Please support this Forum and Neven's Blog

Author Topic: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME  (Read 19615 times)

AbruptSLR

  • ASIF Emperor
  • Posts: 12765
    • View Profile
I have repeated noted (in numerous folders/threads) that virtually all of the AR5 process-based climate projections, and associated literature, present at best low-bound estimates of potential climate consequences.  These lower-bound projections do not adequately account for numerous considerations include: phases of decadal cycles (ala the PDO, etc), initial model conditions and boundary effects, limited understanding of non-linear feedback mechanisms, limited understanding of aerosol radiative forcing mechanisms; limited understanding of anthropogenic radiative forcing scenarios, misinterpretations of paleo-data, climate model limitations, etc, etc.

The next best thing to developing upper-bound projections would be to progressively calibrate each phase of the DOE's non-linear ACME program that its hind-casts reasonably match both observed, and paleo, data and then to use the progressively calibrated ACME program to make improved projections. 

This requires the development & use of "climate model test beds", such as that discussed in the linked EOS article, which for ACME, will be ready for use by the end of 2016.  With this in mind, I am opening this new thread to discuss the topic of how to better calibrate state of the art nonlinear Earth System Models, ESMs, using "climate model test beds" (see the attached image for the ACME climate model test bed architecture):


https://eos.org/project-updates/better-tools-to-build-better-climate-models

Extract: "To determine the accuracy of predictions, results are validated by comparing them to present-day observations.  As new data are fed to the model and scientific understanding of climate systems evolves, new information gets built into the model, and the testing and validation continue.

One of the most resource-intensive aspects of climate modeling is the creation of a system for calibrating climate models, where model simulations are used to validate model output against observational data sets that span the globe. We call this system a “climate model test bed.” Such test bed environments typically evaluate each component of the model in isolation, using a skeleton framework that makes the module behave as if it were functioning within the larger program.

The prototype test bed team is now under the banner of the newly formed Accelerated Climate Modeling for Energy (ACME) project, under the auspices of the U.S. Department of Energy’s Office of Science. Under ACME, the team will continue its efforts to deliver an advanced model development, testing, and execution workflow and data infrastructure production test bed for DOE climate and energy research needs. We anticipate rolling out the test bed by end of 2016 for ACME use."
« Last Edit: February 15, 2016, 10:57:46 AM by AbruptSLR »
“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: 12765
    • View Profile
Re: Climate Model Test Beds for Calibrating Nonlinear ESMs focused on ACME
« Reply #1 on: February 14, 2016, 11:16:50 PM »
As ESMs are very complex and utilize numerous models (e.g. for clouds, oceans, etc.), they typically need numerous different climate test beds, such as the two discussed below:

The linked website discusses NOAA/NCEP's efforts on a Climate Test Bed (CTB):

http://www.nws.noaa.gov/ost/CTB/ov.htm

Extract: "NOAA/NCEP is the lead agency with responsibility for producing US operational climate monitoring, models and predictions on time scales ranging from weeks to years. The mission of NOAA Climate Test Bed (CTB) is to accelerate research-to-operation (R2O) to improve NCEP operational climate models, monitoring and predictions, and to provide operations-to-research (O2R) support to the climate research community with access to operational models, forecast tools and datasets."


The linked website addresses the Lawrence Livermore National Lab's efforts on the Cloud-Associated Parameterizations Testbed (CAPT):

http://www-pcmdi.llnl.gov/projects/capt/

Extract: "The Cloud-Associated Parameterizations Testbed (CAPT) aims to diagnose and improve the representation in climate models of cloud-associated physical processes. In the CAPT, weather forecast techniques are applied to climate models , with an emphasis on the simulations of the Community Atmosphere Model. We will be extending the concept of weather forecasts from the atmosphere to the fully coupled ocean-atmosphere model. Three foci of the project include:
- Comparing of model simulations to detailed process observations available from the ARM data
- Diagnosing the origin of errors in model simulations of climate
- Testing new model parameterizations in order to identify their strengths/weaknesses in simulating cloud-associated processes."

See also:
https://pls.llnl.gov/people/divisions/atmospheric-earth-and-energy-division

Edit: I provide the following link to a DOE pdf on a 2013 Atmospheric Testbed Workshop, and I note that essentially all of the software mentioned in the pdf are now functional:

http://science.energy.gov/~/media/ber/pdf/Brochures/CESD_Atmospheric_Testbed_Workshop_V9.pdf
« Last Edit: February 15, 2016, 10:22:19 PM by AbruptSLR »
“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: 12765
    • View Profile
Re: Climate Model Test Beds for Calibrating Nonlinear ESMs focused on ACME
« Reply #2 on: February 14, 2016, 11:19:41 PM »
The linked reference discusses an improved hindcast approach that can be used in climate model test beds to improve the calibration of complex ESMs:

Ma, H.-Y., C. C. Chuang, S. A. Klein, M.-H. Lo, Y. Zhang, S. Xie, X. Zheng, P.-L. Ma, Y. Zhang, and T. J. Phillips (2015), "An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models", JAMES, Volume 7, Issue 4, Pages 1810–1827 DOI: 10.1002/2015MS000490

 
http://onlinelibrary.wiley.com/doi/10.1002/2015MS000490/full?campaign=wlytk-41855.5282060185

Abstract: "We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a “Core” integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #3 on: February 15, 2016, 11:16:25 AM »
The linked website indicates that from Dec 2016 until Dec 2017, Scripps (lead by Julie McClean) will investigate "Ocean and Sea-Ice Processes" (including both basal melting from ice shelves and grounding lines) in Antarctica  for the ACME program.

https://scripps.ucsd.edu/research/proposals/accelerated-climate-modeling-energy-acme-ocean-and-sea-ice-processes

Extract: "For cryosphere, the team will examine the near-term risks of initiating the dynamic instability and onset of the collapse of the Antarctic Ice Sheet due to rapid melting by warming waters adjacent to the ice sheet grounding lines.
 
The experiment would be the first fully coupled global simulation to include dynamic ice shelf–ocean interactions for addressing the potential instability associated with grounding line dynamics in marine ice sheets around Antarctica."

Furthermore, the linked April 2015 video of Richard Alley's talk about the risk that mainstream science may not have yet recognized the risk of abrupt sea level rise contribution from the WAIS (West Antarctic Ice Sheet) . In it, Alley concludes his talk by calling for more oceanic-ice interaction investigation; which is precisely what the focus of the research to be conducted at Scripps from Dec 2016 to Dec 2017 as part of the ACME program.  I believe that Alley believes that currently the ice mass loss from critical marine glaciers in both the Amundsen, and Bellingshausen, Sea Sectors is limited by "plugs" that could be degraded by "Ocean and Sea-Ice Processes".  Once the "plugs" are lost then both cliff failures and hydrofracturing could result in abrupt SLR contributions from the WAIS.  In light of Hansen et al (2015) such an abrupt SLR contribution would need be simulated by "hosing" fresh meltwater into the Southern Ocean portion of the ACME model:

https://www.youtube.com/watch?v=yCunWFmvUfo

“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #4 on: February 15, 2016, 04:16:15 PM »
I provide the first linked reference (& the four associate images) because the Community Earth System Model, CESM, is the primary basis for the ACME model, and thus lessons learned comparing observed vs CESM projected surface mass balance, SMB, for Antarctica is of primary interest to this thread. 

First, I note that SMB is the prime driver for ice mass loss from the Greenland Ice Sheet, but not from Antarctica; as in Antarctica the SMB has been increasing (since at least 1850) while recently at least the West Antarctic Ice Sheet, WAIS, has been losing ice mass as measured by the GRACE satellite, due to calving from marine glaciers. 

Second, I note that the Scripps effort noted in the immediate prior post, addresses the ocean-ice interaction modeling going on to address this keep aspect of Antarctic ice mass loss (note that geothermal basal melting is also a significant factor). 

Third, I note that no effect that I am aware of for either the CESM or the ACME Antarctic modeling effort consider such state-of-the-art mechanisms as cliff failures, hydrofracturing, or the positive feedback (to increase global warming) projected by Hansen et al (2015) due to the potential growth of Antarctic sea ice extent due to freshening of the Southern Ocean. 

Fourth, I note that the ACME program is a 7-year program and the Scripps effort should conclude the first 3-year phase of ACME, thus acknowledging the need for more Antarctic modeling beyond the first phase. 

Fifth, the second linked article discusses a new 5-year international effort [called: Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES)] to improve modeling of the Antarctic and Greenland Ice Sheets, in which ACME (Sandia Lab) is participating. 

Finally, I note that at some point in the future (say when both ACME & PISCEES are finished in 2021), I believe that the least test data suitable for evaluating the risk of abrupt SLR contribution from Antarctica would be for ACME to model the Eemian era and to match the observed (4m contribution from AIS) SLR contributions:

Jan T. M. Lenaerts, Miren Vizcaino, Jeremy Fyke, Leo van Kampenhout and Michiel R. van den Broeke (2016), "Present‐Day and Future Antarctic Ice Sheet Climate and Surface Mass Balance in the Community Earth System Model." Climate Dynamics, DOI: 10.1007/s00382-015-2907-4.

http://download.springer.com/static/pdf/10/art%253A10.1007%252Fs00382-015-2907-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00382-015-2907-4&token2=exp=1455547955~acl=%2Fstatic%2Fpdf%2F10%2Fart%25253A10.1007%25252Fs00382-015-2907-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252Fs00382-015-2907-4*~hmac=5f4332ecc9ab5bc671638126ae42b0c9acd66448999fce0d9a7ada8d2a4fddfb

http://paperity.org/p/75478324/present-day-and-future-antarctic-ice-sheet-climate-and-surface-mass-balance-in-the

Abstract: "We present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ∼1 degrees in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131 Gt year−1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenario RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gt year−1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content."


Extract: "Although model biases remain in CESM, we have shown that it shows great potential to simulate present-day Antarctic surface climate and SMB. An important drawback of this study is associated to the limited snowpack thickness in CESM, being 1 m w.e., which substantially reduces the refreezing potential of the firn. In reality, the
Antarctic snowpack is much thicker, with a large refreezing capacity. This implies that CESM converts meltwater production too easily into runoff; in reality, the increase of runoff will be delayed by refreezing. This effect has been demonstrated by Ligtenberg et al. (2013), a study that used a model allowing for more realistic storage of meltwater.
Their findings should motivate intensified CESM development to include a multi-layered snow model with enhanced vertical resolution (Reijmer et al. 2012). Additionally, we plan future model improvements focusing on CAM5 cloud microphysics, in order to reduce the longwave flux bias.  These future model improvements will allow use of CESM to detect and attribute past, present and future climate change on Antarctica and the impact of AIS SMB on global sea level, to assess the role of ozone depletion and recovery on AIS climate, and to better qualify the role of Antarctica in the global climate system."



http://phys.org/news/2016-02-ice-sheet-greenland-antarctica-sea-level.html

Extract: "The Greenland and Antarctic ice sheets will make a dominant contribution to 21st century sea-level rise if current climate trends continue. However, predicting the expected loss of ice sheet mass is difficult due to the complexity of modeling ice sheet behavior.

To better understand this loss, a team of Sandia National Laboratories researchers has been improving the reliability and efficiency of computational models that describe ice sheet behavior and dynamics. The team includes researchers Irina Demeshko, Mike Eldred, John Jakeman, Mauro Perego, Andy Salinger, Irina Tezaur and Ray Tuminaro.

This research is part of a five-year project called Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES), funded by the U.S. Department of Energy's (DOE) Scientific Discovery through Advanced Computing (SciDAC) program. PISCEES is a multi-lab, multi-university endeavor that includes researchers from Sandia, Los Alamos, Lawrence Berkeley and Oak Ridge national laboratories, the Massachusetts Institute of Technology, Florida State University, the University of Bristol, the University of Texas Austin, the University of South Carolina and New York University.

Sandia's biggest contribution to PISCEES has been an analysis tool, a land-ice solver called Albany/FELIX (Finite Elements for Land Ice eXperiments). The tool is based on equations that simulate ice flow over the Greenland and Antarctic ice sheets and is being coupled to Earth models through the Accelerated Climate for Energy (ACME) project."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #5 on: February 16, 2016, 05:38:02 PM »
The linked reference uses observational data to reduce the uncertainty of subtropical cloud feedback as compared to CMIP5.  This comparison indicates that this feedback will be weakly positive indicating that global warming will occur faster than projected by CMIP5.  Hopefully, this positive subtropical cloud feedback will be included in ACME and other nonlinear ESMs.

T. A. Myers & J. R. Norris (2016), "Reducing the uncertainty in subtropical cloud feedback", Geophysical Research Letters, DOI: 10.1002/2015GL067416

http://onlinelibrary.wiley.com/doi/10.1002/2015GL067416/abstract

Abstract: "Large uncertainty remains on how subtropical clouds will respond to anthropogenic climate change and therefore whether they will act as a positive feedback that amplifies global warming or negative feedback that dampens global warming by altering Earth's energy budget. Here, we reduce this uncertainty using an observationally constrained formulation of the response of subtropical clouds to greenhouse forcing. The observed interannual sensitivity of cloud solar reflection to varying meteorological conditions suggests that increasing sea-surface temperature and atmospheric stability in the future climate will have largely cancelling effects on subtropical cloudiness, overall leading to a weak positive shortwave cloud feedback (0.4±0.9 W m-2 K-1). The uncertainty of this observationally based approximation of the cloud feedback is narrower than the inter-model spread of the feedback produced by climate models. Subtropical cloud changes will therefore complement positive cloud feedbacks identified by previous work, suggesting that future global cloud changes will amplify global warming."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #6 on: February 29, 2016, 06:03:22 PM »
While the linked (open access) reference emphasizes not only the need to get/calibrate model projections to match spatial observations, but also diurnal observations and then to identify the reason for the diurnal asymmetry of feedbacks [in this case dominated by the planetary boundary layer (PBL)]:

Richard Davy, Igor Esau, Alexander Chernokulsky, Stephen Outten, & Sergej Zilitinkevich (24 February 2016), "Diurnal asymmetry to the observed global warming", International Journal of Climatology, DOI: 10.1002/joc.4688

http://onlinelibrary.wiley.com/doi/10.1002/joc.4688/abstract

Abstract: "The observed warming of the surface air temperature (SAT) over the last 50 years has not been homogenous. There are strong differences in the temperature changes both geographically and on different time frames. Here, we review the observed diurnal asymmetry in the global warming trend: the night-time temperatures have increased more rapidly than day-time temperatures. Several explanations for this asymmetric warming have been offered in the literature. These generally relate differences in the temperature trends to regionalized feedback effects, such as changes to cloud cover, precipitation or soil moisture. Here, we discuss a complementary mechanism through which the planetary boundary layer (PBL) modulates the SAT response to changes in the surface energy balance. This reciprocal relationship between boundary-layer depth and temperature response can explain a part of why the night-time has warmed more rapidly than the daytime. We used a multi-linear regression model to compare the effect of the PBL, cloud cover, precipitation and soil moisture on the SAT. From this, we demonstrate that it is the boundary-layer depth which is the strongest predictor of the strength of temperature trends in the boreal annual cycle, and in all seasons except the summer."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #7 on: February 29, 2016, 06:32:11 PM »
The linked article indicates that direct anthropogenic heat release cannot be ignored when calibrating a state-of-the-art ESM, as while small (currently 0.03 W m−2) it has meaningful regional and seasonal effects that can impact global atmospheric circulation patterns (like directing Chinese aerosols to the Arctic):

Bing Chen, Li Dong, X. Liu, G. Y. Shi, L. Chen, T. Nakajima & A. Habib (23 February 2016 ), "Exploring the possible effect of anthropogenic heat release due to global energy consumption upon global climate: a climate model study", International Journal of Climatology, DOI: 10.1002/joc.4669


http://onlinelibrary.wiley.com/doi/10.1002/joc.4669/abstract

Abstract: "The high-resolution global distribution of anthropogenic heat release (AHR), which is generated by human energy consumption, is estimated by means of applying satellite remote sensing. Additionally, it was considered into a global climate model and the possible climatic effect of AHR is examined in this study. AHR is geographically concentrated and fundamentally correlates with economic activity in global scale. The current mean AHR flux on the global scale is approximately 0.03 W m−2; however, the flux reaches a level high enough to influence the regional climate in concentrated urban areas. Global climate model results indicate that AHR may disrupt the normal atmospheric circulation and could have an obvious effect on the surface temperature at middle and high latitudes in summer and winter over the Northern Hemisphere. The climatic effect of AHR differs in various seasons: the global mean surface temperature could increase by approximately 0.02 K in boreal summer and by 0.10 K in boreal winter. With the continued development of the global economy and urbanization, the climatic effect of AHR will become increasingly pronounced. The climatic effect of AHR should not be merely confined to the regional climate, AHR is a tiny but essential factor in global climate and long-term climate change that should not be ignored."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #8 on: March 02, 2016, 04:40:47 PM »
As a follow-on to Reply #6 that current projections do not yet properly account for diurnal influences; the linked reference and associated image, addresses diurnal adjustments to the middle-troposphere temperature (TMT); which eliminates many of the denialist arguments about such atmospheric temperature data:

Carl A. Mears and Frank J. Wentz (2016), "Sensitivity of satellite-derived tropospheric temperature trends to the diurnal cycle adjustment", Journal of Climate, doi: http://dx.doi.org/10.1175/JCLI-D-15-0744.1


http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-15-0744.1?af=R


Abstract: "Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is the middle tropospheric measurements made by the Microwave Sounding Unit (MSU) channel 2, and the Advanced Microwave Sounding Unit (AMSU) channel 5. Previous versions of the RSS dataset have used a diurnal climatology derived from general circulation model output to remove the effects of drifting local measurement time. In this paper, we present evidence that this previous method is not sufficiently accurate, and present several alternative methods to optimize these adjustments using information from the satellite measurements themselves. These are used to construct a number of candidate climate data records using measurements from 15 MSU and AMSU satellites. The new methods result in improved agreement between measurements made by different satellites at the same time. We choose a method based on an optimized second harmonic adjustment to produce a new version of the RSS dataset, Version 4.0. The new dataset shows substantially increased global-scale warming relative to the previous version of the dataset, particularly after 1998. The new dataset shows more warming than most other middle tropospheric data records constructed from the same set of satellites. We also show that the new dataset is consistent with long-term changes in total column water vapor over the tropical oceans, lending support to its long-term accuracy."

Also see:
https://tamino.wordpress.com/2016/03/02/new-dataset-from-rss-end-of-the-satellite-pause/
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson

LRC1962

  • ASIF Citizen
  • Posts: 405
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #9 on: March 03, 2016, 07:21:29 AM »
I agree the absolute need for these very complex models. I do see some problems developing the complexity needed to get a good understanding of what is coming.
1) The most obvious is the political and financial battles that are and will continue to influence what the models work on as the biggest most important sources of getting the financial aid needed for the development and and political interference that naturally comes with that as to what the final conclusions are arrived at, are also the same ones who for their own purposes want a very specific slant to the story. The scientists and researchers that work on these models not only get it from the sources they are trying to get their funding from the very institutes they work in, because those institute depend on funding to operate on from those same sources.
2) Scientist as a whole tend to be very conservative in their work and traditionally fight very hard and collectively against anything that forces them to change what they believe is the truth. You would be very hard pressed to find any development in our understanding of physics today that did not have to take years if not decades of those physicists being cast into the wasteland of their study before their ideas were generally excepted. Those include the now thought of as greats of Galileo, Newton and Einstein.
3) To do the best of job of bringing a credible model, you need to bring together the technical lab scientist together with the theoretical scientist, and to find a matchup that works well together is no easy task since they tend to view science from very different sides of the coin.
We all know of those who have fought the fight and have won, but there are very few records of those who had the same ideas sometimes at the same time or sometimes earlier and lost. Case in point. Galileo is thought of as the first of the greats to develop our current understanding of the solar system. Very few know that Copernicus had those very same ideas many years before. In his case he capitulated to the forces arrayed against him and revised his theory giving us the Copernican model of the solar system.
"All truth passes through three stages: First, it is ridiculed; Second,  it is violently opposed; and Third, it is accepted as self-evident."
       - Arthur Schopenhauer

AbruptSLR

  • ASIF Emperor
  • Posts: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #10 on: March 03, 2016, 04:45:52 PM »
I agree the absolute need for these very complex models. I do see some problems developing the complexity needed to get a good understanding of what is coming.
1) The most obvious is the political and financial battles that are and will continue to influence what the models work on as the biggest most important sources of getting the financial aid needed for the development and and political interference that naturally comes with that as to what the final conclusions are arrived at, are also the same ones who for their own purposes want a very specific slant to the story. The scientists and researchers that work on these models not only get it from the sources they are trying to get their funding from the very institutes they work in, because those institute depend on funding to operate on from those same sources.
2) Scientist as a whole tend to be very conservative in their work and traditionally fight very hard and collectively against anything that forces them to change what they believe is the truth. You would be very hard pressed to find any development in our understanding of physics today that did not have to take years if not decades of those physicists being cast into the wasteland of their study before their ideas were generally excepted. Those include the now thought of as greats of Galileo, Newton and Einstein.
3) To do the best of job of bringing a credible model, you need to bring together the technical lab scientist together with the theoretical scientist, and to find a matchup that works well together is no easy task since they tend to view science from very different sides of the coin.
We all know of those who have fought the fight and have won, but there are very few records of those who had the same ideas sometimes at the same time or sometimes earlier and lost. Case in point. Galileo is thought of as the first of the greats to develop our current understanding of the solar system. Very few know that Copernicus had those very same ideas many years before. In his case he capitulated to the forces arrayed against him and revised his theory giving us the Copernican model of the solar system.


Per the linked pdf, I do not think that the DOE would be spending hundreds of millions of dollars on the ACME project unless they think that this approach has merit.

Best,
ASLR

http://climatemodeling.science.energy.gov/sites/default/files/publications/acme-project-strategy-plan.pdf

Extract: "ACME will achieve this goal through four intersecting project elements:
1. a series of prediction and simulation experiments addressing scientific questions and mission needs;
2. a well-documented and tested, continuously advancing, evolving, and improving system of model codes that comprise the ACME Earth system model;
3. the ability to use effectively leading (and “bleeding”) edge computational facilities soon after their deployment at DOE national laboratories; and
4. an infrastructure to support code development, hypothesis testing, simulation execution, and analysis of results.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #11 on: March 14, 2016, 11:40:02 PM »
The linked (open access) reference discusses efforts to calibrate CESM to better account for SMB for Antarctica.  CESM was the basis for the ACME model.

Jan T. M. Lenaerts, Miren Vizcaino, Jeremy Fyke, Leo van Kampenhout & Michiel R. van den Broeke (2016), "Present‐Day and Future Antarctic Ice Sheet Climate and Surface Mass Balance in the Community Earth System Model", Climate Dynamics; DOI:10.1007/s00382-015-2907-4

http://link.springer.com/article/10.1007%2Fs00382-015-2907-4

Abstract: "We present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ∼1 degrees in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131 Gt year−1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenario RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gt year−1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #12 on: May 16, 2016, 05:34:21 PM »
Information from the linked reference can be used to improve the calibration of climate models:

Andrea Storto, Chunxue Yang & Simona Masina (online: 14 May 2016) "Sensitivity of global ocean heat content from reanalyses to the Atmospheric reanalysis forcing: A comparative study", Geophysical Research Letters, DOI: 10.1002/2016GL068605


http://onlinelibrary.wiley.com/doi/10.1002/2016GL068605/abstract

Abstract: "The global ocean heat content evolution is a key component of the Earth's energy budget and can be consistently determined by ocean reanalyses that assimilate hydrographic profiles. This work investigates the impact of the atmospheric reanalysis forcing through a multi-forcing ensemble ocean reanalysis, where the ensemble members are forced by five state-of-the-art atmospheric reanalyses during the meteorological satellite era (1979-2013). Data assimilation leads the ensemble to converge towards robust estimates of ocean warming rates and significantly reduces the spread (1.48 +/- 0.18 W/m2, per unit area of the World Ocean); hence the impact of the atmospheric forcing appears only marginal for the global heat content estimates in both upper and deeper oceans. A sensitivity assessment performed through realistic perturbation of the main sources of uncertainty in ocean reanalyses highlights that bias-correction and pre-processing of in-situ observations represent the most crucial component of the reanalysis, whose perturbation accounts for up to 60% of the ocean heat content anomaly variability in the pre-Argo period. Although these results may depend on the single reanalysis system used, they reveal useful information for the ocean observation community and for the optimal generation of perturbations in ocean ensemble systems."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #13 on: July 12, 2016, 05:19:37 PM »
The linked reference demonstrates "… that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period." See the attached image that illustrates conceptually how this occurs.  Thus biased parties (say researchers with ties to the Tea Party) can (and do) put their thumb on the scales while being fully vetted by the IPCC; while careful researcher examine a range of reference periods for their climate change model projections, to try to control for this matter:

Ed Hawkins and Rowan Sutton (2016), "Connecting Climate Model Projections of Global Temperature Change with the Real World", BAMS, DOI: http://dx.doi.org/10.1175/BAMS-D-14-00154.1

http://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-14-00154.1

Abstract: "Current state-of-the-art global climate models produce different values for Earth’s mean temperature. When comparing simulations with each other and with observations, it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate and about the magnitude of expected future changes in climate. For example, observed global temperatures over the past decade are toward the lower end of the range of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations irrespective of what reference period is used, but exactly where they lie in the model distribution varies with the choice of reference period. Additionally, we demonstrate that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period. In this article, we discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections. We highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) choice to use a 1986–2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #14 on: July 15, 2016, 05:50:29 PM »
Climate change is both superimposed on, and influences, atmospheric fluctuations, and the linked article discusses work on characterizing such fluctuations over wide-scale ranges.  Such work is important to consider when calibrating climate change models:

Lovejoy, S., M. Crucifix, and A. De Vernal (2016), Characterizing climate fluctuations over wide-scale ranges, Eos, 97, doi:10.1029/2016EO055791. Published on 14 July 2016

https://eos.org/meeting-reports/characterizing-climate-fluctuations-over-wide-scale-ranges

Extract: "The atmosphere is highly variable—more than 20 orders of magnitude in time and 10 in space: billions of years to milliseconds and tens of thousands of kilometers to millimeters.
In spite of this, almost all approaches to atmospheric variability focus on processes acting over narrow ranges of scale, such as El Niño or the diurnal, annual, and Milankovitch cycles. Empirical analyses show that most of the variability is in the continuous “background” (Figure 1), and over several wide ranges this can be well approximated by (scaling) power laws. The evaluation of the background shows that there is a need to find effective ways to characterize climate fluctuations, to understand their causes, and to focus on these aspects when analyzing both climate data and 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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #15 on: July 25, 2016, 09:51:23 PM »
The linked reference discusses planned PMIP4-CMIP6 simulations that will serve to help calibrate both paleoclimate models and CMIP6 model projections:

Kageyama, M., Braconnot, P., Harrison, S. P., Haywood, A. M., Jungclaus, J., Otto-Bliesner, B. L., Peterschmitt, J.-Y., Abe-Ouchi, A., Albani, S., Bartlein, P. J., Brierley, C., Crucifix, M., Dolan, A., Fernandez-Donado, L., Fischer, H., Hopcroft, P. O., Ivanovic, R. F., Lambert, F., Lunt, D. J., Mahowald, N. M., Peltier, W. R., Phipps, S. J., Roche, D. M., Schmidt, G. A., Tarasov, L., Valdes, P. J., Zhang, Q., and Zhou, T. (2016), "PMIP4-CMIP6: the contribution of the Paleoclimate Modelling Intercomparison Project to CMIP6", Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-106

http://www.geosci-model-dev-discuss.net/gmd-2016-106/
&
http://www.geosci-model-dev-discuss.net/gmd-2016-106/gmd-2016-106.pdf


Abstract: "The goal of the Palaeoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to changes in different climate forcings and to feedbacks. Through comparison with observations of the environmental impacts of these climate changes, or with climate reconstructions based on physical, chemical or biological records, PMIP also addresses the issue of how well state-of-the-art models simulate climate changes. Palaeoclimate states are radically different from those of the recent past documented by the instrumental record and thus provide an out-of-sample test of the models used for future climate projections and a way to assess whether they have the correct sensitivity to forcings and feedbacks. Five distinctly different periods have been selected as focus for the core palaeoclimate experiments that are designed to contribute to the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This manuscript describes the motivation for the choice of these periods and the design of the numerical experiments, with a focus upon their novel features compared to the experiments performed in previous phases of PMIP and CMIP as well as the benefits of common analyses of the models across multiple climate states. It also describes the information needed to document each experiment and the model outputs required for analysis and benchmarking."

Extract: "PMIP4-CMIP6 simulations provide a framework to compare current and future anthropogenic climate change with past natural variations of the Earth’s climate. PMIP4-CMIP6 is a unique opportunity to simulate past climates with exactly the same models as used for simulations of the future. This approach is only valid if the model versions and implementation of boundary conditions are consistent for all periods, and if these boundary conditions are seamless for overlapping periods."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #16 on: July 26, 2016, 05:53:20 PM »
The linked reference indicates that projections from two ESMs managed to simulate the observed abyssal carbonate compensation depth overshoot following the PETM.  This helps serves to calibrate such advanced ESMs:

Donald E. Penman, Sandra Kirtland Turner, Philip F. Sexton, Richard D. Norris, Alexander J. Dickson, Slah Boulila, Andy Ridgwell, Richard E. Zeebe, James C. Zachos, Adele Cameron, Thomas Westerhold & Ursula Röhl (2016), "An abyssal carbonate compensation depth overshoot in the aftermath of the Palaeocene–Eocene Thermal Maximum", Nature Geoscience, doi:10.1038/ngeo2757

http://www.nature.com/ngeo/journal/vaop/ncurrent/full/ngeo2757.html

Abstract: "During the Palaeocene–Eocene Thermal Maximum (PETM) about 56 million years ago, thousands of petagrams of carbon were released into the atmosphere and ocean in just a few thousand years, followed by gradual sequestration over approximately 200,000 years. If silicate weathering is one of the key negative feedbacks that removed this carbon, a period of seawater calcium carbonate saturation greater than pre-event levels would be expected during the event's recovery phase. In marine sediments, this should be recorded as a temporary deepening of the depth below which no calcite is preserved — the calcite compensation depth (CCD). Previous and new sedimentary records from sites that were above the pre-PETM CCD show enhanced carbonate accumulation following the PETM. A new record from an abyssal site in the North Atlantic that lay below the pre-PETM CCD shows a period of carbonate preservation beginning about 70,000 years after the onset of the PETM, providing the first direct evidence for an over-deepening of the CCD. This record confirms an overshoot in ocean carbonate saturation during the PETM recovery. Simulations with two earth system models support scenarios for the PETM that involve a large initial carbon release followed by prolonged low-level emissions, consistent with the timing of CCD deepening in our record. Our findings indicate that sequestration of these carbon emissions was most likely the result of both globally enhanced calcite burial above the CCD and, at least in the North Atlantic, an over-deepening of the CCD."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #17 on: July 26, 2016, 06:39:20 PM »
The linked article adds additional information & a website link about the PMIP4/CMIP6 calibration effort:

Masa Kageyama, Pascale Braconnot, Sandy Harrison, Alan Haywood, Johann Jungclaus, Bette Otto-Bliesner, and Ayako Abe-Ouchi (2016), "From Past to future: the Paleoclimate Modelling Intercomparison Project’s contribution to CMIP6", EGU General Assembly 2016, held 17-22 April, 2016 in Vienna Austria, p.13139

http://adsabs.harvard.edu/abs/2016EGUGA..1813139K

Abstract: "Since the 1990s, PMIP has developed with the following objectives: 1) to evaluate the ability of climate models used for climate prediction in simulating well-documented past climates outside the range of present and recent climate variability; 2) to understand the mechanisms of these climate changes, in particular the role of the different climate feedbacks. To achieve these goals, PMIP has actively fostered paleo-data syntheses, multi-model analyses, including analyses of relationships between model results from past and future simulations, and model-data comparisons. For CMIP6, PMIP will focus on five past periods: - the Last Millennium (850 CE - present), to analyse natural climate variability on multidecadal or longer time-scales - the mid-Holocene, 6000 years ago, to compare model runs with paleodata for a period of warmer climate in the Northern Hemisphere, with an enhanced hydrological cycle - the Last Glacial Maximum, 21000 years ago, to evaluate the ability of climate models to represent a cold climate extreme and examine whether paleoinformation about this period can help and constrain climate sensitivity - the Last InterGlacial (~127,000 year ago), which provides a benchmark for a period of high sea-level stand - the mid-Pliocene warm period (~3.2 million years ago), which allows for the evaluation of the model's long-term response to a CO2 level analogous to the modern one. This poster will present the rationale of these "PMIP4-CMIP6" experiments. Participants are invited to come and discuss about the experimental set-up and the model output to be distributed via CMIP6."

For more information and discussion of the PMIP4-CMIP6 experimental design, please visit:

https://wiki.lsce.ipsl.fr/pmip3/doku.php/pmip3:cmip6:design:index

“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #18 on: July 29, 2016, 01:24:58 AM »
The linked website discusses the DeepMIP effort to calibrate Earth Systems Models to climate sensitivity in 'Deep-Time', tens of millions of years ago (the abstract below indicates that the PMIP program by itself in not sufficient for adequate model calibration):

http://gtr.rcuk.ac.uk/projects?ref=NE/N006828/1

The Deep-Time Model Intercomparison Project (DeepMIP):

Abstract: "Predictions of future climate, essential for safeguarding society and ecosystems, are underpinned by numerical models of the Earth system. These models are routinely tested against, and in many cases tuned towards, observations of the modern Earth system. However, the model predictions of the climate of the end of this century lie largely outside of this evaluation period, due to the projected future CO2 forcing being significantly greater than that seen in the observational record. Indeed, recent work reconstructing past CO2 has shown that the closest analogues to the 22nd century, in terms of CO2 concentration, are tens of millions of years ago, in 'Deep-Time'.

The Palaeoclimate Modelling Intercomparison Project (PMIP) provides a framework (but no funding!) by which the palaeoclimate modelling community assesses state-of-the-art climate models relative to past climate data. Traditionally, PMIP has focussed on the relatively recent mid-Holocene (6,000 years ago) and Last Glacial Maximum (21,000 years ago), but these time periods have even lower CO2 than modern (~280 and ~180 ppmv respectively, c.f. ~400 ppmv for the modern). Recently, PMIP has expanded into other time periods, most notably the mid-Pliocene (3 million years ago), but even then, CO2 was most likely less than modern values (~380 ppmv). The modelling community would clearly benefit from an intercomparison of 'Deep-Time' climates, when CO2 levels were close to those predicted for the end of this century.

We will organise and provide funding for 2 workshops, with the aim of producing papers describing the experimental design and outputs from a new climate Model Intercomparison Project - "DeepMIP", focussing on past climates in which atmospheric CO2 concentrations were similar to those projected for the end of this century. The papers will evaluate the models relative to past geological data, and aim to understand the reasons for the model-model differences and model-data (dis)agreements, providing information of relevance to the IPCC.

A previous NERC grant, NE/K014757/1, is currently aiming to assess climate sensitivity (the response of surface air temperature to a doubling of atmospheric CO2), through geological time. That project is focussing on many time periods, but with only one model. This IOF will complement that project, and bring added-value, by focussing on one particular time period, but with many models. As such we will address the crucial issue of model-dependence."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #19 on: August 01, 2016, 11:09:57 PM »
Hopefully, DeepMIP and PMIP4 can help to reduce the uncertainties associated with CMIP6 climate model tuning (especially w.r.t. ECS), as discussed in the linked reference:

Hourdin, F., T. Mauritsen, A. Gettelman, J. Golaz, V. Balaji, Q. Duan, D. Folini, D.
Ji, D. Klocke, Y. Qian, F. Rauser, C. Rio, L. Tomassini, M. Watanabe, and D.
Williamson (2016), "The art and science of climate model tuning", Bull. Amer.
Meteor. Soc., doi:10.1175/BAMS-D-15-00135.1

http://journals.ametsoc.org/doi/pdf/10.1175/BAMS-D-15-00135.1

Abstract: "The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate sub-models. Most sub-models depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers.  Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so called ‘objective‘ methods in climate model tuning. We discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent."

See also:
https://andthentheresphysics.wordpress.com/

Extract: "The goal of tuning is then to minimise some difference between the model output and selected observations and theories. Although there are a number of different observations/theories that could be used for tuning, something I had not realised is that there is

a dominant shared target for coupled climate models: the climate system should reach a mean equilibrium temperature close to observations when energy received from the sun is close to its real value (340 W/m2).

The bit of the paper that I found most interesting was the section on Tuning to 20th century warming. The suggestion is that even though ECS is an emergent property of models and the match to the 20th century is typically used to evaluate models, there is an indication that some tuning to fit the 20th century is probable. This is largely because it’s been noted that high sensitivity models tend to have smaller total forcing, while low sensitivity models have larger forcing. Hence, there is less spread in historical warming than might be expected.



Given that there are some indications of tuning to match the historical record, what was suggested is that one could construct outlier low- and high-sensitivity models and then run these in pre-historic climates to see if one can rule out some of the more extreme values. This seems like a particularly interesting possibility."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #20 on: August 03, 2016, 07:02:14 PM »
The linked reference ESLD (w.r.t. the ECS for the Pliocene) while admitting that forth-coming work could well prove them wrong (what a nice business science is, where you can publish any incorrect values so long as you publically admit that you might be wrong):

Hargreaves, J. C. and Annan, J. D.: Could the Pliocene constrain the equilibrium climate sensitivity?, Clim. Past, 12, 1591-1599, doi:10.5194/cp-12-1591-2016, 2016.

http://www.clim-past.net/12/1591/2016/

Abstract. The mid-Pliocene Warm Period (mPWP) is the most recent interval in which atmospheric carbon dioxide was substantially higher than in modern pre-industrial times. It is, therefore, a potentially valuable target for testing the ability of climate models to simulate climates warmer than the pre-industrial state. The recent Pliocene Model Intercomparison Project (PlioMIP) presented boundary conditions for the mPWP and a protocol for climate model experiments. Here we analyse results from the PlioMIP and, for the first time, discuss the potential for this interval to usefully constrain the equilibrium climate sensitivity. We observe a correlation in the ensemble between their tropical temperature anomalies at the mPWP and their equilibrium sensitivities. If the real world is assumed to also obey this relationship, then the reconstructed tropical temperature anomaly at the mPWP can in principle generate a constraint on the true sensitivity. Directly applying this methodology using available data yields a range for the equilibrium sensitivity of 1.9–3.7 °C, but there are considerable additional uncertainties surrounding the analysis which are not included in this estimate. We consider the extent to which these uncertainties may be better quantified and perhaps lessened in the next few years."

Extract: "Our main result is an estimate for S of 1.9–3.7 oC, but major uncertainties in the experimental design and analysis cast substantial doubts over the robustness of this estimate.  However, with the evolution of PlioMIP, now moving into phase 2 (Haywood et al., 2016), it seems likely that significant progress can be made on this question in the near future."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #21 on: August 04, 2016, 05:27:26 PM »
The linked (open access) reference serves as a case study of how paleo information can be used to interactively improve the calibration of climate change models, in this case the Community Earth System Models (COSMOS):

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

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

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

In order to evaluate the performance of our LIG simulations, we additionally compare the simulated TS anomalies with marine and terrestrial proxy-based LIG temperature anomalies derived from three different proxy data compilations. Our model results are in good agreement with proxy records with respect to the warming pattern but underestimate the magnitude of temperature change when compared to reconstructions, suggesting a potential misinterpretation of the proxy records or deficits in our model. However, we are able to partly reduce the mismatch between model and data by additionally taking into account the potential seasonal bias of the proxy record and/or the uncertainties in the dating of the proxy records for the LIG thermal maximum. The seasonal bias and the uncertainty of the timing are estimated from new transient model simulations covering the whole LIG. The model–data comparison improves for proxies that represent annual mean temperatures when the GIS is reduced and when we take the local thermal maximum during the LIG (130–120 kyr BP) into account. For proxy data that represent summer temperatures, changes in the GIS are of minor importance for sea surface temperatures. However, the annual mean and summer temperature change over Greenland in the reduced GIS simulations seems to be overestimated as compared to the local ice core data, which could be related to the interpretation of the recorder system and/or the assumptions of GIS reduction. Thus, the question regarding the real size of the GIS during the LIG has yet to be answered.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #22 on: August 08, 2016, 11:19:10 AM »
Some of my recent posts have noted that the CMIP6 models are currently being calibrated to the paleo-record from the PMIP4 effort and that some climate models will even be calibrated against the paleo-findings of the DeepMIP effort; in order to improve the accuracies of the CMIP6 projections through 2100 & beyond.

With this in mind, I first note that essentially none of the CMIP6 models include hydrofracturing and cliff failures; without which Polland, DeConto & Alley (2015) could not even match ice mass loss observed from Antarctica during the Eemian; and that when they included these two mechanisms to modern conditions they found rates of sea level rise as indicated in the first attached plot.

Furthermore, when Hansen et al (2016) applied rates of ice sheet mass loss comparable to those projected by Pollard, DeConto & Alley (2015); they found abrupt & short-term increases in planetary energy imbalance as indicated in the second attached image.

Also, Chen et al (2013) showed that the rotational axis of the Earth is already shifting due to changes in ice sheet mass loss (see the third attached image); and that with increasing ice mass loss as projected by DeConto & Pollard (2016) at the April EGU for this coming century (see the third attached image); we can expect much larger changes in our axis of rotation by the end of this century (assuming that GMST reaches 2.7C before then).

Next, I note that due to Arctic Amplification we will likely see rapid formation of thermokarst lakes in permafrost regions that will cause spikes (this century) in associated methane emissions as indicated in the fourth attached image.  Also, in this regards I note that Coletti, DeConto, Brigham-Grette & Melles (2015) have shown that during super-interglacial periods collapses of the WAIS are associated with an acceleration of Arctic Amplification.


Coletti, A. J., DeConto, R. M., Brigham-Grette, J., and Melles, M.: A GCM comparison of Pleistocene super-interglacial periods in relation to Lake El'gygytgyn, NE Arctic Russia, Clim. Past, 11, 979-989, doi:10.5194/cp-11-979-2015, 2015.

http://www.clim-past.net/11/979/2015/cp-11-979-2015.pdf
http://www.clim-past.net/11/979/2015/cp-11-979-2015.html

So with these selected considerations in-mind, I hope that the CMIP6 (and ACME) calibration efforts results in the associated models adopting: (a) hydrofracturing & cliff failures of ice sheets (as DeConto & Pollard have made their algorithms available to other researchers); (b) the use of hosing that Hansen et al (2016) used to model both ice-climate interaction & the associated planetary energy imbalances; (c) changes in coastal topology due to abrupt sea level rise associated with the WAIS collapse, which can change ocean circulation patterns (particularly from the Pacific Ocean into both the Arctic Sea and into the Southern Ocean); (d) changes in planetary rotation and associated changes in solar radiative forcing; and (e) changes in ESS (including methane emissions from newly formed thermokarst lakes) associated with rapid changes in both anthropogenic radiative forcing and those due to Hansen et al (2016)'s ice-climate feedback.
 
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #23 on: August 16, 2016, 05:40:01 PM »
One of the major reasons that AR5 model projections err so far on the side of least drama is that they count model results with high errors the same as more skillful models.  The linked reference discusses how more models can reduce errors  associated with global land surface models:

Jianduo Li, Ying-Ping Wang, Qingyun Duan, Xingjie Lu, Bernard Pak, Andy Wiltshire, Eddy Robertson & Tilo Ziehn (16 August 2016), "Quantification and attribution of errors in the simulated annual gross primary production and latent heat fluxes by two global land surface models", DOI: 10.1002/2015MS000583


http://onlinelibrary.wiley.com/doi/10.1002/2015MS000583/full

Abstract: "Differences in the predicted carbon and water fluxes by different global land models have been quite large and have not decreased over the last two decades. Quantification and attribution of the uncertainties of global land surface models are important for improving the performance of global land surface models, and are the foci of this study. Here we quantified the model errors by comparing the simulated monthly global gross primary productivity (GPP) and latent heat flux (LE) by two global land surface models with the model-data products of global GPP and LE from 1982 to 2005. By analyzing model parameter sensitivities within their ranges, we identified about 2–11 most sensitive model parameters that have strong influences on the simulated GPP or LE by two global land models, and found that the sensitivities of the same parameters are different among the plant functional types (PFT). Using parameter ensemble simulations, we found that 15%–60% of the model errors were reduced by tuning only a few (<4) most sensitive parameters for most PFTs, and that the reduction in model errors varied spatially within a PFT or among different PFTs. Our study shows that future model improvement should optimize key model parameters, particularly those parameters relating to leaf area index, maximum carboxylation rate, and stomatal conductance."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #24 on: August 17, 2016, 10:04:42 PM »
The linked reference discusses progress made in characterizing the paleobathymetry of the Southern Ocean, that is needed for more accurate paleo-climate modeling:

Hochmuth, K. and Gohl, K. (2016): Paleobathymetry of the Southern Ocean and its role in paleoclimate and paleo-ice sheet variations – A call for a sequence of community paleobathymetric grids , SCAR Open Science Conference, Kuala Lumpur, Malaysia, 10 August 2016 - 20 August 2016 . Cite this page as:
hdl:10013/epic.47512

http://epic.awi.de/40463/

Abstract: "Paleo-ocean circulation models of the Southern Ocean suffer from missing boundary conditions which describe accurately the geometries of the seafloor surfaces at their geological epoch and their dynamics over long time-scales. The accurate parameterisation of these models controls the meaning and implications of regional and global paleo-climate models. For instance, the onset and consequences of the deep-water opening of the Southern Ocean gateways – Drake Passage and the Tasmanian Gateway – is only indirectly and vaguely determined by proxy analyses of microfossils. The development and implications for deflections of major deep-sea current systems through structural obstacles such as oceanic plateaus and ridges, but also the extent and morphological shape of the continental shelves, is not described due to lacking reconstructions of their bathymetric development. Although plate-kinematic reconstructions of the Southern Ocean have reached a state at which the plate circuit can be almost closed with geodynamic constraints of improving certainties, a major obstacle for calculating Southern Ocean paleobathymetric grids has been the missing or insufficiently assessed components of sedimentary deposition/erosion and mantle-driven dynamic topography. Existing paleobathymetric models consider only the top of oceanic basement based on paleo-age models from magnetic sea-floor spreading anomalies and plate-kinematic reconstructions. Others simplify the sedimentary cover using outdated isopach databases. A re-assessment of old seismic data as well as recently collected new seismic lines reveal that the sedimentary cover has been greatly underestimated in almost all conjugate continental margins and in some of the deep Southern Ocean basins. Incorporating sedimentary processes in paleobathymetric reconstruction grids is particularly important in reconstructing the opening of oceanic gateways where the question of shallow to deep water exchange determines the accuracy of paleo-ocean circulation and paleo-climate models. But also the dynamics of ocean currents in proximity of the continental margins is controlled by the development of the regional morphology of the conjugate continental shelves, slopes and rises. The ultimate aim of such grids is to generate Cenozoic climate reconstructions using a variety of Earth system models designed to evaluate the effect of ocean gateways and basins on paleo-circulation patterns, the global carbon cycle and the nature of Antarctic ice sheet development. These experiments will include sensitivity runs incorporating the new paleobathymetric reconstructions. The results from these experiments are compared with other model simulations, which include different forcing factors such as atmospheric greenhouse gasses and mountain uplift to determine the relative importance of paleo-geography on the evolution of global climates over long geological timescales."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #25 on: August 21, 2016, 03:49:25 AM »
The linked reference offers additional information for the calibration of climate models using paleo-information:

Brown, N. and Galbraith, E. D.: Hosed vs. unhosed: interruptions of the Atlantic Meridional Overturning Circulation in a global coupled model, with and without freshwater forcing, Clim. Past, 12, 1663-1679, doi:10.5194/cp-12-1663-2016, 2016.

http://www.clim-past.net/12/1663/2016/

Abstract. It is well known that glacial periods were punctuated by abrupt climate changes, with large impacts on air temperature, precipitation, and ocean circulation across the globe. However, the long-held idea that freshwater forcing, caused by massive iceberg discharges, was the driving force behind these changes has been questioned in recent years. This throws into doubt the abundant literature on modelling abrupt climate change through “hosing” experiments, whereby the Atlantic Meridional Overturning Circulation (AMOC) is interrupted by an injection of freshwater to the North Atlantic: if some, or all, abrupt climate change was not driven by freshwater input, could its character have been very different than the typical hosed experiments? Here, we describe spontaneous, unhosed oscillations in AMOC strength that occur in a global coupled ocean–atmosphere model when integrated under a particular background climate state. We compare these unhosed oscillations to hosed oscillations under a range of background climate states in order to examine how the global imprint of AMOC variations depends on whether or not they result from external freshwater input. Our comparison includes surface air temperature, precipitation, dissolved oxygen concentrations in the intermediate-depth ocean, and marine export production. The results show that the background climate state has a significant impact on the character of the freshwater-forced AMOC interruptions in this model, with particularly marked variations in tropical precipitation and in the North Pacific circulation. Despite these differences, the first-order patterns of response to AMOC interruptions are quite consistent among all simulations, implying that the ocean–sea ice–atmosphere dynamics associated with an AMOC weakening dominate the global response, regardless of whether or not freshwater input is the cause. Nonetheless, freshwater addition leads to a more complete shutdown of the AMOC than occurs in the unhosed oscillations, with amplified global impacts, evocative of Heinrich stadials. In addition, freshwater inputs can directly impact the strength of other polar haloclines, particularly that of the Southern Ocean, to which freshwater can be transported relatively quickly after injection in the North Atlantic.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #26 on: August 29, 2016, 09:54:29 AM »
U.S. Department of Energy recently sponsored a workshop on uncertainty quantification to help in developing a next generation climate and Earth-system model called the Accelerated Climate Modeling for Energy, or ACME; as discussed in the linked reference.  Key findings included: (a) an emphasis on using more Bayesian frameworks; (b) model calibration using short-term weather related events; and (c) an appreciation that due to the cost of making long-term runs the current phase of development for ACME while not be able to use paleo-records to calibrate for the ice-climate feedback risks identified by Hansen et al (2016):

Yun Qian et al. Uncertainty Quantification in Climate Modeling and Projection, Bulletin of the American Meteorological Society (2016). DOI: 10.1175/BAMS-D-15-00297.1


http://journals.ametsoc.org/doi/10.1175/BAMS-D-15-00297.1


Extract: "Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in vulnerability, impact, and adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty.

The workshop especially emphasized the use of a Bayesian framework for synthesizing uncertainties affecting climate projections. Computation for the Bayesian approach can make use of a simple relationship in conditional probability to divide a large and seemingly intractable problem into a sequence of smaller calculations from which one can construct the desired estimates. The workshop focused on uncertainties in representing climate system physics in current models. Our best knowledge of climate modeling uncertainty can be currently derived from the CMIP framework, which includes results from a standard set of experiments by ∼30–40 state-of-the-art climate system models constructed by different teams of experts and centers throughout the world. This “ensemble of opportunity” is the best available source of information on the range of physically plausible climate evolutions over the next century. Bayesian inference provides an unproven, but potentially powerful, alternative approach to quantify climate model uncertainties from individual models. While the approach is most easily adapted to consider uncertain model parameter settings (i.e., uncertainty in model tuning), it can also be used to explore alternate parameterization schemes.
Applying Bayesian inference to climate projections is not trivial because of the challenges imposed by the computational expense of running large ensembles of climate simulations and the nonlinear interactions of climate system processes. For example, it has been found that changes of model parameters aimed at improving the simulation of Greenland’s surface mass balance can have major consequences on how the model simulates tropical water vapor. To meet these challenges, the Bayesian statistical community has developed strategies for reducing the size of the problem by developing 1) global sensitivity analyses that can weed out unimportant parameters; 2) surrogate models, such as Gaussian process emulation, that can predict the response of a climate model to arbitrary changes in model parameter settings; and 3) adaptive sampling strategies that can significantly reduce the number of model experiments needed in the construction of response functions.

The most recent national climate projection assessment in the United Kingdom [United Kingdom Climate Projections 2009 (UKCP09)] provides an example of such an approach. UKCP09 made use of emulation techniques and multiple simulations with a single climate model and applied a Bayesian methodology to quantify a (conditional) probability for future climate changes at United Kingdom scales. Based on multiple climate model simulations, the emulators are used to estimate the wider climate response space of all possible parameter combinations. The Bayesian framework can then be used to evaluate the relative likelihood of each of these possible simulated climates relative to the observed world. There are a number of other aspects to this approach (such as the use of available multimodel ensembles to include an estimate of the intermodel structural uncertainties), but at its core the application uses a standard set of UQ tools that were presented at the workshop. Similar probabilistic frameworks are being built by other national modeling centers. The statistical framework on which these estimates are built still requires various assumptions that may be difficult to fully justify. Nevertheless, they do provide a feasible way to combine different sources of information relevant to assessments of climate change impacts.

The other result from this project that was relevant to the workshop participants is that the currently generated projection ensembles (e.g., CMIP) may underrepresent the range of possible impacts in particular regions where there has not been a concerted effort to explore parameters or forcings important to that region.

Currently, concerns about model deficiencies in projections are assessed by the level of agreement within a multimodel ensemble and metrics that summarize how a certain response is obtained. There do not seem to be clear-cut answers on how to account for the effects of missing physics.
One of the challenges for calibrating climate models with observational data is the interdependency that exists in the selection of parameters affecting different component models, especially with components of the climate system that take a long time to adjust to a change in forcing or parameters such as the ocean and ice sheets. The time scales of adjustment in the ocean make any practical testing of a range of alternate model configurations untenable.

One of the key limitations toward the application of full UQ approaches to current climate models is computational. The challenge is how to run sufficiently large numbers of simulations to estimate the uncertainties without degrading either the resolution or complexity beyond a level where the simulations would not be representative of the state of the art. One way forward could be to make use of information on shorter, weather time scales. A number of systematic model biases arise from the fast physics that can emerge on short 2–3-day time scales (such as vertical stability and cloud responses). An increasing number of modeling groups now make use of a “seamless” approach of using model evaluation on weather, seasonal, and climate time scales to inform model development. The workshop participants discussed how information from short time-scale simulations could be used in UQ approaches."

See also:

http://phys.org/news/2016-08-climate-methods-corral-uncertainty.html

Extract: ""Uncertainty quantification is a focus for the U.S. Department of Energy," said workshop lead and PNNL atmospheric scientist Dr. Yun Qian. "DOE has gathered eight national laboratories and six partner institutions to collaborate in developing a next generation climate and Earth-system model called the Accelerated Climate Modeling for Energy, or ACME. This workshop will help us address critical gaps in scientific computing and develop the resources needed to fill them."

“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #27 on: September 03, 2016, 01:22:03 AM »
The linked reference discuss some of the changes of calibrating the climate sensitivity of climate models:

Loeb, N.G., Su, W. & Kato, S. (2016), "Understanding Climate Feedbacks and Sensitivity Using Observations of Earth’s Energy Budget", Curr Clim Change Rep; doi:10.1007/s40641-016-0047-5

http://rd.springer.com/article/10.1007%2Fs40641-016-0047-5

Abstract: "While climate models and observations generally agree that climate feedbacks collectively amplify the surface temperature response to radiative forcing, the strength of the feedback estimates varies greatly, resulting in appreciable uncertainty in equilibrium climate sensitivity. Because climate feedbacks respond differently to different spatial variations in temperature, short-term observational records have thus far only provided a weak constraint for climate feedbacks operating under global warming. Further complicating matters is the likelihood of considerable time variation in the effective global climate feedback parameter under transient warming. There is a need to continue to revisit the underlying assumptions used in the traditional forcing-feedback framework, with an emphasis on how climate models and observations can best be utilized to reduce the uncertainties. Model simulations can also guide observational requirements and provide insight on how the observational record can most effectively be analyzed in order to make progress in this critical area of climate research."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #28 on: September 04, 2016, 04:08:05 PM »
The linked reference provides new/refined data about clouds, that will allow modelers to better calibrate their models.  Also, the reported finding that almost 50% of the observed clouds were high clouds (which have positive feedback) will likely provide support for a ECS towards the high end of AR5's estimate range:

W. Paul Menzel, Richard A. Frey, Eva. E. Borbas, Bryan A. Baum, Geoff Cureton, and Nick Bearson (1 September 2016), "Reprocessing of HIRS Satellite Measurements from 1980-2015: Development Towards a Consistent Decadal Cloud Record", Journal of Applied Meteorology and Climatology, DOI: http://dx.doi.org/10.1175/JAMC-D-16-0129.1

http://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-16-0129.1

Abstract: "This paper presents the cloud parameter data records derived from HIRS (High-resolution Infrared Radiation Sounder) measurements from 1980 through 2015 on the NOAA and MetOp polar orbiting platforms. Over this time period, the HIRS sensor has been flown on sixteen satellites from TIROS-N through NOAA-19 and MetOp-A and –B, forming a 35-year cloud data record. Inter-calibration of the IASI (Infrared Advanced Sounding Interferometer) and HIRS on MetOp-A has created confidence in the on-board calibration of this HIRS as a reference for others. A recent effort to improve the understanding of IR channel response functions of earlier HIRS sensor radiance measurements using simultaneous nadir overpasses has produced a more consistent sensor-to-sensor calibration record. Incorporation of a cloud mask from the higher spatial resolution AVHRR (Advanced Very High Resolution Radiometer) improves the sub-pixel cloud detection within the HIRS measurements. Cloud top pressure (CTP) and effective emissivity (εf, cloud emissivity multiplied by cloud fraction) are derived using the 15-μm spectral bands in the CO2 absorption band and implementing the CO2 slicing technique; the approach is robust for high semi-transparent clouds but weak for low clouds with little thermal contrast from clear sky radiances. This paper documents the effort to incorporate the recalibration of the HIRS sensors, notes the improvements to the cloud algorithm, and presents the HIRS cloud data record from 1980 to 2015. The reprocessed HIRS cloud data record reports clouds in 76.5% of the observations and 36.1% find high clouds."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #29 on: September 12, 2016, 09:38:29 PM »
The linked reference demonstrates a correlation between cloud feedbacks and the patterns of sea surface heat fluxes; which should allow for better calibration of future climate models:

Rose, B.E.J. & Rayborn, L. (2016), "The Effects of Ocean Heat Uptake on Transient Climate Sensitivity", Curr Clim Change Rep, doi:10.1007/s40641-016-0048-4


http://rd.springer.com/article/10.1007%2Fs40641-016-0048-4?wt_mc=Affiliate.CommissionJunction.3.EPR1089.DeepLink

Abstract: "Transient climate sensitivity tends to increase on multiple timescales in climate models subject to an abrupt CO2 increase. The interdependence of radiative and ocean heat uptake processes governing this increase are reviewed. Heat uptake tends to be spatially localized to the subpolar oceans, and this pattern emerges rapidly from an initially uniform distribution. Global climatic impact of heat uptake is studied through the lens of the efficacy concept and a linear systems perspective in which responses to individual climate forcing agents are additive. Heat uptake can be treated as a slowly varying forcing on the atmosphere and surface, whose efficacy is strongly determined by its geographical pattern. An illustrative linear model driven by simple prescribed uptake patterns demonstrates the emergence of increasing climate sensitivity as a consequence of the slow decay of high-efficacy subpolar heat uptake. Evidence is reviewed for the key role of shortwave cloud feedbacks in setting the high efficacy of ocean heat uptake and thus in increasing climate sensitivity. A causal physical mechanism is proposed, linking subpolar heat uptake to a global-scale increase in lower-tropospheric stability. It is shown that the rate of increase in estimated inversion strength systematically slows as heat uptake decays. Variations in heat uptake should therefore manifest themselves as differences in low cloud feedbacks."

Extract: "An important implication is that temporal variations in both magnitude and spatial pattern of OHU (and thus also in its global efficacy) may be expressed radiatively through SW cloud responses. The same may be said about inter-model differences in OHU. This is a tantalizing proposition, as cloud feedbacks continue to be the largest source of spread in estimates of climate sensitivity. If part of that spread is driven in systematic ways by patterns of sea surface heat fluxes, it may be more reducible and falsifiable than typically acknowledged.
In light of this, we suggest as a priority for future research understanding the physics linking OHU to tropospheric stratification, and connecting this to ongoing studies of the environmental constraints on cloud feedbacks. Another priority should be understanding the spatial structure of OHU, how it evolves on different timescales, and how realistically these processes are modeled in current AOGCMs. Finally, longer integrations of AOGCMs would enable a better understanding of the equilibration process, including the role of changing ocean circulation."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #30 on: September 14, 2016, 03:22:08 AM »
As we many be headed towards Eocene like climate conditions, and the linked reference on the experimental design of the DeepMIP may help calibrate ESMs to project for such conditions:

Lunt, D. J., Huber, M., Baatsen, M. L. J., Caballero, R., DeConto, R., Donnadieu, Y., Evans, D., Feng, R., Foster, G., Gasson, E., von der Heydt, A. S., Hollis, C. J., Kirtland Turner, S., Korty, R. L., Kozdon, R., Krishnan, S., Ladant, J.-B., Langebroek, P., Lear, C. H., LeGrande, A. N., Littler, K., Markwick, P., Otto-Bliesner, B., Pearson, P., Poulsen, C., Salzmann, U., Shields, C., Snell, K., Starz, M., Super, J., Tabour, C., Tierney, J., Tourte, G. J. L., Upchurch, G. R., Wade, B., Wing, S. L., Winguth, A. M. E., Wright, N., Zachos, J. C., and Zeebe, R.: DeepMIP: experimental design for model simulations of the EECO, PETM, and pre-PETM, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-127, in review, 2016.

http://www.geosci-model-dev-discuss.net/gmd-2016-127/

Abstract. Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high (> 800 ppmv) atmospheric CO2 concentrations. Although a post-hoc intercomparison of Eocene (~50 million years ago, Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the latest Paleocene and the early Eocene. Together these form the first phase of DeepMIP – the deeptime model intercomparison project, itself a group within the wider Paleoclimate Modelling Intercomparison Project (PMIP). The experimental design consists of three core paleo simulations and a set of optional sensitivity studies. The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, orbital configuration, solar constant, land surface parameters, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological datasets, which will be used to evaluate the simulations, will be developed.


“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #31 on: September 24, 2016, 12:58:32 AM »
The linked open access reference discusses the PRISM4 designed to calibrate climate models against paleo-data on the mid-Piacenzian:



Dowsett, H.J., Dolan, A.M., Rowley, D., Moucha, R., Forte,A.M., Mitrovica, J.X., Pound, M., Salzmann, U., Robinson, M., Chandler, M.A., Foley, K., and Haywood, A.M. (2016), "The PRISM4 (mid-Piacenzian) paleoenvironmental reconstruction", Climate of the Past, Vol. 12, pp. 1519-1538, DOI NO:10.5194/cp-12-1519-2016


http://www.clim-past.net/12/1519/2016/cp-12-1519-2016.pdf


Abstract: "The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian (~3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments.  The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #32 on: September 24, 2016, 12:59:54 AM »
The linked open access reference discusses the PlioMIP designed to calibrate climate models against paleo-data on the Pliocene:

Haywood, A.M., Dowsett, H.J., Dolan, A.M., Rowley, D., Ayako, A., Otto-Bliesner, B., Chandler, M.A., Hunter, S.J., Lunt, D.J., Pound, M. and Salzmann, U. (2016), "The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: scientific objectives and experimental design", Climate of the Past, Vol. 12, pp. 663-675, DOI NO: 10.5194/cp-12-663-2016

http://www.clim-past.net/12/663/2016/cp-12-663-2016.pdf

Abstract: "The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data–model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land–ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models.

Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate
change in a discrete way."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #33 on: September 25, 2016, 05:01:36 PM »
The three linked (open access) Geosci. Model Dev. references discuss Model Intercomparison Projects for sea ice; the stratosphere–troposphere system, and land use, respectively.  All will be used to help calibrate CMIP6 projections:

Notz, D., Jahn, A., Holland, M., Hunke, E., Massonnet, F., Stroeve, J., Tremblay, B., and Vancoppenolle, M.: The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): understanding sea ice through climate-model simulations, Geosci. Model Dev., 9, 3427-3446, doi:10.5194/gmd-9-3427-2016, 2016.

http://www.geosci-model-dev.net/9/3427/2016/

Abstract. A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standard for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. In this contribution, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.

&

Gerber, E. P. and Manzini, E.: The Dynamics and Variability Model Intercomparison Project (DynVarMIP) for CMIP6: assessing the stratosphere–troposphere system, Geosci. Model Dev., 9, 3413-3425, doi:10.5194/gmd-9-3413-2016, 2016.

http://www.geosci-model-dev.net/9/3413/2016/

Abstract. Diagnostics of atmospheric momentum and energy transport are needed to investigate the origin of circulation biases in climate models and to understand the atmospheric response to natural and anthropogenic forcing. Model biases in atmospheric dynamics are one of the factors that increase uncertainty in projections of regional climate, precipitation and extreme events. Here we define requirements for diagnosing the atmospheric circulation and variability across temporal scales and for evaluating the transport of mass, momentum and energy by dynamical processes in the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6). These diagnostics target the assessments of both resolved and parameterized dynamical processes in climate models, a novelty for CMIP, and are particularly vital for assessing the impact of the stratosphere on surface climate change.

&

Lawrence, D. M., Hurtt, G. C., Arneth, A., Brovkin, V., Calvin, K. V., Jones, A. D., Jones, C. D., Lawrence, P. J., de Noblet-Ducoudré, N., Pongratz, J., Seneviratne, S. I., and Shevliakova, E.: The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design, Geosci. Model Dev., 9, 2973-2998, doi:10.5194/gmd-9-2973-2016, 2016.

http://www.geosci-model-dev.net/9/2973/2016/

Abstract. Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.

LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #34 on: September 26, 2016, 11:53:31 PM »
Per the linked article, the test bed for the ACME project should be available before the end of 2016:

Williams, D. N. (2016), Better tools to build better climate models, Eos, 97, doi:10.1029/2016EO045055. Published on 9 February 2016.

https://eos.org/project-updates/better-tools-to-build-better-climate-models

Extract: "The prototype test bed team is now under the banner of the newly formed Accelerated Climate Modeling for Energy (ACME) project, under the auspices of the U.S. Department of Energy’s Office of Science. Under ACME, the team will continue its efforts to deliver an advanced model development, testing, and execution workflow and data infrastructure production test bed for DOE climate and energy research needs. We anticipate rolling out the test bed by end of 2016 for ACME use."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #35 on: September 27, 2016, 06:01:27 PM »
The linked editorial discusses efforts to try to quantify uncertainties in future ocean carbon uptake:

John P. Dunne (22 September 2016), "Quantifying uncertainty in future ocean carbon uptake", Global Biogeochemical Cycles, DOI: 10.1002/2016GB005525

http://onlinelibrary.wiley.com/doi/10.1002/2016GB005525/abstract

Abstract: "Attributing uncertainty in ocean carbon uptake between societal trajectory (scenarios), earth system model construction (structure), and inherent natural variation in climate (internal), is critical to make progress in identifying, understanding and reducing those uncertainties. In the present issue of Global Biogeochemical Cycles, Lovenduski et al. (2016) disentangle these drivers of uncertainty in ocean carbon uptake over time and space and assess the resulting implications for the emergence timescales of structural and scenario uncertainty over internal variability. Such efforts are critical for establishing realizable and efficient monitoring goals and prioritizing areas of continued model development. Under recently proposed climate stabilization targets, such efforts to partition uncertainty also become increasingly critical to societal decision-making in the context of carbon stabilization."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #36 on: October 03, 2016, 04:59:44 AM »
The linked reference discusses the effect of quadrupling the pre-industrial levels of atmospheric CO2 concentrations (to about 1120ppmv)  on the poleward expansion of the Hadley Cell as projected by nine models within the Geoengineering Model Intercomparison Project (GeoMIP).  The fact that responses of the nine models ranged by a factor of 3 does not give me much confidence that these models are ready to project the out-comes of potential geoengineering efforts:

Davis, N. A., Seidel, D. J., Birner, T., Davis, S. M., and Tilmes, S.: Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulations, Atmos. Chem. Phys., 16, 10083-10095, doi:10.5194/acp-16-10083-2016, 2016.

http://www.atmos-chem-phys.net/16/10083/2016/


Abstract. Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause this pattern of changes in observations and model experiments, but the results here indicate that seasonally and hemispherically asymmetric tropical expansion can be a basic response of the general circulation to climate forcings.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #37 on: October 06, 2016, 03:34:35 AM »
The linked article confirms that currently climate model projections may not correctly characterize “true” climate system sensitivity for the conditions in the near future; hand hopes that paleo work on the last glacial cycle will help to clarify this issue:


Latif, M., M. Claussen, M. Schulz, and T. Brücher (2016), Comprehensive Earth system models of the last glacial cycle, Eos, 97, doi:10.1029/2016EO059587. Published on 23 September 2016


https://eos.org/project-updates/comprehensive-earth-system-models-of-the-last-glacial-cycle

 
Extract: “Current ESMs also lack potentially important interactions, involving the global carbon cycle, sea level, and ice sheets, which may, for example, explain fast and asynchronous changes in atmospheric carbon dioxide (CO2) and methane during abrupt climate changes. Also, ESMs do not yet adequately incorporate the effects of carbon and methane stored in permafrost on land and as gas hydrates in marine sediments in amplifying climate variations triggered by Earth’s orbit and rotation axis changes.
PalMod scientists intend to fill these gaps. Climate reconstructions on multimillennial timescales show a high correlation between globally averaged surface air temperature and atmospheric CO2levels. This correlation suggests a tight coupling between the physical climate system and the carbon cycle, such that perturbations in either component will be reinforced by the other.
The sea surface temperature is one factor that influences oceanic carbon uptake because the solubility of CO2 in water varies inversely with temperature. Sea surface temperature is largely governed by the strength of the greenhouse effect, which in turn depends on atmospheric CO2levels, so PalMod scientists are working to better incorporate proxies of past sea surface temperatures into their models.

So far, most model studies have attempted to estimate equilibrium climate sensitivity—the globally averaged equilibrium surface air temperature change in response to a doubling of the preindustrial CO2 concentration. However, the response of the very slow components of the Earth system, including ice sheets and weathering, is not yet represented in the models. Thus, the question of the “true” climate system sensitivity, or Earth system sensitivity, remains unanswered. “
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #38 on: October 07, 2016, 05:46:06 PM »
The linked research provides insights from a refined decomposition analysis of cloud feedbacks.  Such research should help to allow researchers to better calibrate their climate models in order to reduce uncertainties associated with ECS:

Mark D. Zelinka, Chen Zhou & Stephen A. Klein (14 September 2016), "Insights from a refined decomposition of cloud feedbacks", Geophysical Research Letters, DOI: 10.1002/2016GL069917


http://onlinelibrary.wiley.com/doi/10.1002/2016GL069917/abstract


Abstract: "Decomposing cloud feedback into components due to changes in several gross cloud properties provides valuable insights into its physical causes. Here we present a refined decomposition that separately considers changes in free tropospheric and low cloud properties, better connecting feedbacks to individual governing processes and avoiding ambiguities present in a commonly used decomposition. It reveals that three net cloud feedback components are robustly nonzero: positive feedbacks from increasing free tropospheric cloud altitude and decreasing low cloud cover and a negative feedback from increasing low cloud optical depth. Low cloud amount feedback is the dominant contributor to spread in net cloud feedback but its anticorrelation with other components damps overall spread. The ensemble mean free tropospheric cloud altitude feedback is roughly 60% as large as the standard cloud altitude feedback because it avoids aliasing in low cloud reductions. Implications for the “null hypothesis” climate sensitivity from well-understood and robustly simulated feedbacks are discussed."

See also:

Hall, S. (2016), "Eliminating uncertainty one cloud at a time", Eos, 97, doi:10.1029/2016EO059887. Published on 03 October 2016.


https://eos.org/research-spotlights/eliminating-uncertainty-one-cloud-at-a-time?utm_source=eos&utm_medium=email&utm_campaign=EosBuzz100716

Extract: "For decades, climate models have strongly disagreed on how cloud properties—and their effects on Earth’s energy budget—will change with global warming, making clouds the biggest source of uncertainty in climate model predictions.
Thus, climate scientists will be able to narrow uncertainty in forecasting climate change only if they can better constrain the feedbacks from clouds. With that in mind, Zelinka et al. decompose cloud feedbacks to better connect them to specific physical processes.

In this case, the authors refined the technique to compute amount, altitude, and optical depth feedbacks separately for upper-level and low-level clouds. Low-level clouds are those that reside in the boundary layer, the layer of Earth’s atmosphere directly influenced by its surface. Upper-level clouds reside above the boundary layer and are affected by different processes.
The team discovered that all climate models agree on the direction of three main feedbacks that accompany global warming. First, upper-level clouds rise to higher altitudes in all models, warming the planet by trapping more heat. Although this was previously known, the positive feedback is actually smaller and better constrained than past research has suggested. Second, low-level cloud cover decreases in all models, warming the planet by reflecting less incoming sunlight back to space. And third, the optical depth of low-level clouds increases in all models, cooling the planet by reflecting more sunlight.

Decomposing cloud feedbacks into individual components provides valuable insights into the individual mechanisms at play."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #39 on: October 10, 2016, 05:35:17 PM »
The linked reference discusses efforts to help calibrated climate models to better represent Arctic Cloud feedback mechanisms:

Kay, J.E., L’Ecuyer, T., Chepfer, H. et al. (2016), "Recent Advances in Arctic Cloud and Climate Research", Curr Clim Change Rep, doi:10.1007/s40641-016-0051-9


http://rd.springer.com/article/10.1007%2Fs40641-016-0051-9?wt_mc=Affiliate.CommissionJunction.3.EPR1089.DeepLink&utm_medium=affiliate&utm_source=commission_junction&utm_campaign=3_nsn6445_deeplink&utm_content=deeplink


Abstract: "While the representation of clouds in climate models has become more sophisticated over the last 30+ years, the vertical and seasonal fingerprints of Arctic greenhouse warming have not changed. Are the models right? Observations in recent decades show the same fingerprints: surface amplified warming especially in late fall and winter. Recent observations show no summer cloud response to Arctic sea ice loss but increased cloud cover and a deepening atmospheric boundary layer in fall. Taken together, clouds appear to not affect the fingerprints of Arctic warming. Yet, the magnitude of warming depends strongly on the representation of clouds. Can we check the models? Having observations alone does not enable robust model evaluation and model improvement. Comparing models and observations is hard enough, but to improve models, one must both understand why models and observations differ and fix the parameterizations. It is all a tall order, but recent progress is summarized here."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #40 on: October 12, 2016, 11:25:48 PM »
The linked reference discusses CORE-II simulations, Part III: Hydrography and fluxes, as part of an effort to better calibrate Arctic Ocean models (see the attached image of the main Arctic Ocean masses of water of Atlantic origin).  Once properly calibrates such ocean models could be identify the risk of ocean heat transport from the Atlantic & Pacific into the Arctic Basin under different future radiative forcing scenarios:

Mehmet Ilıcak et. al. (April 2016), "An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part III: Hydrography and fluxes", Ocean Modelling, Volume 100, Pages 141–161, http://dx.doi.org/10.1016/j.ocemod.2016.02.004


http://www.sciencedirect.com/science/article/pii/S1463500316000238


Abstract: "In this paper we compare the simulated Arctic Ocean in 15 global ocean–sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE-II). Most of these models are the ocean and sea-ice components of the coupled climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments. We mainly focus on the hydrography of the Arctic interior, the state of Atlantic Water layer and heat and volume transports at the gateways of the Davis Strait, the Bering Strait, the Fram Strait and the Barents Sea Opening. We found that there is a large spread in temperature in the Arctic Ocean between the models, and generally large differences compared to the observed temperature at intermediate depths. Warm bias models have a strong temperature anomaly of inflow of the Atlantic Water entering the Arctic Ocean through the Fram Strait. Another process that is not represented accurately in the CORE-II models is the formation of cold and dense water, originating on the eastern shelves. In the cold bias models, excessive cold water forms in the Barents Sea and spreads into the Arctic Ocean through the St. Anna Through. There is a large spread in the simulated mean heat and volume transports through the Fram Strait and the Barents Sea Opening. The models agree more on the decadal variability, to a large degree dictated by the common atmospheric forcing. We conclude that the CORE-II model study helps us to understand the crucial biases in the Arctic Ocean. The current coarse resolution state-of-the-art ocean models need to be improved in accurate representation of the Atlantic Water inflow into the Arctic and density currents coming from the shelves."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #41 on: October 14, 2016, 04:28:56 PM »
he linked reference cites the use of paleo data to help calibrate the HadCM3L climate model.  Such calibration of climate models will help improve the accuracy of projections for future conditions.

Howard A. Armstrong et. al. (3 August 2016), "Hadley circulation and precipitation changes controling black shale deposition in the Late Jurassic Boreal Seaway", Paleoceanography, DOI: 10.1002/2015PA002911


http://onlinelibrary.wiley.com/doi/10.1002/2015PA002911/full

Abstract: "New climate simulations using the HadCM3L model with a paleogeography of the Late Jurassic (155.5 Ma) and proxy-data corroborate that warm and wet tropical-like conditions reached as far north as the UK sector of the Jurassic Boreal Seaway (~35°N). This is associated with a northern hemisphere Jurassic Hadley cell and an intensified subtropical jet which both extend significantly poleward than in the modern (July–September). Deposition of the Kimmeridge Clay Formation (KCF) occurred in the shallow, storm-dominated, epeiric Boreal Seaway. High-resolution paleo-environmental proxy data from the Kimmeridge Clay Formation (KCF; ~155–150 Ma), UK, are used to test for the role of tropical atmospheric circulation on meter-scale heterogeneities in black shale deposition. Proxy and model data show that the most organic-rich section (eudoxus to mid-hudlestoni zones) is characterized by a positive δ13Corg excursion and up to 37 wt % total organic carbon (%TOC). Orbital modulation of organic carbon burial primarily in the long eccentricity power band combined with a clear positive correlation between %TOC carbonate-free and the kaolinite/illite ratio supports peak organic carbon burial under the influence of very humid climate conditions, similar to the modern tropics. This reinterpretation of large-scale climate relationships, supported by independent modeling and geological data, has profound implications for atmospheric circulation patterns and processes affecting marine productivity and organic carbon burial further north along the Boreal Seaway, including the Arctic."

See also:
Hall, S. (2016), Simulating the climate 145 million years ago, Eos, 97, doi:10.1029/2016EO060569. Published on 10 October 2016.

https://eos.org/research-spotlights/simulating-the-climate-145-million-years-ago?utm_source=eos&utm_medium=email&utm_campaign=EosBuzz101416

Extract: "Not only were the researchers able to verify that the United Kingdom was once a tropical oasis, but they were also able to simulate and map the climate 145 million years ago—research that will help scientists better understand how Earth will react to anthropogenic warming today and in the future."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #42 on: October 20, 2016, 05:26:14 PM »
The linked reference studies seasonal constraints on inferred planetary heat content, and finds that there is a need to more thoroughly measure the upper ocean heat content.

Karen A. McKinnon & Peter Huybers (18 October 2016), "Seasonal constraints on inferred planetary heat content", Geophysical Research Letters, DOI: 10.1002/2016GL071055

http://onlinelibrary.wiley.com/doi/10.1002/2016GL071055/abstract

Abstract: "Planetary heating can be quantified using top of the atmosphere energy fluxes or through monitoring the heat content of the earth system. It has been difficult, however, to compare the two methods with each other because of biases in satellite measurements and incomplete spatial coverage of ocean observations. Here, we focus on the the seasonal cycle whose amplitude is large relative to satellite biases and observational errors. The seasonal budget can be closed through inferring contributions from high-latitude oceans and marginal seas using the covariance structure of NCAR CESM1. In contrast, if these regions are approximated as the average across well-observed regions, the amplitude of the seasonal cycle is overestimated relative to satellite constraints. Analysis of the same CESM1 simulation indicates that complete measurement of the upper ocean would increase the magnitude and precision of interannual trend estimates in ocean heating more than fully measuring the deep ocean."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #43 on: October 21, 2016, 05:02:58 PM »
The linked reference examines the uncertainties associated with projecting how much CO₂ the ocean will absorb through 2080; and it finds that these uncertainties are spatial and heterogenous in nature.  Pinning down such uncertainties is important if we are going to avoid unpleasant future surprises w.r.t. climate change response:

Nicole S. Lovenduski, Galen A. McKinley, Amanda R. Fay, Keith Lindsay & Matthew C. Long (1 September 2016), "Partitioning uncertainty in ocean carbon uptake projections: Internal variability, emission scenario, and model structure", Global Biogeochemical Cycles, DOI: 10.1002/2016GB005426

http://onlinelibrary.wiley.com/doi/10.1002/2016GB005426/abstract

Abstract: "We quantify and isolate the sources of projection uncertainty in annual-mean sea-air CO2 flux over the period 2006–2080 on global and regional scales using output from two sets of ensembles with the Community Earth System Model (CESM) and models participating in the 5th Coupled Model Intercomparison Project (CMIP5). For annual-mean, globally-integrated sea-air CO2 flux, uncertainty grows with prediction lead time and is primarily attributed to uncertainty in emission scenario. At the regional scale of the California Current System, we observe relatively high uncertainty that is nearly constant for all prediction lead times, and is dominated by internal climate variability and model structure, respectively in the CESM and CMIP5 model suites. Analysis of CO2 flux projections over 17 biogeographical biomes reveals a spatially heterogenous pattern of projection uncertainty. On the biome scale, uncertainty is driven by a combination of internal climate variability and model structure, with emission scenario emerging as the dominant source for long projection lead times in both modeling suites."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #44 on: October 21, 2016, 05:38:05 PM »
The linked open access reference offers new observations and recommendations for modeling procedures to reduce uncertainties for both aerosol radiative forcing and for climate sensitivity associated with atmospheric updrafts:

Donner, L. J., O'Brien, T. A., Rieger, D., Vogel, B., and Cooke, W. F.: Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?, Atmos. Chem. Phys., 16, 12983-12992, doi:10.5194/acp-16-12983-2016, 2016.

http://www.atmos-chem-phys.net/16/12983/2016/

Abstract. Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction.

Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations that do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models.

New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #45 on: October 21, 2016, 05:50:26 PM »
The linked open access reference provides recommendations on how to better use paleo data about fast and slow feedback mechanisms in order to better estimate future non-stationary climate sensitivity (see the attached image of Figure 2 from the reference):

von der Heydt, A.S., Dijkstra, H.A., van de Wal, R.S.W. et al. (2016), "Lessons on Climate Sensitivity From Past Climate Changes", Curr Clim Change Rep; doi:10.1007/s40641-016-0049-3


http://rd.springer.com/article/10.1007%2Fs40641-016-0049-3?wt_mc=Affiliate.CommissionJunction.3.EPR1089.DeepLink&utm_medium=affiliate&utm_source=commission_junction&utm_campaign=3_nsn6445_deeplink&utm_content=deeplink

Abstract: "Over the last decade, our understanding of climate sensitivity has improved considerably. The climate system shows variability on many timescales, is subject to non-stationary forcing and it is most likely out of equilibrium with the changes in the radiative forcing. Slow and fast feedbacks complicate the interpretation of geological records as feedback strengths vary over time. In the geological past, the forcing timescales were different than at present, suggesting that the response may have behaved differently. Do these insights constrain the climate sensitivity relevant for the present day? In this paper, we review the progress made in theoretical understanding of climate sensitivity and on the estimation of climate sensitivity from proxy records. Particular focus lies on the background state dependence of feedback processes and on the impact of tipping points on the climate system. We suggest how to further use palaeo data to advance our understanding of the currently ongoing climate change."

Caption for Figure 2: "Schematic of the phase diagram of a climate model with two stable coexisting climate states. The shape of the S curve follows closely that discussed in [62–64]; see also [65]. The climate sensitivity parameter S is defined on each of the stable branches as the local slope of the global mean surface temperature T versus the (logarithm of) atmospheric pCO2 (cf. Eq. 8 ). Type I state dependence: When starting at point A (e.g. the pre-industrial climate), the temperature increase after a doubling of pCO2 (point B) is smaller than when starting from a colder climate (point C) on the same branch. Type II state dependence: When the initial pCO2 is the same as in point A, but the climate is initially on the cold branch (point D), a doubling of pCO2 results in a smaller temperature increase (point E) than if starting from point A and ending in point B. S becomes undefined at the transition points (open squares) between the two branches. The conditional climate sensitivity is equal to S for small perturbations (going from points D to E), but largely increases if the perturbation in CO2 is large enough to move the system from point D beyond the bifurcation point (blue open square) and jumps to the warm branch. Note that S is generally defined as a local gradient, while the 2xCO2 definition in the ECS may involve a perturbation too large for the linear assumption along the branch to be applicable."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #46 on: October 23, 2016, 06:54:23 PM »
The linked reference discusses the planned contribution of the The Global Monsoons Model Inter-comparison Project (GMMIP) to better calibrating CMIP6:

Zhou, T., Turner, A. G., Kinter, J. L., Wang, B., Qian, Y., Chen, X., Wu, B., Wang, B., Liu, B., Zou, L., and He, B.: GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project, Geosci. Model Dev., 9, 3589-3604, doi:10.5194/gmd-9-3589-2016, 2016


http://www.geosci-model-dev.net/9/3589/2016/

Abstract. The Global Monsoons Model Inter-comparison Project (GMMIP) has been endorsed by the panel of Coupled Model Inter-comparison Project (CMIP) as one of the participating model inter-comparison projects (MIPs) in the sixth phase of CMIP (CMIP6). The focus of GMMIP is on monsoon climatology, variability, prediction and projection, which is relevant to four of the “Grand Challenges” proposed by the World Climate Research Programme. At present, 21 international modeling groups are committed to joining GMMIP. This overview paper introduces the motivation behind GMMIP and the scientific questions it intends to answer. Three tiers of experiments, of decreasing priority, are designed to examine (a) model skill in simulating the climatology and interannual-to-multidecadal variability of global monsoons forced by the sea surface temperature during historical climate period; (b) the roles of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation in driving variations of the global and regional monsoons; and (c) the effects of large orographic terrain on the establishment of the monsoons. The outputs of the CMIP6 Diagnostic, Evaluation and Characterization of Klima experiments (DECK), “historical” simulation and endorsed MIPs will also be used in the diagnostic analysis of GMMIP to give a comprehensive understanding of the roles played by different external forcings, potential improvements in the simulation of monsoon rainfall at high resolution and reproducibility at decadal timescales. The implementation of GMMIP will improve our understanding of the fundamental physics of changes in the global and regional monsoons over the past 140 years and ultimately benefit monsoons prediction and projection in the current century.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #47 on: October 23, 2016, 07:24:04 PM »
Many people seem to consider the RCP scenarios as if they definitively cover our radiative forcing risk profile.  However, the linked reference on the Radiative Forcing Model Intercomparison Project (RFMIP); indicates that CMIP6 understands that this simply is not the case; and seek to provide a better foundation to understanding what these risks actually are:

Robert Pincus, Piers M Forster and Bjorn Stevens (2016), "The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental Protocol for CMIP6", Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-88

http://www.geosci-model-dev-discuss.net/gmd-2016-88/gmd-2016-88.pdf

Abstract. The phrasing of the first of three questions motivating CMIP6 – “How does the Earth system respond to forcing?” – suggests that forcing is always well-known, but in fact forcing has historically been uncertain even in coordinated experiments such as CMIP. The Radiative Forcing Model Intercomparison Project endorsed by CMIP6 seeks to provide a foundation for answering the question for forcing and response through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near pre-industrial baseline, and careful diagnosis of the components of this forcing; (ii) assessment of the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to a tightly-specified aerosol radiative forcing from 1850 to present.


Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphere-only simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model’s pre-industrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally-detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model’s radiation code applied to specified atmospheric conditions. The search for robust responses to aerosol changes rely on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one, and up to four, 165-year coupled ocean-atmosphere simulations at Tier 1."
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #48 on: October 29, 2016, 04:53:51 PM »
The linked open source reference discusses the importance of open ocean sensible heat flux & its influence of the Artic boundary layer during the early boreal Fall (see the attached plot):

Ganeshan, M. and Wu, D. L.: The open-ocean sensible heat flux and its significance for Arctic boundary layer mixing during early fall, Atmos. Chem. Phys., 16, 13173-13184, doi:10.5194/acp-16-13173-2016, 2016.

http://www.atmos-chem-phys.net/16/13173/2016/


Abstract. The increasing ice-free area during late summer has transformed the Arctic to a climate system with more dynamic boundary layer (BL) clouds and seasonal sea ice growth. The open-ocean sensible heat flux, a crucial mechanism of excessive ocean heat loss to the atmosphere during the fall freeze season, is speculated to play an important role in the recently observed cloud cover increase and BL instability. However, lack of observations and understanding of the resilience of the proposed mechanisms, especially in relation to meteorological and interannual variability, has left a poorly constrained BL parameterization scheme in Arctic climate models. In this study, we use multi-year Japanese cruise-ship observations from R/V Mirai over the open Arctic Ocean to characterize the surface sensible heat flux (SSHF) during early fall and investigate its contribution to BL turbulence. It is found that mixing by SSHF is favored during episodes of high surface wind speed and is also influenced by the prevailing cloud regime. The deepest BLs and maximum ocean–atmosphere temperature difference are observed during cold air advection (associated with the stratocumulus regime), yet, contrary to previous speculation, the efficiency of sensible heat exchange is low. On the other hand, the SSHF contributes significantly to BL mixing during the uplift (low pressure) followed by the highly stable (stratus) regime. Overall, it can explain  ∼  10 % of the open-ocean BL height variability, whereas cloud-driven (moisture and radiative) mechanisms appear to be the other dominant source of convective turbulence. Nevertheless, there is strong interannual variability in the relationship between the SSHF and the BL height which can be intensified by the changing occurrence of Arctic climate patterns, such as positive surface wind speed anomalies and more frequent conditions of uplift. This study highlights the need for comprehensive BL observations like the R/V Mirai for better understanding and predicting the dynamic nature of the Arctic climate.
“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: 12765
    • View Profile
Re: Climate Model Test Beds: Calibrating Nonlinear ESMs focused on ACME
« Reply #49 on: October 31, 2016, 05:14:58 PM »
The linked reference provides information to better calibrate ESM projection with regard to the influence of black carbon on radiative forcing in the Arctic:

D.O.U. Ting-Feng & X.I.A.O. Cun-De (October 28, 2016), "An overview of black carbon deposition and its radiative forcing over the Arctic", Advances in Climate Change Research, http://dx.doi.org/10.1016/j.accre.2016.10.003


http://www.sciencedirect.com/science/article/pii/S1674927816300284


Abstract: "This paper gives an overview of the current understanding of the observations of black carbon (BC) in snow and ice, and the estimates of BC deposition and its radiative forcing over the Arctic. Both of the observations and model results show that, in spring, the average BC concentration and the resulting radiative forcing in Russian Arctic > Canadian and Alaskan Arctic > Arctic Ocean and Greenland. The observed BC concentration presented a significant decrease trend from the Arctic coastal regions to the center of Arctic Ocean. In summer, due to the combined effects of BC accumulation and enlarged snow grain size, the averaged radiative forcing per unit area over the Arctic Ocean is larger than that over each sector of the Arctic in spring. However, because summer sea ice is always covered by a large fraction of melt ponds, the role of BC in sea ice albedo evolution during this period is secondary. Multi-model mean results indicate that the annual mean radiative forcing from all sources of BC in snow and ice over the Arctic was ∼0.17 W m-2. Wet deposition is the dominant removal mechanism in the Arctic, which accounts for more than 90% of the total deposition. In the last part, we discuss the uncertainties in present modeling studies, and suggest potential approaches to reduce the uncertainties."
“It is not the strongest or the most intelligent who will survive but those who can best manage change.”
― Leon C. Megginson