Please support this Forum and Neven's Blog

Author Topic: Modelling the Anthropocene  (Read 25761 times)

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #100 on: February 18, 2017, 04:10:21 PM »
The linked (open access) reference indicates that the current IPCC assessment models miss critical dynamic human-earth systems feedback mechanisms that means that our current assessments significantly underestimate coming impacts (see image of different types of possible collapses under our influence).

Safa Motesharrei et al, Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems, National Science Review (2016). DOI: 10.1093/nsr/nww081 

https://academic.oup.com/nsr/article-lookup/doi/10.1093/nsr/nww081

Abstract: “Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections. This makes current models likely to miss important feedbacks in the real Earth–Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth–Human system models for devising effective science-based policies and measures to benefit current and future generations.”

Significance Statement: “The Human System has become strongly dominant within the Earth System in many different ways. However, in current models that explore the future of humanity and environment, and guide policy, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates such as United Nations (UN) population projections. This makes the models likely to miss important feedbacks in the real Earth–Human system that may result in unexpected outcomes requiring very different policy interventions. The importance of humanity's sustainability challenges calls for collaboration of natural and social scientists to develop coupled Earth–Human system models for devising effective science-based policies and measures.”

See also the associated linked article entitled: “It's more than just climate change”.

https://phys.org/news/2017-02-climate_1.html


Extract: “Co-author Matthias Ruth, Director and Professor at the School of Public Policy and Urban Affairs, Northeastern University, said: "The result of not dynamically modeling these critical Human-Earth System feedbacks would be that the environmental challenges humanity faces may be significantly underestimated. Moreover, there's no explicit role given to policies and investments to actively shape the course in which the dynamics unfold. Rather, as the models are designed now, any intervention—almost by definition—comes from the outside and is perceived as a cost. Such modeling, and the mindset that goes with it, leaves no room for creativity in solving some of the most pressing challenges."

"The paper correctly highlights that other human stressors, not only the climate ones, are very important for long-term sustainability, including the need to reduce inequality'', said Carlos Nobre (not a co-author), one of the world's leading Earth System scientists, who recently won the prestigious Volvo Environment Prize in Sustainability for his role in understanding and protecting the Amazon. "Social and economic equality empowers societies to engage in sustainable pathways, which includes, by the way, not only the sustainable use of natural resources but also slowing down population growth, to actively diminish the human footprint on the environment."

Michael Mann, Distinguished Professor and Director of the Earth System Science Center at Penn State University, who was not a co-author of the paper, commented: "We cannot separate the issues of population growth, resource consumption, the burning of fossil fuels, and climate risk. They are part of a coupled dynamical system, and, as the authors show, this has dire potential consequences for societal collapse. The implications couldn't be more profound."”
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

sidd

  • ASIF Upper Class
  • Posts: 1264
    • View Profile
Re: Modelling the Anthropocene
« Reply #101 on: February 18, 2017, 06:57:20 PM »
Thanks for the Motasharrei et. al link to human influenced models. I reviewed his 2014 publication (ref 134 in this one, http://www.sciencedirect.com/science/article/pii/S0921800914000615 which oddly enuf has no doi) while reading this one, especially the graphs (including Fig 5 in the present review which you attached.)

In some of the 2014 results we see oscillations, and in others we do not. In the old days we used to call these underdamped and overdamped cases. It might be interesting to apply the methods of Sugihara(2012, doi:10.1126/science.1227079 ) and Ye(2015, http://www.pnas.org/cgi/doi/10.1073/pnas.1417063112 ) directly to the underdamped cases, while the overdamped ones might require rotation to imaginary time and back after the calculation.

I think i have some of the code written ... I may have to take a look

sidd
« Last Edit: February 18, 2017, 07:02:48 PM by sidd »

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #102 on: February 18, 2017, 09:00:29 PM »
I think i have some of the code written ... I may have to take a look


sidd,

If you get your model calibrated, see if you can include the impacts of a human-climate interaction mechanism coded as a strange attractor feeding into a meltdown of the entire financial system (maybe you can numerically show the elite that they suffer more losses than their collective guts are telling them):

See the linked article entitled: "Climate change could threaten entire financial system, APRA warns"

http://www.abc.net.au/news/2017-02-17/climate-change-could-threaten-entire-financial-system-apra/8281436

Extract: "Climate change could threaten the stability of the entire financial system, the prudential regulator has warned, as it prepares to apply climate change "stress tests" to the nation's financial institutions.

In its first major speech on climate change, the Australian Prudential Regulation Authority chastised companies for a lack of action on the risks it poses."

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

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #103 on: February 18, 2017, 09:47:57 PM »
The linked reference examines the sensitivity of Shared Socioeconomic Pathways to changes in key parameters & finds that energy intensity and economic growth are the two most important determinants of future GHG emissions.  Now all we have to do is to convince people (including elites) to use less energy (of all types) and to accept less economic growth.

G. Marangoni, et. al. (2017), "Sensitivity of projected long-term CO2 emissions across the Shared Socioeconomic Pathways", Nature Climate Change, Volume: 7, Pages: 113–117, doi:10.1038/nclimate3199

http://www.nature.com/nclimate/journal/v7/n2/full/nclimate3199.html

Abstract: "Scenarios showing future greenhouse gas emissions are needed to estimate climate impacts and the mitigation efforts required for climate stabilization. Recently, the Shared Socioeconomic Pathways (SSPs) have been introduced to describe alternative social, economic and technical narratives, spanning a wide range of plausible futures in terms of challenges to mitigation and adaptation. Thus far the key drivers of the uncertainty in emissions projections have not been robustly disentangled. Here we assess the sensitivities of future CO2 emissions to key drivers characterizing the SSPs. We use six state-of-the-art integrated assessment models with different structural characteristics, and study the impact of five families of parameters, related to population, income, energy efficiency, fossil fuel availability, and low-carbon energy technology development. A recently developed sensitivity analysis algorithm allows us to parsimoniously compute both the direct and interaction effects of each of these drivers on cumulative emissions. The study reveals that the SSP assumptions about energy intensity and economic growth are the most important determinants of future CO2 emissions from energy combustion, both with and without a climate policy. Interaction terms between parameters are shown to be important determinants of the total sensitivities."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

sidd

  • ASIF Upper Class
  • Posts: 1264
    • View Profile
Re: Modelling the Anthropocene
« Reply #104 on: February 18, 2017, 10:14:58 PM »
My ideas at the moment  to take the model output (HANDY) in Motasharrei(2014), then real world data and

1)  use the empirical dynamic method in Ye(2015) to see if in fact there is at all evidence for the efficacy of the Sugihara(2012) method     
`
2) if there is, use cross convergence as in Sugihara(2012) to attemp to untangle causality between various outcomes

3) Either 1) or 2) could be used for prediction

4) Coupling financial systems into HANDY is not something i would untertake lightly. I have a more general idea in mind toward those ends, which would take me to far afield to explain fully at the moment. But briefly, the idea is to investigate the stability of the dynamical orbits describing the system (stability of projections into lower dimensional spaces from the full manifold, if you like). Once that is done i think coupling to other dynamical systems such as financial/economic/... ones would be much easier, since one could establish at a glance (well, a few glances and based on the independent behaviour of each system you were trying to couple) what the effect of the coupling on each would be.

5) Another powerful idea is from the notion of transfer entropy as in Liang(2015, doi:10.1103/PhysRevE.90.052150 ) to detect causality _and_ stabilization between time series. I have already coded to combine transfer entropy with cross convergence and empirical dynamical methods. The strength of this combination is that it winnows the relevant subspaces down to those which capture the essentials of the dynamics. Thus we only have to look at a few possible combinations for the relevant subspaces, neatly evading combinatorial explosion (i hope)

6) I can do all this from realworld time series (as I have already done in some ecological systems) or from the HANDY output. My instinct is to jump right into real data, but i need to get some familiarity with these methods on simple (ha!) models before diving into the cold and deep pools of reality

The program outlined above is very easy to conceive, on a sunny afternoon in Philly, sitting on a deck outside, drinking hi test microbrew, and cheeping back at the birds and miaowing at itinerant cats. How much of it i actually get done I cannot say.

sidd

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #105 on: February 18, 2017, 10:41:25 PM »
The program outlined above is very easy to conceive, on a sunny afternoon in Philly, sitting on a deck outside, drinking hi test microbrew, and cheeping back at the birds and miaowing at itinerant cats. How much of it i actually get done I cannot say.

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

sidd

  • ASIF Upper Class
  • Posts: 1264
    • View Profile
Re: Modelling the Anthropocene
« Reply #106 on: February 19, 2017, 05:32:46 AM »
"Godspeed, John Glenn."

Heehee. I didn't think I was quite so obviously dead yet. 

His funeral was on a bitingly cold day in Columbus, OH. They had an imressive turnout for the weather, but then ohioans, even the soft ones in columbus, are quite stoic. I was in columbus then, but did not attend.

There are little towns in ohio like Cambridge and New Concord where he grew up, and I have been thru many times. They have seen hard times.

sidd

bligh8

  • ASIF Citizen
  • Posts: 131
    • View Profile
Re: Modelling the Anthropocene
« Reply #107 on: February 21, 2017, 08:24:15 AM »
Hey…..wow, such musings on a Saturday afternoon in April, a breath of fresh air indeed.

Fair Winds
bligh

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #108 on: March 06, 2017, 07:52:22 PM »
The linked open access reference discusses various techniques to expand current ESMs to better human behavior:

Finn Müller-Hansen, Maja Schlüter, Michael Mäs, Rainer Hegselmann, Jonathan F. Donges, Jakob J. Kolb, Kirsten Thonicke, and Jobst Heitzig (2017), "How to represent human behavior and decision making in Earth system models? A guide to techniques and approaches", Earth Syst. Dynam. Discuss., doi:10.5194/esd-2017-18

http://www.earth-syst-dynam-discuss.net/esd-2017-18/esd-2017-18.pdf

Abstract: "In the Anthropocene, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth System Models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. In this tutorial review, we compare existing modeling approaches and techniques from different disciplines and schools of thought dealing with human behavior at various levels of decision making. Providing an overview over social-scientific modeling approaches, we demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions.

After discussing which socio-economic units are potentially important for ESMs, we review models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We discuss approaches to model social interaction, covering game theoretic frameworks, models of social influence and network models. Finally, we elaborate approaches to study how the behavior of individuals, groups and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #109 on: March 15, 2017, 10:26:03 PM »
The linked reference uses Amazonian deep convective clouds as an example of the valued of using the Gamma phase space for modeling clouds:

Cecchini, M. A., Machado, L. A. T., Wendisch, M., Costa, A., Krämer, M., Andreae, M. O., Afchine, A., Albrecht, R. I., Artaxo, P., Borrmann, S., Fütterer, D., Klimach, T., Mahnke, C., Martin, S. T., Minikin, A., Molleker, S., Pardo, L. H., Pöhlker, C., Pöhlker, M. L., Pöschl, U., Rosenfeld, D., and Weinzierl, B.: Illustration of microphysical processes in Amazonian deep convective clouds in the Gamma phase space: Introduction and potential applications, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2017-185, in review, 2017.

http://www.atmos-chem-phys-discuss.net/acp-2017-185/

Abstract. The behavior of tropical clouds remains a major open scientific question, given that the associated phys-ics is not well represented by models. One challenge is to realistically reproduce cloud droplet size dis-tributions (DSD) and their evolution over time and space. Many applications, not limited to models, use the Gamma function to represent DSDs. However, there is almost no study dedicated to understanding the phase space of this function, which is given by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and inter-comparisons. Here, we introduce the phase-space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, where the relative dispersion parameter of the DSD can play a significant role. Overall, the Gamma phase-space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on Gamma DSDs.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #110 on: March 16, 2017, 03:34:21 AM »
The linked reference discusses the use of Wasserstein distance can be used to better understand climate attractors.

Robin, Y., Yiou, P., and Naveau, P.: Detecting Changes in Forced Climate Attractors with Wasserstein Distance, Nonlin. Processes Geophys. Discuss., doi:10.5194/npg-2017-5, in review, 2017.

http://www.nonlin-processes-geophys-discuss.net/npg-2017-5/

Abstract. The climate system can been described by a dynamical system and its associated attractor. The dynamics of this attractor depends on the external forcings that influence the climate. Such forcings can affect the mean values or variances, but regions of the attractor that are seldom visited can also be affected. It is an important challenge to measure how the climate attractor responds to different forcings. Currently, the Euclidean distance or similar measures like the Mahalanobis distance have been favoured to measure discrepancies between two climatic situations. Those distances do not have a natural building mechanism to take into account the attractor dynamics. In this paper, we argue that a Wasserstein distance, stemming from optimal transport theory, offers an efficient and practical way to discriminate between dynamical systems. After treating a toy example, we explore how the Wasserstein distance can be applied and interpreted to detect non-autonomous dynamics from a Lorenz system driven by seasonal cycles and a warming trend.

For the open access pdf see:

http://www.nonlin-processes-geophys-discuss.net/npg-2017-5/npg-2017-5.pdf

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

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #111 on: March 22, 2017, 06:23:30 PM »
The linked reference discusses model projected changes in extreme precipitation with global warming; and indicates that rainfall will likely increase through 2100; which to my mind will (among other things) accelerate degradation of permafrost.

Guiling Wang, Dagang Wang, Kevin E. Trenberth, Amir Erfanian, Miao Yu, Michael G. Bosilovich, & Dana T. Parr (2017), "The peak structure and future changes of the relationships between extreme precipitation and temperature", Nature Climate Change, doi:10.1038/nclimate3239

http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3239.html

Abstract: "Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius–Clapeyron (C–C) relationship.  Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe, the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low–medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (Tpeak) will increase with warming; the two increases generally conform to the C–C scaling rate in mid- and high-latitudes, and to a super C–C scaling in most of the tropics. Because projected increases of local mean temperature (Tmean) far exceed projected increases of Tpeak over land, the conventional approach of relating extreme precipitation to Tmean produces a misleading sub-C–C scaling rate."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #112 on: May 04, 2017, 01:05:02 AM »
The linked reference & associated article indicate that CMIP5 climate models can be corrected to accurately hind-caste the faux hiatus:

Iselin Medhaug, Martin B. Stolpe, Erich M. Fischer& Reto Knutti (2017), "Reconciling controversies about the ‘global warming hiatus’", Nature, doi:10.1038/nature22315

http://www.nature.com/nature/journal/v545/n7652/full/nature22315.html

http://www.nature.com/articles/nature22315.epdf?referrer_access_token=JLkSn0TiKxcgOZC96Yyo1tRgN0jAjWel9jnR3ZoTv0NuFtYPLl1PUnqxUYbpB1uVru_rIjRyseUxK8YNRXQS41-Xf6ZZogTkPn3KRcKavtILhD4coONJlcGDCKvzDODIkuk843_-Ed8uysUYSjoO1mnSC9MKgJe-AEdiQrYEil_J7dXfrqXcEk3aUKEwwbhH12BmIcywDhqQFLGneIRyuBCPPM_uThqWtrjDhaarzoM2Q58JLurh9B00TC_dOiOwjlp9Kpu1_r9BOi4c5Nq5AA%3D%3D&tracking_referrer=www.latimes.com

Abstract: "Between about 1998 and 2012, a time that coincided with political negotiations for preventing climate change, the surface of Earth seemed hardly to warm. This phenomenon, often termed the ‘global warming hiatus’, caused doubt in the public mind about how well anthropogenic climate change and natural variability are understood. Here we show that apparently contradictory conclusions stem from different definitions of ‘hiatus’ and from different datasets. A combination of changes in forcing, uptake of heat by the oceans, natural variability and incomplete observational coverage reconciles models and data. Combined with stronger recent warming trends in newer datasets, we are now more confident than ever that human influence is dominant in long-term warming."


See also the linked article entitled: "Detailed look at the global warming ‘hiatus’ again confirms that humans are changing the climate"

http://www.latimes.com/science/sciencenow/la-sci-sn-global-warming-hiatus-20170503-htmlstory.html

Extract: "For years, the global warming ‘hiatus’ from 1998 to 2012 puzzled scientists and fueled skeptics looking to cast doubt on the very idea that Earth’s temperature has been on the rise, largely because of human-produced greenhouse gas emissions such as carbon dioxide — and that significant policy changes would need to be made to keep that rise in check.
Recent papers have begun to chip away at the idea of the slowdown. Now, a new analysis in the journal Nature brings together many of those arguments to show that the hiatus may not have been quite what it seemed."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #113 on: May 17, 2017, 10:11:10 PM »
The linked reference indicates that we need to pay more attention to changes to extreme precipitation patterns with continued global warming:

Geert Lenderink & Hayley J. Fowler (2017), "Hydroclimate: Understanding rainfall extremes", Nature Climate Change, doi:10.1038/nclimate3305

https://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3305.html

Extract: "Warming induced by greenhouse gases will increase the amount of moisture in the atmosphere, causing heavier rainfall events. Changing atmospheric circulation dynamics are now shown to either amplify or weaken regional increases, contributing to uncertainty in future precipitation extremes."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #114 on: May 19, 2017, 05:22:23 PM »
The linked reference finds that: "The model predicts that land surfaces have a 50% greater climate sensitivity than ocean surfaces, and that the nighttime temperatures on land increase about twice as much as daytime temperatures because of the absence of turbulent fluxes at night."

Kleidon, A. and Renner, M.: An explanation for the different climate sensitivities of land and ocean surfaces based on the diurnal cycle, Earth Syst. Dynam. Discuss., doi:10.5194/esd-2017-44, in review, 2017

http://www.earth-syst-dynam-discuss.net/esd-2017-44/

Abstract. Observations and climate model simulations consistently show a higher climate sensitivity of land surfaces compared to ocean surfaces, with the cause for this difference being still unclear. Here we show that this difference in temperature sensitivity can be explained by the different means by which the diurnal variation in solar radiation is buffered. While ocean surfaces buffer the diurnal variations by heat storage changes below the surface, land surfaces buffer it mostly by heat storage changes above the surface in the lower atmosphere that are reflected in the diurnal growth of a convective boundary layer. Storage changes below the surface allow the ocean surface-atmosphere system to maintain turbulent fluxes over day and night, while the land surface-atmosphere system maintains turbulent fluxes only during the daytime hours when the surface is heated by absorption of solar radiation. This shorter duration of turbulent fluxes on land then results in a greater sensitivity of the land surface-atmosphere system to changes in the greenhouse forcing because nighttime temperatures are then shaped by radiative exchange only, which are more sensitive to changes in greenhouse forcing. We use a simple, analytic energy balance model of the surface-atmosphere system in which turbulent fluxes are constrained by the maximum power limit to estimate the effects of these different means to buffer the diurnal cycle on the resulting temperature sensitivities. The model predicts that land surfaces have a 50% greater climate sensitivity than ocean surfaces, and that the nighttime temperatures on land increase about twice as much as daytime temperatures because of the absence of turbulent fluxes at night. Both predictions compare very well with observations and CMIP 5 climate model simulations. Hence, the greater climate sensitivity of land surfaces can be explained by its buffering of diurnal variations of solar radiation in the lower atmosphere.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

gerontocrat

  • ASIF Citizen
  • Posts: 421
    • View Profile
Re: Modelling the Anthropocene
« Reply #115 on: May 27, 2017, 03:25:29 PM »
I am looking for a model that predicts the probability for and date of a post-Anthropocene world, i.e. when humans have damaged the world and themselves as a species so badly that humans' further influence on the planet is minimal. (Feeling pessimistic today)

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #116 on: May 28, 2017, 01:44:29 AM »
gerontocrat,

If you accept the logic that our modern global socio-economic system will collapse (including into: warfare, famine, drought, disease & financial ruin) when the West Antarctic Ice Sheet collapses (together with meaningful ice mass loss from Greenland) due both the abrupt sea level rise (ASLR) and Hansen's ice-climate feedback, then the attached image may answer your question. The image shows my proposed PDFs and CDFs associated with RSLR for California for the years 2070 and 2100; assuming that we follow RCP 8.5 through at least 2035.

While all of my posts assume this probability distribution, the following two threads are useful to understand the logic behind these curves.

Thread: "Potential Collapse Scenario for the WAIS"
http://forum.arctic-sea-ice.net/index.php/topic,31.0.html

&
Thread: "Hansen et al paper: 3+ meters SLR by 2100"
http://forum.arctic-sea-ice.net/index.php/topic,1327.0.html

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

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #117 on: June 06, 2017, 04:02:18 PM »
Accurately projecting the sensitivity of the hydraulic cycle is critical to estimating climate change impact:

James J. Benedict, Brian Medeiros, Amy C. Clement & Angeline G. Pendergrass (1 June 2017), "Sensitivities of the hydrologic cycle to model physics, grid resolution, and ocean type in the aquaplanet Community Atmosphere Model", JAMES, DOI: 10.1002/2016MS000891

http://onlinelibrary.wiley.com/doi/10.1002/2016MS000891/full

Abstract: "Precipitation distributions and extremes play a fundamental role in shaping Earth's climate and yet are poorly represented in many global climate models. Here, a suite of idealized Community Atmosphere Model (CAM) aquaplanet simulations is examined to assess the aquaplanet's ability to reproduce hydroclimate statistics of real-Earth configurations and to investigate sensitivities of precipitation distributions and extremes to model physics, horizontal grid resolution, and ocean type. Little difference in precipitation statistics is found between aquaplanets using time-constant sea-surface temperatures and those implementing a slab ocean model with a 50 m mixed-layer depth. In contrast, CAM version 5.3 (CAM5.3) produces more time mean, zonally averaged precipitation than CAM version 4 (CAM4), while CAM4 generates significantly larger precipitation variance and frequencies of extremely intense precipitation events. The largest model configuration-based precipitation sensitivities relate to choice of horizontal grid resolution in the selected range 1–2°. Refining grid resolution has significant physics-dependent effects on tropical precipitation: for CAM4, time mean zonal mean precipitation increases along the Equator and the intertropical convergence zone (ITCZ) narrows, while for CAM5.3 precipitation decreases along the Equator and the twin branches of the ITCZ shift poleward. Increased grid resolution also reduces light precipitation frequencies and enhances extreme precipitation for both CAM4 and CAM5.3 resulting in better alignment with observational estimates. A discussion of the potential implications these hydrologic cycle sensitivities have on the interpretation of precipitation statistics in future climate projections is also presented."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #118 on: June 10, 2017, 04:20:05 AM »
The linked opinion article recommends the use of climate model pluralism in order to better represent complex Earth Systems:

FULVIO MAZZOCCHI, ANTONELLO PASINI(May 31 2017), "Climate model pluralism beyond dynamical ensembles", WIRES Climate Change, DOI: 10.1002/wcc.477

http://wires.wiley.com/WileyCDA/WiresArticle/wisId-WCC477.html


Abstract: "Using pluralist research strategies can be a profitable way to study complex systems. This contribution focuses on the approaches for studying the climate that make use of multiple different models, aiming to increase the reliability (in terms of robustness) of attribution results. This Opinion article argues that the traditional approach, which is based on ensemble runs of global climate models, only partially allows the application of a robustness scheme, owing to the difficulty to match or evaluate the conditions required for robustness (i.e., independence or heterogeneity among models). An alternative ‘multi‐approach’ strategy is advanced, beyond dynamical modeling but still preserving the idea of model pluralism. Such a strategy, which uses a set of ensembles of different model types by combining dynamical modeling with data‐driven methodological approaches (i.e., neural networks and Granger causality), seems to better match the condition of independence. In addition, neural networks and Granger causality lead to achievements in attribution studies that can complement those obtained by dynamical modeling."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #119 on: June 13, 2017, 02:57:13 PM »
Projecting extreme hydroclimatic events is important but challenging, & the linked reference uses Bayesian multi-model projections to make progress on this issue:

Qiao-Hong Sun, et. al. (2017), "Bayesian multi-model projections of extreme hydroclimatic events under RCPs scenarios", Advances in Climate Change Research, https://doi.org/10.1016/j.accre.2017.06.001

http://www.sciencedirect.com/science/article/pii/S1674927816300934

Abstract: "A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China (i.e., Liaohe River Basin, Yellow River Basin, Yangtze River Basin, and Pearl River Basin) under RCP2.6, RCP4.5, and RCP8.5 scenarios using multiple global climate model projections from the IPCC Fifth Assessment Report. The results projected more summer days and fewer frost days in 2006‒2099. The ensemble prediction shows the Pearl River Basin is projected to experience more summer days than other basins with the increasing trend of 16.3, 38.0, and 73.0 d per 100 years for RCP 2.6, RCP 4.5 and RCP 8.5, respectively. Liaohe River Basin and Yellow River Basin are forecasted to become wetter and warmer with the co-occurrence of increases in summer days and wet days. Very heavy precipitation days (R20, daily precipitation ≥20 mm) are projected to increase in all basins. The R20 in the Yangtze River Basin are projected to have the highest change rate in 2006‒2099 of 1.8, 2.5, and 3.8 d per 100 years for RCP 2.6, RCP 4.5 and RCP 8.5, respectively."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #120 on: June 17, 2017, 07:03:28 PM »
The two linked references indicate that CMIP5 projections lack sufficient dynamical behavior to model decadal variations in the rate of global warming:

Shuai-Lei Yao et al, Distinct global warming rates tied to multiple ocean surface temperature changes, Nature Climate Change (2017). DOI: 10.1038/nclimate3304

https://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3304.html

Abstract: "The globally averaged surface temperature has shown distinct multi-decadal fluctuations since 1900, characterized by two weak slowdowns in the mid-twentieth century and early twenty-first century and two strong accelerations in the early and late twentieth century. While the recent global warming (GW) hiatus has been particularly ascribed to the eastern Pacific cooling, causes of the cooling in the mid-twentieth century and distinct intensity differences between the slowdowns and accelerations remain unclear. Here, our model experiments with multiple ocean sea surface temperature (SST) forcing reveal that, although the Pacific SSTs play essential roles in the GW rates, SST changes in other basins also exert vital influences. The mid-twentieth-century cooling results from the SST cooling in the tropical Pacific and Atlantic, which is partly offset by the Southern Ocean warming. During the recent hiatus, the tropical Pacific-induced strong cooling is largely compensated by warming effects of other oceans. In contrast, during the acceleration periods, ubiquitous SST warming across all the oceans acts jointly to exaggerate the GW. Multi-model simulations with separated radiative forcing suggest diverse causes of the SST changes in multiple oceans during the GW acceleration and slowdown periods. Our results highlight the importance of multiple oceans on the multi-decadal GW rates."

&

Power et. al. (2017), "Apparent limitations in the ability of CMIP5 climate models to simulate recent multi-decadal change in surface temperature: implications for global temperature projections", Clim Dyn (2017) 49: 53. doi:10.1007/s00382-016-3326-x

https://link.springer.com/article/10.1007%2Fs00382-016-3326-x?utm_content=buffer44ff8&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Abstract: "Observed surface temperature trends over the period 1998–2012/2014 have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short-trends, whether they indicate a possible bias in the model values and the implications for global warming generally. Here we re-examine these issues, but as they relate to changes over much longer-term changes. We find that on multi-decadal time scales there is little evidence for any change in the observed global warming rate, but some evidence for a recent temporary slowdown in the warming rate in the Pacific. This multi-decadal slowdown can be partly explained by a cool phase of the Interdecadal Pacific Oscillation and a short-term excess of La Niña events. We also analyse historical and projected changes in 38 CMIP climate models. All of the model simulations examined simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This difference cannot be fully explained by observed internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. Models which simulate the greatest global warming over the past half-century also project warming that is among the highest of all models by the end of the twenty-first century, under both low and high greenhouse gas emission scenarios. Given that the same models are poorest in representing observed multi-decadal temperature change, confidence in the highest projections is reduced."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #121 on: June 18, 2017, 06:12:23 PM »
The linked reference discusses incremental progress in modeling temporal fluctuations (such as the faux hiatus) in GMSTA:

Hege-Beate Fredriksen and Martin Rypdal (2017), "Long-range persistence in global surface temperatures explained by linear multi-box energy balance models", Journal of Climate, https://doi.org/10.1175/JCLI-D-16-0877.1

http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0877.1?utm_content=buffer22000&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Abstract: "The temporal fluctuations in global mean surface temperature is an example of a geophysical quantity which can be described using the notions of long-range persistence and scale invariance/scaling, but this description has suffered from lack of a generally accepted physical explanation. Processes with these statistical signatures can arise from non-linear effects, for instance through cascade-like energy transfer in turbulent fluids, but they can also be produced by linear models with scale-invariant impulse-response functions. This paper demonstrates that on time scales from months to centuries, the scale-invariant impulse-response function of global surface temperature can be explained from simple linear multi-box energy balance models. This explanation describes both the scale invariance of the internal variability and the lack of a characteristic time scale of the response to external forcings. With parameters estimated from observational data, the climate response is approximately scaling in these models, even if the response function is not chosen to be scaling a priori. It is also demonstrated that the differences in scaling exponents for temperatures over land and for sea-surface temperatures can be reproduced by a version of the multi-box energy balance model with two distinct surface boxes."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #122 on: July 03, 2017, 03:57:39 PM »
The linked reference uses a CMIP type of climate model to examine the strengths of different carbon cycles during glacial and interglacial periods.  They find that overall climate sensitivity is stronger during interglacial periods such as we live in now.  However, I note that if their model errs on the side of least drama then so do their findings:


Adloff, M., Reick, C. H., and Claussen, M.: Earth system model simulations show different carbon cycle feedback strengths under glacial and interglacial conditions, Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-67, in review, 2017.

http://www.earth-syst-dynam-discuss.net/esd-2017-67/

Abstract. In Earth system model simulations we find different carbon cycle sensitivities for recent and glacial climate. This result is obtained by comparing the transient response of the terrestrial carbon cycle to a fast and strong atmospheric CO2 concentration increase (roughly 1000ppm) in C4MIP type simulations starting from climate conditions of the Last Glacial Maximum (LGM) and from Pre-Industrial times (PI). The sensitivity β to CO2 fertilization is larger in the LGM experiment during most of the simulation time: The fertilization effect leads to a terrestrial carbon gain in the LGM experiment almost twice as large as in the PI experiment. The larger fertilization effect in the LGM experiment is caused by the stronger initial CO2 limitation of photosynthesis, implying a stronger potential for its release upon CO2 concentration increase. In contrast, the sensitivity γ to climate change induced by the radiation effect of rising CO2 is larger in the PI experiment for most of the simulation time. Yet, climate change is less pronounced in the PI experiment, resulting in only slightly higher terrestrial carbon losses than in the LGM experiment. The stronger climate sensitivity in the PI experiment results from the vastly more extratropical soil carbon under those interglacial conditions whose respiration is enhanced under climate change. Comparing the radiation and fertilization effect in a factor analysis, we find that they are almost additive, i.e. their synergy is small in the global sum of carbon changes. From this additivity, we find that the carbon cycle feedback strength is more negative in the LGM than in the PI simulations.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #123 on: July 05, 2017, 07:37:55 PM »
The linked article provides an overview of the CMIP project including CMIP6:

Title: "Highlight article: WCRP’s Coupled Model Intercomparison Project: a remarkable contribution to climate science".

http://www.egu.eu/news/highlight-articles/586/wcrps-coupled-model-intercomparison-project-a-remarkable-contribution-to-climate-science/

Extract: "CMIP6 confronts a number of new challenges. More centers will run more versions of more models of increasing complexity. An ongoing demand to resolve more processes requires increasingly higher model resolutions. Archiving, documenting, subsetting, supporting, distributing, and analyzing the petabytes of CMIP6 model outputs will challenge the capacity and creativity of the largest data centres and fastest data networks. Fundamentally, CMIP6 will allow continuous and flexible model innovation schedules while remaining mindful of the IPCC process, will ensure that CMIP products address priorities identified by the climate research community, and will foster open and inclusive participation. Prof Veronika Eyring, researcher at the German Aerospace Center (DLR) and Chair of the CMIP Panel, outlines that “with CMIP6 we aim to achieve a balance between fundamental improvements of our modeling skills and rapid progress on urgent science questions – not an easy task for the modeling centres and researchers who analyze the data.”

The growing dependency on CMIP products by a broad research community and by national and international climate assessments means that basic CMIP activities, such as the creation of forcing datasets, the provision and archiving of CMIP products, and model development, require substantial efforts. CMIP continues to rely heavily on volunteer efforts by enthusiastic climate researchers. It represents one of society’s most robust and reliable sources for climate information – a source that deserves international acclaim and substantial ongoing support."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

Andre

  • ASIF Lurker
  • Posts: 52
    • View Profile
Re: Modelling the Anthropocene
« Reply #124 on: July 06, 2017, 01:34:02 AM »
Crossposted from Consequences thread, as I believe it fits here too.

It is starting to look more and more like we arent so lucky and climate sensitivity might be much higher than anticipated so far:

https://www.theguardian.com/environment/2017/jul/05/hopes-of-mild-climate-change-dashed-by-new-research?CMP=Share_iOSApp_Other

Hopes of mild climate change dashed by new research

"Hopes that the world’s huge carbon emissions might not drive temperatures up to dangerous levels have been dashed by new research.

The work shows that temperature rises measured over recent decades do not fully reflect the global warming already in the pipeline and that the ultimate heating of the planet could be even worse than feared.

How much global temperatures rise for a certain level of carbon emissions is called climate sensitivity and is seen as the single most important measure of climate change. Computer models have long indicated a high level of sensitivity, up to 4.5C for a doubling of CO2 in the atmosphere.

However in recent years estimates of climate sensitivity based on historical temperature records from the past century or so have suggested the response might be no more than 3C. This would mean the planet could be kept safe with lower cuts in emissions, which are easier to achieve.

But the new work, using both models and paleoclimate data from warming periods in the Earth’s past, shows that the historical temperature measurements do not reveal the slow heating of the planet’s oceans that takes place for decades or centuries after CO2 has been added to the atmosphere.

“The hope was that climate sensitivity was lower and the Earth is not going to warm as much,” said Cristian Proistosescu, at Harvard University in the US, who led the new research. “There was this wave of optimism.”

The new research, published in the journal Science Advances, has ended that. “The worrisome part is that all the models show there is an amplification of the amount of warming in the future,” he said. The situation might be even worse, as Proistosescu’s work shows climate sensitivity could be as high as 6C."


The Guardian article is based on this paper:

http://advances.sciencemag.org/content/3/7/e1602821

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #125 on: July 13, 2017, 06:20:23 PM »
Per the linked reference, climate models need to do a better job of accounting for the feedback between human and natural processes in the land Earth Systems:

Robinson, D. T., Di Vittorio, A., Alexander, P., Arneth, A., Barton, C. M., Brown, D. G., Kettner, A., Lemmen, C., O'Neill, B. C., Janssen, M., Pugh, T. A. M., Rabin, S. S., Rounsevell, M., Syvitski, J. P., Ullah, I., and Verburg, P. H.: Modelling feedbacks between human and natural processes in the land system, Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-68, in review, 2017.

http://www.earth-syst-dynam-discuss.net/esd-2017-68/

Abstract. The unprecedented use of Earth's resources by humans, in combination with the increasing natural variability in natural processes over the past century, is affecting evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g., climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. To capture and formalize our understanding of the interactions and feedback between human and natural systems a variety of modelling approaches are used. While integrated assessment models are widely recognized as supporting this goal and integrating representations of the human and natural system for global applications, an increasing diversity of models and corresponding research have focused on coupling models specializing in specific human (e.g., decision-making) or natural (e.g., erosion) processes at multiple scales. Domain experts develop these specialized models with a greater degree of detail, accuracy, and transparency, with many adopting open-science norms that use new technology for model sharing, coupling, and high performance computing. We highlight examples of four different approaches used to couple representations of the human and natural system, which vary in the processes represented and in the scale of their application. The examples illustrate how groups of researchers have attempted to overcome the lack of suitable frameworks for coupling human and natural systems to answer questions specific to feedbacks between human and natural systems. We draw from these examples broader lessons about system and model coupling and discuss the challenges associated with maintaining consistency across models and representing feedback between human and natural systems in coupled models.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #126 on: July 13, 2017, 08:01:50 PM »
Most IAM projections are so poor that researchers don't even bother to do hind-caste evaluations to help calibrate their future modeling development.  The linked reference provides recommendations on how to begin to address this short-coming in the IAM field:

Snyder, A. C., Link, R. P., and Calvin, K. V.: Evaluation of Integrated Assessment Model hindcast experiments: A case study of the GCAM 3.0 land use module, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-97, in review, 2017.

http://www.geosci-model-dev-discuss.net/gmd-2017-97/

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data is available) are rarely undertaken in the Integrated Assessment Model (IAM) community. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation based measures that can be applied at different spatial scales (regional versus global) to make evaluating the large number of variable-region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. This is key in the integrated assessment community, where there often are not multiple models conducting hindcast experiments to allow for model intercomparison. The performance benchmarks serve a second purpose, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. As a case study, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs, such as GCAM, that require global supply to equal global demand at each time period. Additionally, the deviation measures examined in this work successfully identity parametric and structural changes that may improve land allocation decisions in GCAM. Future work will involve implementing the suggested improvements to the GCAM land allocation system identified by the measures in this work, using the measures to quantify performance improvement due to these changes, and, ideally, applying these measures to other sectors of GCAM and other land allocation models.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

rboyd

  • ASIF Citizen
  • Posts: 449
    • View Profile
Re: Modelling the Anthropocene
« Reply #127 on: July 13, 2017, 09:11:53 PM »
In the financial world this is called "backtesting the models", a very good idea indeed. The problem is when the past does not represent the future correctly, as seen when all the models failed in 2008. Their biggest problem was the assumption of liquidity (the availability of willing buyers) and a normal distribution of outcomes (as against skew and "fat tails"). This latter problem lead to "stress testing".

It looks like the IAM modellers have not learnt much from the failure of the financial modellers. The IAM version of liquidity is the assumption that food exports will be available during a food shortage - already shown to be completely unrealistic. Another is that the financial system will continue to function perfectly as the climate goes to hell ("Ceterus Paribus" is a wonderful economics assumptions - "all other things remain the same").

Yep, the IAMs are pretty much useless.

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #128 on: July 16, 2017, 06:31:05 PM »
Correctly projecting changes in the ENSO cycle, with continued global warming, is important w.r.t. correctly estimating ECS this century:

Bayr, T., Latif, M., Dommenget, D. et al. (2017), "Mean-state dependence of ENSO atmospheric feedbacks in climate models", Clim Dyn, doi:10.1007/s00382-017-3799-2

https://link.springer.com/article/10.1007%2Fs00382-017-3799-2?utm_content=buffer87cf6&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Extract: "We investigate the dependence of ENSO atmospheric feedbacks on the mean-state in a perturbed atmospheric physics ensemble with the Kiel Climate Model (KCM) and in CMIP5 models. Additionally, uncoupled simulations are conducted with the atmospheric component of the KCM to obtain further insight into the mean-state dependence. It is found that the positive zonal wind feedback and the negative heat flux feedback, with the short-wave flux as dominant component, are strongly linearly related through sea surface temperature (SST) and differences in model physics are less important. In observations, strong zonal wind and heat flux feedbacks are caused by a convective response in the western central equatorial Pacific (Niño4 region), resulting from an eastward (westward) shift of the rising branch of the Walker Circulation (WC) during El Niño (La Niña). Many state-of-the-art climate models exhibit an equatorial cold SST bias in the Niño4 region, i.e. are in a La Niña-like mean-state. Therefore they simulate a too westward located rising branch of the WC (by up to 30°) and only a weak convective response. Thus, the position of the WC determines the strength of both the amplifying wind and usually damping heat flux feedback, which also explains why biases in these two feedbacks partly compensate in many climate models. Furthermore, too weak atmospheric feedbacks can cause quite different ENSO dynamics than observed, while enhanced atmospheric feedbacks lead to a substantial improvement of important ENSO properties such as seasonal ENSO phase locking and asymmetry between El Niño and La Niña. Differences in the mean-state SST are suggested to be a major source of ENSO diversity in current climate models."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #129 on: July 17, 2017, 03:50:25 AM »
The linked reference discusses cloud feedback mechanisms & how they are modeled, including the possibility that the net cloud feedback might be significantly positive and may have a significant dynamical impact of both climate and weather:

Paulo Ceppi, Florent Brient, Mark D. Zelinka & Dennis L. Hartmann (2017), “Cloud feedback mechanisms and their representation in global climate models”, WIREs Clim Change, 8:e465. doi: 10.1002/wcc.465

http://onlinelibrary.wiley.com/doi/10.1002/wcc.465/abstract

http://www.atmos.washington.edu/~dennis/cloud_fdbk_review_revised.pdf

Abstract: “Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO2forcing simulated by global climate models (GCMs). We review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). These cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. The causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.”
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #130 on: July 17, 2017, 05:07:18 AM »
I think that we will all be unpleasantly surprised by how rapidly methane emissions from thermokarst lakes will increase in the coming decades:

Alex Matveev, Isabelle Laurion, Bethany N. Deshpande, Najat Bhiry & Warwick F. Vincent (2017), “High methane emissions from thermokarst lakes in subarctic peatlands”, Limnology and Oceanography, DOI: 10.1002/lno.10311

http://onlinelibrary.wiley.com/doi/10.1002/lno.10311/abstract

Abstract: “The thawing and subsidence of frozen peat mounds (palsas) in permafrost landscapes results in the formation of organic-rich thermokarst lakes. We examined the effects of palsa degradation on CH4 and CO2 emissions by comparing thermokarst lakes at two peatland locations in subarctic Québec, Canada: in the northern discontinuous permafrost region, and in southern sporadic permafrost where palsas are more rapidly degrading. The lakes were shallow (< 3 m) but stratified at both sites, and most had anoxic bottom waters. The surface waters at both sites were supersaturated in CH4 and CO2, and to a greater extent in the southern lakes, where the surface CH4 concentrations were up to 3 orders of magnitude above air equilibrium. Concentrations of CH4 and CO2 increased by orders of magnitude with depth in the southern lakes, however these gradients were less marked or absent in the North. Strong CH4 and CO2 emissions were associated with gas ebullition, but these were greatly exceeded by diffusive fluxes, in contrast to thermokarst lakes studied elsewhere. Also unusual relative to other studies to date, the surface concentrations of both gases increased as a linear function of water column depth, with highest values over the central, deepest portion of the lakes. Radiocarbon dating of ebullition gas samples showed that the CH4 had 14C-ages from 760 yr to 2005 yr before present, while the CO2 was consistently younger.  Peatland thermokarst lakes may be an increasingly important source of greenhouse gases as the southern permafrost limit continues to shift northwards.”
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #131 on: July 17, 2017, 11:39:28 PM »
The linked reference highlights the importance of using multiple oceans when using climate models to project multi-decadal rates of global warming:

Shuai-Lei Yao, Jing-Jia Luo, Gang Huang & Pengfei Wang (2017), "Distinct global warming rates tied to multiple ocean surface temperature changes", Nature Climate Change,  7,  486–491, doi:10.1038/nclimate3304

http://www.nature.com/nclimate/journal/v7/n7/full/nclimate3304.html

Abstract: "The globally averaged surface temperature has shown distinct multi-decadal fluctuations since 1900, characterized by two weak slowdowns in the mid-twentieth century and early twenty-first century and two strong accelerations in the early and late twentieth century. While the recent global warming (GW) hiatus has been particularly ascribed to the eastern Pacific cooling, causes of the cooling in the mid-twentieth century and distinct intensity differences between the slowdowns and accelerations remain unclear. Here, our model experiments with multiple ocean sea surface temperature (SST) forcing reveal that, although the Pacific SSTs play essential roles in the GW rates, SST changes in other basins also exert vital influences. The mid-twentieth-century cooling results from the SST cooling in the tropical Pacific and Atlantic, which is partly offset by the Southern Ocean warming. During the recent hiatus, the tropical Pacific-induced strong cooling is largely compensated by warming effects of other oceans. In contrast, during the acceleration periods, ubiquitous SST warming across all the oceans acts jointly to exaggerate the GW. Multi-model simulations with separated radiative forcing suggest diverse causes of the SST changes in multiple oceans during the GW acceleration and slowdown periods. Our results highlight the importance of multiple oceans on the multi-decadal GW rates."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #132 on: July 17, 2017, 11:48:18 PM »
The linked reference discusses improved modeling of biospheric feedback effects in a synchronously coupled model of human and Earth systems:

Peter E. Thornton, et. al. (2017), "Biospheric feedback effects in a synchronously coupled model of human and Earth systems", Nature Climate Change, 7,  496–500, doi:10.1038/nclimate3310

http://www.nature.com/nclimate/journal/v7/n7/full/nclimate3310.html

Abstract: "Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO 2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #133 on: July 21, 2017, 05:11:26 PM »
In the way of color commentary, it seems to me that the linked reference (and associated article) about biospheric feedback effect in a synchronously coupled model of human and Earth system is a play to try to document the potential validity of negative emissions technology like BECCS using ACME (Phase 1).  While ACME tries to account for the impact of phosphorous on the biosphere, I am concerned that much of their focus on BECCS is just happy talk, which will not prevent a socio-economic collapse in the 2050 to 2060 timeframe.  Nevertheless, it appears that these BECCS assumptions & associated projections will be rolled into both CMIP6 and AR6 to further the illusion that the situation is in capable hands (i.e. the DOE [which runs ACME] controlled by Rick Perry).

Peter E. Thornton et al, Biospheric feedback effects in a synchronously coupled model of human and Earth systems, Nature Climate Change (2017). DOI: 10.1038/nclimate3310

http://www.nature.com/nclimate/journal/v7/n7/full/nclimate3310.html?foxtrotcallback=true

Abstract: "Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO 2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date."

See also the associated linked article entitled:  Titan simulations show importance of close two-way coupling between human and Earth systems"

https://phys.org/news/2017-07-titan-simulations-importance-two-way-coupling.html

Extract: "Through the Advanced Scientific Computing Research Leadership Computing Challenge program, Thornton's team was awarded 85 million compute hours to improve the Accelerated Climate Modeling for Energy (ACME) effort, a project sponsored by the Earth System Modeling program within DOE's Office of Biological and Environmental Research. Currently, ACME collaborators are focused on developing an advanced climate model capable of simulating 80 years of historic and future climate variability and change in 3 weeks or less of computing effort.

Now in its third year, the project has achieved several milestones—notably the development of ACME version 1 and the successful inclusion of human factors in one of its component models, the iESM.

"What's unique about ACME is that it's pushing the system to a higher resolution than has been attempted before," Thornton said. "It's also pushing toward a more comprehensive simulation capability by including human dimensions and other advances, yielding the most detailed Earth system models to date.

The development of iESM started before the ACME initiative when a multilaboratory team aimed to add new human dimensions—such as how people affect the planet to produce and consume energy—to Earth system models. The model—now a part of the ACME human dimensions component—is being merged with ACME in preparation for ACME version 2.

ACME version 1 will be publicly released in late-2017 for analysis and use by other researchers. Results from the model will also contribute to the Coupled Model Intercomparison Project, which provides foundational material for climate change assessment reports."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #134 on: July 23, 2017, 04:20:22 PM »
The linked reference projects substantial dynamical ocean response to projected changes in the global water cycle from RCP 8.5.  Just image how much response would occur due to freshwater hosing from Hansen's ice-climate feedback mechanism:

Xin Liu, Armin Köhl & Detlef Stammer (22 July 2017), "Dynamical ocean response to projected changes of the global water cycle", Journal of Geophysical Research Oceans, DOI: 10.1002/2017JC013061

http://onlinelibrary.wiley.com/doi/10.1002/2017JC013061/abstract?utm_content=buffere7420&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Abstract: "Over the next century substantial changes will occur in the ocean as a consequence of an accelerated global hydrological cycle and the associated net surface freshwater flux change is projected to result from global warming. This paper is concerned with the dynamical response to the associated surface volume flux anomalies. Based on ocean model runs driven by RCP8.5 surface freshwater flux anomalies over the period 2081-2100 relative to 1986-2005, we show that the adjustment of the circulation involves a barotropic circulation response as predicted from the Goldsbrough-Stommel theory. The corresponding barotropic circulation intensifies by approximately 20% with a stronger intensification of about 50% in the Southern Ocean, comparing to the present-day Goldsbrough-Stommel Circulation. The barotropic circulation anomaly induced by intensified freshwater flux reaches to 0.6 Sv in the Antarctic Circumpolar Current region. The adjustment also involves changes in the meridional overturning circulation mirroring the basin-wide averages of changes in the convergence and divergence of the mass transport driven by the surface volume flux. The subsequent pathways of fresh water match with the spreading of volume flux in the shallow cells but diverge substantially with depth. Associated with changes of the flow field are the changes in meridional heat and freshwater transports. Changes in the circulation also lead to a redistribution of temperature and salinity from which a significant contribution result in form of regional steric sea level changes. These changes are of the order of 0.5 cm and can be largely attributed to the displacement of the isopycnals."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #135 on: July 24, 2017, 05:43:26 PM »
The linked reference indicates that extreme El Nino events could double in frequency if/when we reach a 1.5C increase in global mean surface temperature anom. relative to pre-industrial:

Guojian Wang, et. al. (2017), " Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization", Nature Climate Change, doi:10.1038/nclimate3351

http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate3351.html?foxtrotcallback=true

Abstract: "The Paris Agreement aims to constrain global mean temperature (GMT) increases to 2 °C above pre-industrial levels, with an aspirational target of 1.5 °C. However, the pathway to these targets and the impacts of a 1.5 °C and 2 °C warming on extreme El Niño and La Niña events—which severely influence weather patterns, agriculture, ecosystems, public health and economies—is little known. Here, by analysing climate models participating in the Climate Model Intercomparison Project’s Phase 5 (CMIP5) under a most likely emission scenario, we demonstrate that extreme El Niño frequency increases linearly with the GMT towards a doubling at 1.5 °C warming. This increasing frequency of extreme El Niño events continues for up to a century after GMT has stabilized, underpinned by an oceanic thermocline deepening that sustains faster warming in the eastern equatorial Pacific than the off-equatorial region. Ultimately, this implies a higher risk of extreme El Niño to future generations after GMT rise has halted. On the other hand, whereas previous research suggests extreme La Niña events may double in frequency under the 4.5 °C warming scenario, the results presented here indicate little to no change under 1.5 °C or 2 °C warming."

See also: "‘Extreme’ El Niños to double in frequency under 1.5C of warming, study says"

https://www.carbonbrief.org/extreme-el-ninos-double-frequency-under-one-point-five-celsius-warming-study

Extract: "Now a new study, published in Nature Climate Change, suggests that similar “extreme” El Niño events could become more frequent as global temperatures rise.

If global warming reaches 1.5C above pre-industrial levels – the aspirational limit of the Paris Agreement – extreme El Niño events could happen twice as often, the researchers find.

That means seeing an extreme El Niño on average every 10 years, rather every 20 years."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

rboyd

  • ASIF Citizen
  • Posts: 449
    • View Profile
Re: Modelling the Anthropocene
« Reply #136 on: July 24, 2017, 10:45:20 PM »
If I understand correctly, more frequent extreme El Nino events, with no increase in extreme La Nina, will act as a positive feedback. More periods of warm surface waters in the Pacific that exchange heat with the atmosphere, and El Nino related jumps in atmospheric carbon dioxide.

Only benefit would seem to be fewer hurricanes in the Atlantic.

AbruptSLR

  • ASIF Emperor
  • Posts: 12069
    • View Profile
Re: Modelling the Anthropocene
« Reply #137 on: July 25, 2017, 03:30:05 AM »
If I understand correctly, more frequent extreme El Nino events, with no increase in extreme La Nina, will act as a positive feedback. More periods of warm surface waters in the Pacific that exchange heat with the atmosphere, and El Nino related jumps in atmospheric carbon dioxide.

Only benefit would seem to be fewer hurricanes in the Atlantic.

Concur, but more extreme El Ninos can also accelerate the degradation of the WAIS
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson