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Author Topic: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME  (Read 15705 times)

AbruptSLR

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Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #100 on: July 05, 2017, 07:23:00 PM »
The linked reference correlates changes in large-scale weather patterns with changes in surface temperature gradients in the N.H.:

Molnos, S., Petri, S., Lehmann, J., Peukert, E., and Coumou, D.: The sensitivity of the large-scale atmosphere circulation to changes in surface temperature gradients in the Northern Hemisphere, Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-65, in review, 2017.

http://www.earth-syst-dynam-discuss.net/esd-2017-65/

Abstract. Climate and weather conditions in the mid-latitudes are strongly driven by the large-scale atmosphere circulation. Observational data indicates that important components of the large-scale circulation have changed in recent decades including the strength of the Hadley cell, jet streams, storm tracks and planetary waves. Associated impacts cover a broad range, including changes in the frequency and nature of weather extremes and shifts of fertile habitats with implications for biodiversity and agriculture. Dynamical theories have been proposed that link the shift of the poleward edge of the Northern Hadley cell to changes in the meridional temperature gradient. Moreover, model simulations have been carried out to analyse the cause of observed and projected changes in the large-scale atmosphere circulation. However, the question of the underlying drivers and particularly the possible role of global warming is still debated. Here, we use a statistical-dynamical atmosphere model (SDAM) to analyse the sensitivity of the Northern Hemisphere Hadley cell, storm tracks, jet streams and planetary waves to changes in temperature fields by systematically altering the zonal and meridional temperature gradient as well as the global mean surface temperature.  SDAMs are computationally fast compared to more complex general circulation models (GCM) which enables us to scan a large and high-dimensional parameter space for sensitivity analyses using more than thousand individual model runs.

Our results show that the strength of the Hadley cell, storm tracks and jet streams depends almost linearly on both the global mean temperature and the meridional temperature gradient whereas the zonal temperature gradient has little or no influence. The magnitude of planetary waves is clearly affected by all three temperature components. Finally, the width of the Hadley cell behaves nonlinearly with respect to all three temperature components.

Under global warming the meridional temperature gradient is expected to change: Enhanced warming is expected in the Arctic, largely near the surface, and at the equator at high altitudes. Also there is a pronounced seasonality to these warming patterns. Using SDAMs to disentangle and separately analyse the effect of individual temperature changes might thus help to understand observed and projected changes in large-scale atmosphere dynamics.
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #101 on: July 07, 2017, 04:29:15 PM »
One of the many Achilles heels (others include: Hansen's ice-climate feedback, timing of slow response feedbacks, and dynamical climate attractors) of climate change projection is uncertainty about feedbacks from CO₂ absorption/emissions from the terrestrial biosphere.  The linked article discusses new findings on how to better calibrate this feedback mechanism via tracking of carbonyl sulfide.  In the attached image GPP means gross primary production

Campbell, J. E., et al. (05 July 2017.), "Assessing a new clue to how much carbon plants take up", Eos, 98, https://doi.org/10.1029/2017EO075313

https://eos.org/features/assessing-a-new-clue-to-how-much-carbon-plants-take-up?utm_source=eos&utm_medium=email&utm_campaign=EosBuzz070717

Extract: "Current climate models disagree on how much carbon dioxide land ecosystems take up for photosynthesis. Tracking the stronger carbonyl sulfide signal could help.

Climate change projections include an Achilles heel: We don’t know enough about feedbacks from the terrestrial biosphere. Plants and other organisms take in carbon dioxide (CO2), which they use to manufacture their own food, using photosynthesis. This process lets ecosystems sequester atmospheric CO2, creating one of the largest known feedbacks in the climate system. But models of the global climate system differ greatly in their estimates of carbon uptake, leading to critical uncertainties in global climate projections.

This predicament has inspired a search for new approaches to study the photosynthetic uptake of CO2. In response, atmospheric scientists, biogeochemists, and oceanographers have proposed measuring a gas called carbonyl sulfide (COS or OCS) to help quantify the contribution that photosynthesis makes to carbon uptake. COS is similar in structure and composition to CO2, with a sulfur atom replacing one of CO2’s oxygen atoms.

Ten years ago, scientists discovered a massive and persistent biosphere signal in atmospheric COS measurements. In these data, COS and CO2 levels follow a similar seasonal pattern, but the COS signal is much stronger over continental regions, suggesting that the terrestrial biosphere is a sink for COS"
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #102 on: July 07, 2017, 05:13:06 PM »

The linked reference provides useful insight in how to untangle the impacts of efficacies of forcing and ocean heat uptake on the evolution of radiative feedbacks:

A. D. Haugstad, K. C. Armour, D. S. Battisti & B. E. J. Rose (6 July 2017), "Relative roles of surface temperature and climate forcing patterns in the inconstancy of radiative feedbacks", Geophysical Research Letters, DOI: 10.1002/2017GL074372 

http://onlinelibrary.wiley.com/doi/10.1002/2017GL074372/abstract?utm_content=bufferca02a&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Abstract: "Radiative feedbacks robustly vary over time in transient warming simulations. Published studies offer two explanations: (i) evolving patterns of ocean heat uptake (OHU) or radiative forcing give rise to OHU or forcing ‘efficacies’, and (ii) evolving patterns of surface temperature change. This study seeks to determine whether these explanations are indeed distinct. Using an idealized framework of an aquaplanet atmosphere-only model, we show radiative feedbacks depend on the pattern of climate forcing. Yet, the same feedbacks arise when the temperature pattern induced by that climate forcing is prescribed in the absence of any forcing. These findings suggest the perspective that feedbacks are influenced by ‘efficacies’ of forcing and OHU is equivalent to the perspective that feedbacks are dependent on the temperature patterns induced by those forcings. These findings suggest that prescribed surface temperature simulations are valuable for studying the temporal evolution of radiative feedbacks."
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #103 on: July 09, 2017, 05:02:07 PM »
The linked reference raises an important and complex topic that is poorly understood: "The nexus between sea ice and polar emissions of marine biogenic aerosols.  I hope that the complexity of this topic does not cause climate model makers to underplay the risk that an increase in polar marine biogenic aerosols could increase rainfall, which could increase polar amplification in the future.

Albert Gabric, Patricia Matrai, Graham Jones, and Julia Middleton (July 7, 2017), "The nexus between sea ice and polar emissions of marine biogenic aerosols", BAMS, https://doi.org/10.1175/BAMS-D-16-0254.1

http://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-16-0254.1?utm_content=buffer45905&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Abstract: "We examine the relationship between sea ice dynamics, phytoplankton biomass and emissions of marine biogenic aerosols in both Arctic and Southern Oceans.

Accurate estimation of the climate sensitivity requires a better understanding of the nexus between polar marine ecosystem responses to warming, changes in sea ice extent and emissions of marine biogenic aerosol (MBA). Sea ice brine channels contain very high concentrations of MBA precursors that once ventilated have the potential to alter cloud microphysical properties, such as cloud droplet number, and the regional radiative energy balance. In contrast to temperate latitudes, where the pelagic phytoplankton are major sources of MBAs, the seasonal sea ice dynamic plays a key role in determining MBA concentration in both the Arctic and Antarctic. We review the current knowledge of MBA sources and the link between ice melt and emissions of aerosol precursors in the polar oceans. We illustrate the processes by examining decadal scale time series in various satellite-derived parameters such as aerosol optical depth (AOD), sea ice extent and phytoplankton biomass in the sea ice zones of both hemispheres. The sharpest gradients in aerosol indicators occur during the spring period of ice melt. In sea ice covered waters, the peak in AOD occurs well before the annual maximum in biomass in both hemispheres. The results provide strong evidence that suggests seasonal changes in sea ice and ocean biology are key drivers of the polar aerosol cycle. The positive trend in annual mean Antarctic sea ice extent is now almost one-third of the magnitude of the annual mean decrease in Arctic sea ice, suggesting the potential for different patterns of aerosol emissions in the future."

Extract: "Marine biogenic aerosol (MBA) plays an important role in the radiative budget of remote marine atmospheres by potentially shaping regional climate (McCoy et al. 2015). MBAs can influence cloud microphysical properties as cloud condensation nuclei (CCN), affecting cloud albedo and lifetime.

There is now strong evidence to suggest that ocean biology augments the aerosol and cloud droplet concentration and radiative forcing also over the biologically active SO by a significant amount (McCoy et al. 2015; Vallina et al. 2006)."
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #104 on: July 10, 2017, 04:51:49 AM »
Hopefully, CMIP6 will learn that summertime atmospheric may contribute up to 60% of the September sea-ice extent loss:

Qinghua Ding, Axel Schweiger, Michelle L’Heureux, David S. Battisti, Stephen Po-Chedley,Nathaniel C. Johnson, Eduardo Blanchard-Wrigglesworth, Kirstin Harnos, Qin Zhang, Ryan Eastman & Eric J. Steig (2017), “Influence of high-latitude atmospheric circulation changes on summertime Arctic sea ice”, Nature Climate Change, 7, 289–295, doi:10.1038/nclimate3241

http://www.nature.com/nclimate/journal/v7/n4/abs/nclimate3241.html

Abstract: “The Arctic has seen rapid sea-ice decline in the past three decades, whilst warming at about twice the global average rate. Yet the relationship between Arctic warming and sea-ice loss is not well understood. Here, we present evidence that trends in summertime atmospheric circulation may have contributed as much as 60% to the September sea-ice extent decline since 1979. A tendency towards a stronger anticyclonic circulation over Greenland and the Arctic Ocean with a barotropic structure in the troposphere increased the downwelling longwave radiation above the ice by warming and moistening the lower troposphere. Model experiments, with reanalysis data constraining atmospheric circulation, replicate the observed thermodynamic response and indicate that the near-surface changes are dominated by circulation changes rather than feedbacks from the changing sea-ice cover. Internal variability dominates the Arctic summer circulation trend and may be responsible for about 30–50% of the overall decline in September sea ice since 1979.”
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #105 on: July 10, 2017, 05:15:52 AM »
My last post focused on research focused on Arctic summertime sea ice, while the linked reference discusses a positive feedback (associated with longwave radiation) for Arctic sea ice during wintertime (I hope CMIP6 is paying attention):

Kwang-Yul Kim, Jinju Kim, Saerim Yeo, Hanna Na , Benjamin D. Hamlington, and Robert R. Leben (2017), “Understanding the Mechanism of Arctic Amplification and Sea Ice Loss”, The Cryosphere Discuss., doi:10.5194/tc-2017-39

http://www.the-cryosphere-discuss.net/tc-2017-39/tc-2017-39.pdf

Abstract: “Sea ice reduction is accelerating in the Barents and Kara Seas. Several mechanisms are proposed to explain the accelerated loss of polar sea ice, which remains an open question. In the present study, the detailed physical mechanism of sea ice reduction in winter is identified using the daily ERA interim reanalysis data. Downward longwave radiation is an essential element for sea ice reduction, but can only be sustained by excessive upward heat flux from the sea surface exposed to air in the region of sea ice loss. The increased turbulent heat flux is used to increase air temperature and specific humidity in the lower troposphere, which in turn increases downward longwave radiation. This feedback process is clearly observed in the Barents and Kara Seas in the reanalysis data. A quantitative assessment reveals that this feedback process is amplifying at the rate of ~8.9 % every year during 1979-2016. Based on this estimate, sea ice will completely disappear in the Barents and Kara Seas by around 2025. Availability of excessive heat flux is necessary for the maintenance of this feedback process; a similar mechanism of sea ice loss is expected to take place over the sea-ice covered polar region when sea ice is not fully recovered in winter.”
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #106 on: July 11, 2017, 05:39:25 PM »
The linked reference indicates that current climate models are biased w.r.t. methane emissions from global wetlands (as in ESLD), and recommends that the uncertainties associated with such bias be reduced.

Bowen Zhang, Hanqin Tian , Chaoqun Lu, Guangsheng Chen, Shufen Pan, Christopher Anderson & Benjamin Poulter (September 2017), "Methane emissions from global wetlands: An assessment of the uncertainty associated with various wetland extent data sets", Atmospheric Environment, Volume 165, Pages 310–321, https://doi.org/10.1016/j.atmosenv.2017.07.001

http://www.sciencedirect.com/science/article/pii/S1352231017304429

Abstract: "A wide range of estimates on global wetland methane (CH4) fluxes has been reported during the recent two decades. This gives rise to urgent needs to clarify and identify the uncertainty sources, and conclude a reconciled estimate for global CH4 fluxes from wetlands. Most estimates by using bottom-up approach rely on wetland data sets, but these data sets show largely inconsistent in terms of both wetland extent and spatiotemporal distribution. A quantitative assessment of uncertainties associated with these discrepancies among wetland data sets has not been well investigated yet. By comparing the five widely used global wetland data sets (GISS, GLWD, Kaplan, GIEMS and SWAMPS-GLWD), it this study, we found large differences in the wetland extent, ranging from 5.3 to 10.2 million km2, as well as their spatial and temporal distributions among the five data sets. These discrepancies in wetland data sets resulted in large bias in model-estimated global wetland CH4 emissions as simulated by using the Dynamic Land Ecosystem Model (DLEM). The model simulations indicated that the mean global wetland CH4 emissions during 2000–2007 were 177.2 ± 49.7 Tg CH4 yr−1, based on the five different data sets. The tropical regions contributed the largest portion of estimated CH4 emissions from global wetlands, but also had the largest discrepancy. Among six continents, the largest uncertainty was found in South America. Thus, the improved estimates of wetland extent and CH4 emissions in the tropical regions and South America would be a critical step toward an accurate estimate of global CH4 emissions. This uncertainty analysis also reveals an important need for our scientific community to generate a global scale wetland data set with higher spatial resolution and shorter time interval, by integrating multiple sources of field and satellite data with modeling approaches, for cross-scale extrapolation."
“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: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #107 on: July 12, 2017, 12:47:16 AM »
The linked reference confirms that the Earth is warming at unprecedented rates, and which provides data that can be used to better calibrate climate models:

PAGES2k Consortium (2017), "A global multiproxy database for temperature reconstructions of the Common Era", Scientific Data 4, Article number: 170088, doi:10.1038/sdata.2017.88

http://www.nature.com/articles/sdata201788

Abstract: "Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #108 on: July 14, 2017, 06:32:00 PM »
he linked reference discusses efforts to improve the calibration of models for the Greenland Ice Sheet in CMIP6:

Goelzer, H., Nowicki, S., Edwards, T., Beckley, M., Abe-Ouchi, A., Aschwanden, A., Calov, R., Gagliardini, O., Gillet-Chaulet, F., Golledge, N. R., Gregory, J., Greve, R., Humbert, A., Huybrechts, P., Kennedy, J. H., Larour, E., Lipscomb, W. H., Le clec´h, S., Lee, V., Morlighem, M., Pattyn, F., Payne, A. J., Rodehacke, C., Rückamp, M., Saito, F., Schlegel, N., Seroussi, H., Shepherd, A., Sun, S., van de Wal, R., and Ziemen, F. A.: Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-129, in review, 2017.

http://www.the-cryosphere-discuss.net/tc-2017-129/

Abstract. Earlier large-scale Greenland ice sheet sea-level projections (e.g., those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions can have a large effect on the projections and give rise to important uncertainties. The goal of the initMIP-Greenland intercomparison exercise is to compare, evaluate and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6). Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of 1) the initial present-day state of the ice sheet and 2) the response in two schematic forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly), and should not be interpreted as sea-level projections. We present and discuss results that highlight the wide diversity of data sets, boundary conditions and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to SMB changes in areas where the simulated ice sheets overlap, but in general differences arise due to the initial size of the ice sheet. The spread in model drift is reduced compared to earlier intercomparison exercises.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #109 on: July 14, 2017, 06:34:30 PM »
The linked reference discusses efforts to improve modeling of black carbon impacts on the Third Pole.

Zhang, Y., Kang, S., Sprenger, M., Cong, Z., Gao, T., Li, C., Tao, S., Li, X., Zhong, X., Xu, M., Meng, W., and Sillanpää, M.: Black carbon and mineral dust in snow cover on the Third Pole, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-111, in review, 2017.

http://www.the-cryosphere-discuss.net/tc-2017-111/

Abstract. Light-absorbing impurities (including black carbon, organic carbon, and mineral dust) deposited on snow can reduce surface albedo and contribute to the near-worldwide melting of snow cover and ice. This study found that the black carbon, organic carbon, and dust concentrations in snow cover ranged generally from 202–17 468 ng g−1, 491–13 880 ng g−1, and 22–846 µg g−1, respectively, with higher concentrations in the central to northern areas of the Third Pole region (referred to by scientists also as the Tibetan Plateau and its surrounding mountains). Footprint analyses suggested that the northern Third Pole was influenced mainly by air masses from Central Asia with some Euro-Asia influence; air masses in the central and Himalayan region originated mainly from Central and South Asia. The open burning-sourced black carbon contributions decreased from ~ 50 % in the southern Third Pole region to ~ 30 % in the northern Third Pole region. The contribution of black carbon and dust to snow albedo reduction reached approximately 37 % and 15 %, respectively. The effect of black carbon and dust reduced the average snow cover duration by 3.1 ± 0.1 days to 4.4 ± 0.2 days. Meanwhile, the black carbon and dust had an import implication for snowmelt water loss over the Third Pole region. Findings indicate that the impacts of black carbon and mineral dust need to be properly accounted for in future regional climate projections, particularly in the high-altitude cryosphere.
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #110 on: July 15, 2017, 08:45:36 PM »
Low cloud cover (LCC) is associated with negative climate change feedback; thus the finding of the linked reference that LCC decreases with continued warming indicates that ECS is likely higher than assumed by AR5:

Daniel T. McCoy, Ryan Eastman, Dennis L. Hartmann, and Robert Wood (2017), “The Change in Low Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim”, Journal of Climate, https://doi.org/10.1175/JCLI-D-15-0734.1

http://journals.ametsoc.org/doi/10.1175/JCLI-D-15-0734.1

Abstract: “Decreases in subtropical low cloud cover (LCC) occur in climate model simulations of global warming. In this study 8-day-averaged observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) spanning 2002–14 are combined with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis to compute the dependence of the observed variability of LCC on various predictor variables. Large-scale thermodynamic and dynamic predictors of LCC are selected based on insight from large-eddy simulations (LESs) and observational analysis. It is found that increased estimated inversion strength (EIS) is associated with increased LCC. Drying of the free troposphere is associated with decreased LCC. Decreased LCC accompanies subsidence in regions of relatively low EIS; the opposite is found in regions of high EIS. Finally, it is found that increasing sea surface temperature (SST) leads to a decrease in LCC. These results are in keeping with previous studies of monthly and annual data. Based upon the observed response of LCC to natural variability of the control parameters, the change in LCC is estimated for an idealized warming scenario where SST increases by 1 K and EIS increases by 0.2 K. For this change in EIS and SST the LCC is inferred to decrease by 0.5%–2.7% when the regression models are trained on data observed between 40°S and 40°N and by 1.1%–1.4% when trained on data from trade cumulus–dominated regions. When the data used to train the regression model are restricted to stratocumulus-dominated regions the change in LCC is highly uncertain and varies between −1.6% and +1.4%, depending on the stratocumulus-dominated region used to train the regression model.”
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
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Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #111 on: July 21, 2017, 05:07:48 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.

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