and the non-linearity and regional peculiarities of the processes involved, the uncertainties associated with the possible future occurrence of abrupt shifts are large and not well quantified. We highlight the potential of data mining approaches to tackle this problem, and finally discuss how the scientific community can collaborate to make efficient progress in understanding abrupt climate shifts."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

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Re: Modelling the Anthropocene
« Reply #93 on: January 07, 2017, 01:37:27 AM »
Interesting paper.  I have only dealt with fluid dynamic instabilities in simple systems close to equilibrium , I wonder how large departures from equilibrium ( due to our ever increasing radiative forcing )  and the properties of non equilibrium thermodynamics can affect our ability to study abrupt changes in the earth system. 
“You can know the name of a bird in all the languages of the world, but when you're finished, you'll know absolutely nothing whatever about the bird... So let's look at the bird and see what it's doing -- that's what counts.”
― Richard P. Feynman

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Re: Modelling the Anthropocene
« Reply #94 on: January 07, 2017, 03:20:04 AM »
Interesting paper.  I have only dealt with fluid dynamic instabilities in simple systems close to equilibrium , I wonder how large departures from equilibrium ( due to our ever increasing radiative forcing )  and the properties of non equilibrium thermodynamics can affect our ability to study abrupt changes in the earth system.

Climate change is wicked problem, and depending on the complexity (or wickedness) of such problems, solutions to such problems may be uncalculatable in reasonable timespan and thus require alternate approximate approaches/strategies such as those discussed in the following Wikipedia article focused on social policy planning:

https://en.wikipedia.org/wiki/Wicked_problem

However, science has advanced sense C. West Churchman introduced the term "wick problem", and this post focuses on how chaos theory, strange attractors, information networks and energy landscapes can be used to create and calibrate alternate models for wick problems (including better understanding how systemic isolation leads to a lack of human willpower to effective tackle climate change)

The first linked article is entitled: "A mathematical view on personality"; and it introduces the concept of how attractors can be used to model the human psyche within a network (including the use of energy landscape concepts).

http://blogs.plos.org/neuro/2016/03/21/a-mathematical-view-on-personality-by-solve-saebo/


Extract: "Interestingly, more diffuse properties of the human psyche, like personality (Van Eenwyk, 1997) and consciousness (Tononi, 2004) may, in fact, be connected to mathematical properties of networks, and in this post I will focus on what mathematics can teach us about these matters.

In mathematics there are complex models for information transfer across networks called attractor networks, and the neural network of our brain appears to be well approximated by these models

Attractor networks are built from nodes (for example neurons) which typically are recurrently linked (loops) with edges (like synaptic connections), and the dynamics of the network tend to stabilize at least locally to certain patterns. These stable patterns are the attractors. For example, a memory stored in long time memory may be considered as a so-called point attractor, a subnetwork of strongly connected neurons.

The point attractors are low-energy states in an energy landscape with surrounding basins of attraction, much like hillsides surrounding the bottom of a valley, as shown in the figure below. {see the first attached image}

Also other types of mathematical attractors exist, like line-, plane- and cyclic attractors, and these have been used to explain neural responses like eye-vision control and cyclic motor control, like walking and chewing (Eliasmith, 2005).
Common to these attractors are their stability and predictability, and this is good with regard to having stable memory and stable bodily control, but what about personality? Is personality also an attractor? Do we all have our basins of attraction, which pulls our personality towards stable behavior?

Probably yes, but if you think about it, personality is a more unpredictable property than memory and body control. We think we know someone, and the suddenly they behave in an unexpected manner. Still, the overall personality seems to be more or less stable. How can something be both stable and unpredictable at the same time?

Well there is another class of attractors that may occur in attractor networks. These are the strange (or chaotic) attractors, and they are exactly that, partly stable and partly unpredictable. We say they are bounded, but non-repeating.

A famous example is the Lorenz attractor discovered by Edward Lorenz while he was programming his “weather machine” where typical weather patterns appeared, but never repeated themselves. In the figure below {see the second attached image} the blue curve is pulled towards the red strange attractor state, and once it enters the attractor, it is bound to follow a certain pattern, though it never repeats itself.

The discovery of strange attractors led to the development of chaos theory and fractal geometry in mathematics. Many phenomena around us may develop smoothly in linear predictable fashions until a certain border is reached, at which point a chaotic state appears before a new order may be settled."


The second linked reference cites the development of a dissipative strange attractor that coexists with an invariant conservative torus that can be used to better model brain dynamics.

Artuor Tozzi and James F. Peters (2016), "TOWARDS EQUATIONS FOR BRAIN DYNAMICS AND THE CONCEPT OF EXTENDED CONNECTOME"

http://rxiv.org/pdf/1609.0045v1.pdf

Abstract: "The brain is a system at the edge of chaos equipped with nonlinear dynamics and functional energetic landscapes.  However, still doubts exist concerning the type of attractors or the trajectories followed by particles in the nervous phase space. Starting from an unusual system governed by differential equations in which a dissipative strange attractor coexists with an invariant conservative torus, we developed a 3D model of brain phase space which has the potential to be operationalized and assessed empirically. We achieved a system displaying both a torus and a strange attractor, depending just on the initial conditions. Further, the system generates a funnel-like attractor equipped with a fractal structure. Changes in three easily detectable brain phase parameters (log frequency, excitatory/inhibitory ratio and fractal slope) lead to modifications in funnel’s breadth or in torus/attractor superimposition: it explains a large repertoire of brain functions and activities, such as sensations/perceptions, memory and self-generated thoughts."

Extract: "Starting from the unusual Sprott’s system of ODEs, we built a system equipped with both a conservative torus and a dissipative strange attractor. When a moving particle starts its trajectory from a given position x,y,z in the 3D nervous phase space, we may predict whether it will fall in the torus or into the strange attractor. The funnel shape is fractal, and not just a simple fixed-point attractor. A narrower funnel means that the trajectory is constrained towards a small zone of the phase space. When the two structures are closely superimposed, we might hypothesize a state of phase transition at the edge of the chaos, equipped with high symmetry, in which it is difficult to evaluate every single initial position: a slightly change in the starting point could indeed lead to completely different outcomes. When the torus and the strange attractor are clearly splitted, a single starting point gives rise to a sharp outcome. It means that in the latter case, the two conformations are neatly separated, as if the system went out of phase transition and a symmetry breaking occurred."

The third linked reference develops the concept of an attractor network to better understand how to calibrate nonlinear dynamical networks.
Wang et al (2016), "A geometrical approach to control and controllability of nonlinear dynamical networks", Nature communications 7, Article No. 11323, doi: 10.1038/ncomms11323.


http://www.nature.com/articles/ncomms11323


The fourth linked reference and the associated fifth linked article, discuss a new efficient Monte Carlo method that can be used to more efficiently find solutions to models of wick problems:

Stefano Martiniani et al. Structural analysis of high-dimensional basins of attraction, Physical Review E (2016). DOI: 10.1103/PhysRevE.94.031301


http://journals.aps.org/pre/abstract/10.1103/PhysRevE.94.031301

Abstract: "We propose an efficient Monte Carlo method for the computation of the volumes of high-dimensional bodies with arbitrary shape. We start with a region of known volume within the interior of the manifold and then use the multistate Bennett acceptance-ratio method to compute the dimensionless free-energy difference between a series of equilibrium simulations performed within this object. The method produces results that are in excellent agreement with thermodynamic integration, as well as a direct estimate of the associated statistical uncertainties. The histogram method also allows us to directly obtain an estimate of the interior radial probability density profile, thus yielding useful insight into the structural properties of such a high-dimensional body. We illustrate the method by analyzing the effect of structural disorder on the basins of attraction of mechanically stable packings of soft repulsive spheres."


The linked article is entitled: "New method for making effective calculations in 'high-dimensional space'".

http://phys.org/news/2016-10-method-effective-high-dimensional-space.html


Extract: " Researchers have developed a new method for making effective calculations in "high-dimensional space" – and proved its worth by using it to solve a 93-dimensional problem.


Those include, for example, trying to model the likely shape and impact of a decaying ecosystem, such as a developing area of deforestation, or the potential effect of different levels of demand on a power grid.


"There is a very large class of problems that can be solved through the sort of approach that we have devised," Martiniani said. "It opens up a whole world of possibilities in the study of things like dynamical systems, chemical structure prediction, or artificial neural networks."


The set of initial conditions leading to this stable state is called a "basin of attraction". The fundamental theory is that, if the volume of each basin of attraction can be calculated, then this begins to provide some sort of indication of the probability of a given state's occurrence."
« Last Edit: May 29, 2017, 11:19:28 PM by AbruptSLR »
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AbruptSLR

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Re: Modelling the Anthropocene
« Reply #95 on: February 01, 2017, 04:02:31 AM »
The linked reference discusses the importance of correctly modeling vegetation processes in ESM w.r.t. Fast precipitation response to carbon dioxide forcing:

DeAngelis AM, Qu X & Hall A  (2016), "Importance of Vegetation Processes for Model Spread in the Fast Precipitation Response to CO2 Forcing." Geophysical Research Letters.;43:12550-12559, DOI: 10.1002/2016GL071392

http://onlinelibrary.wiley.com/doi/10.1002/2016GL071392/full

Abstract: “In the current generation of climate models, the projected increase in global precipitation over the 21st century ranges from 2% to 10% under a high-emission scenario. Some of this uncertainty can be traced to the rapid response to carbon dioxide (CO2) forcing. We analyze an ensemble of simulations to better understand model spread in this rapid response. A substantial amount is linked to how the land surface partitions a change in latent versus sensible heat flux in response to the CO2-induced radiative perturbation; a larger increase in sensible heat results in a larger decrease in global precipitation. Model differences in the land surface response appear to be strongly related to the vegetation response to increased CO2, specifically, the closure of leaf stomata. Future research should thus focus on evaluation of the vegetation physiological response, including stomatal conductance parameterizations, for the purpose of constraining the fast response of Earth’s hydrologic cycle to CO2 forcing.”
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #96 on: February 09, 2017, 07:36:25 PM »
The linked reference cites progress being made in the application of modeling Lorenz atmospheric attractors (chaos theory) focused on the North Atlantic.  Such research may someday help to better define climate sensitivity.

Davide Faranda, Gabriele Messori & Pascal Yiou (2017), "Dynamical proxies of North Atlantic predictability and extremes", Nature, Scientific Reports 7, Article number: 41278, doi:10.1038/srep41278

https://hal.archives-ouvertes.fr/hal-01340301/document

Abstract: "Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns. These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: “the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid”. The average dimension D of the attractor corresponds to the number of degrees of freedom sufficient to describe the atmospheric circulation. However, obtaining reliable estimates of D has proved challenging . Moreover, D does not provide information on transient atmospheric motions, which lead to weather extremes . Using recent developments in dynamical systems theory, we show that such motions can be classified through instantaneous rather than average properties of the attractor. The instantaneous properties are uniquely determined by instantaneous dimension and stability. Their extreme values correspond to specific atmospheric patterns, and match extreme weather occurrences. We further show the existence of a significant correlation between the time series of instantaneous stability and dimension and the mean spread of sea-level pressure fields in an operational ensemble weather forecast at steps of over two weeks. We believe this method provides an efficient and practical way of evaluating and informing operational weather forecasts."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Modelling the Anthropocene
« Reply #97 on: February 10, 2017, 07:53:08 PM »
The linked reference is entitled: "The Anthropocene equation".  The associated image implies that climate sensitivity in the Anthropocene will likely be higher than in the paleorecord due the action of climate attractors.

http://journals.sagepub.com/doi/full/10.1177/2053019616688022

Extract: "The dominant external forces influencing the rate of change of the Earth System have been astronomical and geophysical during the planet’s 4.5-billion-year existence. In the last six decades, anthropogenic forcings have driven exceptionally rapid rates of change in the Earth System. This new regime can be represented by an ‘Anthropocene equation’, where other forcings tend to zero, and the rate of change under human influence can be estimated. Reducing the risk of leaving the glacial–interglacial limit cycle of the late Quaternary for an uncertain future will require, in the first instance, the rate of change of the Earth System to become approximately zero."
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Re: Modelling the Anthropocene
« Reply #98 on: February 12, 2017, 06:07:27 PM »
The linked article entitled: "Humans causing climate to change 170 times faster than natural forces", provides back-up discussion to my Reply #97:

https://www.skepticalscience.com/2017-SkS-Weekly-Digest_06.html
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Re: Modelling the Anthropocene
« Reply #99 on: February 14, 2017, 08:15:56 PM »
The linked reference discusses efforts to make model calibration more transparent.

Schmidt, G. A., Bader, D., Donner, L. J., Elsaesser, G. S., Golaz, J.-C., Hannay, C., Molod, A., Neale, R., and Saha, S.: Practice and philosophy of climate model tuning across six U.S. modeling centers, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2017-30, in review, 2017.

http://www.geosci-model-dev-discuss.net/gmd-2017-30/

Abstract. Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major U.S. climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present day radiative imbalance vs. the implied balance in the pre-industrial as a target.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson