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Pattern Scaling, Climate Model Emulators and their Application
to the New Scenario Process
National Center for Atmospheric Research (NCAR), Boulder, CO April 23-25, 2014
Meeting Report
Version 2, October 21, 2014
Organizing committee and core writing team Brian O’Neill, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA. Claudia Tebaldi, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA. James Murphy, Met Office Hadley Centre, Exeter, UK. Tim Carter, Finnish Environment Institute (SYKE), Helsinki, Finland. Acknowledgments This workshop was supported by the Institute for Mathematics Applied to the Geosciences (IMAGe) and the Climate and Global Dynamics (CGD) division of the National Center for Atmospheric Research, Boulder, Colorado, and the World Meteorological Organization (WMO), Geneva, Switzerland.
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Table of Contents
1. Meeting goals and background ..................................................................... 3 2. Outline of the meeting ..................................................................................... 4
2.1 Participants and structure .................................................................................... 4 2.2 Day 1 ........................................................................................................................ 5 2.3 Day 2 ........................................................................................................................ 6 2.4 Day 3 ........................................................................................................................ 8
3. Meeting Outcomes ........................................................................................... 9 3.1 To what extent do pattern scaling or other forms of emulation work well (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties)? ............................................................................. 9 3.2 What are current and near-future needs from impact and IAM communities (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties and measures of reliability)? ........................... 10 3.3 What is the outlook for progress in areas that do not yet work well? What new ESM simulations would be useful? .................................................................... 11 3.4 How should emulation techniques be incorporated in integrated scenario development and in the planning of future climate model experiments? ........... 12
4. Next steps ........................................................................................................ 13 Appendix 1 Participants Appendix 2 Meeting agenda Appendix 3 Pattern scaled or emulated primary variables of potential interest to users.
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1. Meeting goals and background Climate model emulators are techniques for generating projections of future climate using a statistical model designed to reproduce results that would be expected from applying more complex Earth System Models (ESMs) of the global climate system, but in a fraction of the time. One of the more popular and widely used of these techniques is pattern scaling. Emulators in general, and pattern scaling in particular, could play an important role in a new process underway by the climate change research community to produce integrated scenarios of future climate and societal change. These scenarios will underpin research by the integrated assessment modeling (IAM) and impact modeling communities on options for mitigating or adapting to climate change, as well as on estimating impacts that may occur. The research community would like to explore a large number of scenarios, but projecting climate change in each case with large, computationally expensive climate models is infeasible. At the same time, the option of using emulators as a practical and credible alternative is open to question. A workshop was organized on April 23-25, 2014, at the National Center for Atmospheric Research (NAR) in order to investigate this topic. The workshop had three main goals:
• Assess the current state of pattern scaling/climate model emulator science;
• Assess to what extent current approaches to the statistical approximation of climate model output can meet the needs for climate change information of integrated assessment and impact modelers;
• Identify and prioritize research directions so that these methods can better meet the needs of applied research in the future.
Based on these goals, the organizing committee formulated a set of four key questions for the workshop to address:
• To what extent do pattern scaling or other forms of emulation work well (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties)?
• What are current and near-future needs from impact and IAM communities (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties and measures of reliability)?
• What is the outlook for progress in areas that do not yet work well? What new ESM simulations would be useful?
• How should emulation techniques be incorporated in integrated scenario development and in the planning of future climate model experiments?
The workshop was organized as part of a wider process leading to the adoption of an experimental design for the Coupled Model Intercomparison Project Phase
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6 (CMIP6), and specifically a particular inter-comparison activity focused on future scenarios (ScenarioMIP). CMIP6 coordinates climate model simulations by modeling centers from around the world in order to improve understanding of the climate system. Under the new structure proposed for CMIP6, a small set of core runs performed as part of the regular diagnosis and evaluation of the new climate models will be augmented by further experiments, proposed by satellite MIPs and approved and coordinated by the CMIP panel (Meehl et al., 2014). ScenarioMIP is one such satellite MIP and is responsible for proposing a set of plausible future scenarios of anthropogenic forcings (greenhouse gases, aerosols and land use changes) to be run by the participating modeling centers. At an August 2013 Aspen Global Change Institute workshop on “Next generation climate change experiments needed to advance knowledge and for assessment of CMIP6”, the importance was highlighted of assessing the potential of pattern scaling and other forms of emulation in filling the gaps left by the necessity of identifying only a small number of future scenarios to be run as part of ScenarioMIP. Plans for the Boulder workshop were initiated at that event. However, the possible role of pattern scaling in producing climate information for the scenario process had been noted much earlier (Moss et al., 2010). Plans for CMIP6 were further discussed and refined at the 17th World Climate Research Programme (WCRP) Working Group on Coupled Modeling (WGCM) session that took place in October 2013 in Victoria, Canada, which also provided additional endorsement for the Boulder pattern scaling workshop. In this report we provide in section 2 a sketch of the meeting structure and content, in section 3 a synthesis of the meeting outcomes and in section 4 a summary of next steps.
2. Outline of the meeting
2.1 Participants and structure The workshop participants (60, including 1 participating remotely, see Appendix 1) belonged, broadly speaking, to three different research communities: climate scientists with direct experience of climate modeling, experts in empirical emulation techniques and impact or integrated assessment modelers. Thus they represented both the producers of climate information (using process-based or statistical models) and its users. The meeting agenda (Appendix 2) was structured around the two main perspectives on the emulation issue, the first being the top-down perspective of the producers of climate model output and its empirical approximations, and the second the bottom-up perspective of the impact and assessment modeling
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communities, which is informed by the climate data requirements for impact modeling, and by the need to develop understanding of alternative mitigation pathways.
2.2 Day 1 Day 1 started with an introductory talk that outlined the meeting motivation and goals (C. Tebaldi), and an overview talk (B. O’Neill) that explained the scenario process, its matrix structure, and the potential role of emulation techniques within it. After those talks set the stage, the first session focused on pattern scaling and emulation (PS/E) methods, with an overview talk (J. Murphy and C. Tebaldi) that broadly described the techniques and highlighted some of the main challenges. Two talks then focused on reasons why patterns might not be constant across time, because of non-linear behaviors or differences in the time-scale of the response (P. Good), or from dependence of precipitation patterns on emission scenarios, especially when aerosols are a significant part of the forcing mix (H. Shiogama). Then, the use of pattern scaling to produce probabilistic projections at regional scale was presented, with specific application to projections for the Australian region, and a particular focus on the challenge of producing coherent joint PDFs of temperature and precipitation (I. Watterson). The discussion session highlighted the need for rigorous evaluation of PS/E errors (compared, for example, to multi-model spread) and for better assessment of how important non-linearities and time-scale differences really are, and stressed the importance of examining variables other than average temperature and precipitation (e.g., extremes, storm track shifts, SLR) for impact analysis. The second session addressed user needs, with an overview talk (T. Carter) followed by talks on three applications. The overview talk described uses of PS/Es by the IAV and IAM communities and benefits and shortcomings of the methods from users’ perspectives. Benefits include the expediency with which users can produce a range of climate scenarios drawing on a library of model patterns. However there are a number of concerns or shortcomings as well, including the consistency of joint realizations of multiple variable or across time, the need to account for variability at the scales not resolved by pattern scaling but still crucial for impact analysis, and the lack of signals from non-GHG forcing agents, such as aerosols. The first of the three presentations of applications offered the experience of the MIT group in adapting pattern scaling to the analysis of hydrological impacts for specific river basin in an integrated modeling framework (A. Schlosser). It highlighted some key shortcomings of the method having to do with spatial and time resolutions, representation of variability, and missing local-scale feedbacks. The second presentation (K. Frieler) identified a set of relevant variables for impact modeling based on the experience of the Inter-Sectoral Impact Model
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Intercomparison Project (ISI-MIP). It also compared the approach of driving impact models with PS/E output to the approach of developing and using impact response functions, which fit a direct relationship between global average temperature change and impacts. The last talk presented the implementation of PS in the ClimGen software (T. Osborn), emphasizing the treatment of variability that is added to the spatial patterns not as a fixed-size noise, but using parameters that scale variability itself (for precipitation) with global temperature change. Uncertainties due to differences in patterns when comparing different multi-model ensembles were also highlighted, with the related question of characterizing interaction between global and regional changes if one wants to build probabilistic projections at the local scale. The discussion period for this session focused on the different time horizons that are relevant for different clients/users of climate information. PS, by construction, works by identifying the signal that emerges from internal variability, and the longer time scales are therefore more appropriate to both developing and using PS. The point was made that academic researchers, policy makers and analysts providing decision support for adaptation have very different time horizons and ideally PS should address all of them. Choosing between undertaking many short simulations with complex ESMs rather than fewer longer ones (given finite computational resources) did not seem straightforward. The larger discussion at the end of the day covered the importance of understanding processes and feedbacks responsible for local and regional changes; the possibility of using coarser resolution models as alternative or complementary sources of climate information, given that these are cheaper to run than the state-of-the-art Earth System Models; the need to determine the number of ensemble members necessary to isolate signals from background noise; the role of emission driven ESMs vs. concentration driven general circulation models (GCMs) in the quest to represent sources of uncertainty as comprehensively as possible; and how the carbon-cycle uncertainty may be incorporated in PS/E techniques. The day concluded with a well-populated poster session covering both methodological and user needs perspectives, and a keynote talk by T. Wigley, who conceived of the pattern scaling technique and developed the software tool MAGICC-SCENGEN, which has offered ready access to model-based climate change information for thousands of researchers. The talk focused on the approach to aerosol forcing signal emulation within MAGICC-SCENGEN, a little-known feature of the software, based on Schlesinger et al. (2010).
2.3 Day 2
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The second day of the meeting was divided into two morning sessions with talks addressing methodology and user needs, and an afternoon of discussion within breakout groups focusing separately on the same two themes, with end-of-the-day reports back to plenary. The talks in the methodology session covered analyses and approaches that went beyond the traditional PS method. These included a description of the UKCP09 probabilistic projections, in which PS is only one aspect of a complex method making use of Perturbed Parameter Ensembles, Multi-model Ensembles, emulators, and statistical downscaling (G. Harris). An analysis of non-linearities when forcing pathways are different from the traditional steady increase (for example ramp-up/ramp-down or instantaneous doubling or quadrupling of CO2, or asymmetry in forcings such as CO2 increase compensated by change in solar constant) showed aspects of the climate system that do not behave in ways easily representable through PS (e.g., AMOC; N. Schaller). The alternative of distributed computing (e.g., Weather@Home) as a cheap solution to computationally expensive GCM experiments was mentioned. Also presented were an application of historical SST pattern estimation to isolate anthropogenic signals (assumed scalable by forcing), and hence drive atmosphere-only GCM simulations of climate change (A. Bichet), and a complex emulation technique recently implemented in the PLASIM-ENTSem software, emulating past and future spatio-temporal variations in decadal averages, for selected variables of interest (P. Holden). During the discussion of the session the idea of a Pattern Scaling MIP with standard validation/evaluation criteria and benchmarks was proposed, prompted by a comment about the reliability of the probabilistic projections computed through these methods and a question about the users’ interpretation and value of the methods’ outcomes. The second session of the morning presented applications of the methods to several specific domains. European projections obtained through RCMs within the ENSEMBLES projects were tested for linearity with respect to the corresponding global average temperature projections. All variables (averages over European subregions of temperature and precipitation variables, including some extremes indices) seemed to behave linearly (O. & J. Christensen). A presentation about sea level rise highlighted the complexity of scaling variables whose changes are the effect of different components, with different time scales and degrees of uncertainty: thermal expansion is scalable successfully using ocean heat content; regional patterns dominated by currents are estimated less robustly; other components present challenges, such as gravitational effects, ice sheet melting, possibly changes in storm characteristics when storm surges are also of interest (even if the evidence so far is that the sea level rise component dominates changes in surges, rather than changes in storm variability). The necessity of taking into account different types of users was highlighted in this application: policy makers interested in mitigation options with implications over
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multi-decadal to centennial time scales could be contrasted to adaptation planners, who may have shorter time scales of interest but might also require more robust uncertainty characterizations, especially when engineering projects are informed by these projections (J. Lowe). One of the few examples of validation of pattern scaling was presented for regional changes in SW England relevant to water resource management and heat wave characteristics in S Europe, illustrating the challenges of assessing pattern scaled results in the light of levels of accuracy required for decision making (A. Lopez).
The discussion after this session focused on the need for devising rigorous but fair (realistic) standards for validation, deciding upon which regional scales we should confront pattern scaling with, what metrics to use to measure errors, and against what alternative sources of climate information should pattern scaling be judged. The points were made that at times it is an intrinsic shortcoming of climate modeling, not necessarily a failure of emulators, that confronts the scientific community, and that users need guidance on what to look for, and expect, when they ask for climate change information.
During the afternoon, participants separated into three breakout groups, two of which discussed methodological aspects, while the third focused on user needs. They were provided with the overarching questions for the workshop (section 1) in order to guide discussion:
• To what extent does pattern scaling or other forms of emulation work well(which variables, geographic resolution, over time, uncertainty) and whatis the outlook for progress in areas that do not yet work well?
• What are current and near-future needs from impact and IAM communities(variables, geographic resolution, time resolution, uncertainty)?
• How should emulation techniques be incorporated in integrated scenariodevelopment and in the planning of future climate model experiments?
Results from the discussions were presented at the end of the day and are reported as part of the meeting outcomes described in section 3.
2.4 Day 3
On Friday morning, three of the co-chairs proposed short summaries of the main takeaway messages from the meeting as they related to methodology, user needs and the scenario process (see next section). Then a number of representatives of other MIPs provided their perspectives on the topic (J.-F. Lamarque for the Aerosols and Atmospheric Chemistry Model Intercomparison Project, AerChemMIP; D. Lawrence for the Land-Use Model Intercomparison Project, LUMIP; L. Mearns for the Agricultural Model Intercomparison and Improvement Project, AgMIP, and V. Eyring, chair of CMIP panel). The possibility of
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identifying idealized experiments that could aid the development of emulation methods and would be run within other MIPs was an underlying theme of this session. In the case of AgMIP, there is a clear and explicit interest by the group in adopting pattern scaling as a tool for exploring multiple scenarios/models and thus better characterizing uncertainty, and also providing projections not necessarily linked to a specific date but as a function of global temperature changes (e.g., the world at +2oC).
The meeting concluded with plans to produce concrete outcomes as described in sections 3 and 4.
3. Meeting Outcomes
We summarize meeting outcomes related to each of the key questions identified in section 1.
3.1 To what extent do pattern scaling or other forms of emulation work well (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties)?
It appears that no emulation method has to date been documented to produce results across a range of user relevant variables that are sufficiently accurate to fully substitute for climate model experiments.
• Experience suggests that PS/E may work well for some variables (such astemperature) averaged over a sufficient time period. To date, however,only a few studies provide formal demonstrations of the associated error.More work is needed to characterize PS/E errors systematically acrossdifferent methods, at different time and space scales and for differentvariables.
• Many approaches to the problem of emulation are being pursued for bothcommonly analyzed variables such as temperature and precipitation aswell as less commonly treated variables, suggesting that sophisticatedemulation techniques may eventually be shown to be successful undermany conditions.
• Criteria for what works “well” are application specific, depending on theuse to which PS/E is being put, the desired accuracy of the method, andthe relation between uncertainty in climate outcomes and uncertainty inother aspects of the application.
• It would be useful to develop a categorization of variables according todemonstrated performance, and of types of forcing which can be more or
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less accurately emulated (including greenhouse gases, aerosols and land use).
• It would be valuable to evaluate methods according to their ability toemulate the difference between two forcing scenarios, where thisdifference has been demonstrated to matter to outcomes of interest.
3.2 What are current and near-future needs from impact and IAM communities (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties and measures of reliability)?
The users of PS/E approaches and results are diverse. • This group can be coarsely divided into “clients”, i.e., policy advisers at
international or national levels and technical advisers at regional or localscales on the one hand, and “hands-on” users on the other, i.e., modelersof integrated or sectoral coarse-scale impacts, economic modelers,modelers of detailed processes, and decision support analysts in the IAMor IAV communities working at scales ranging from global, throughregional to local.
• PS/E approaches are attractive for a variety of reasons, including theproduction of easily available climate information in accessible formats,their ability to produce a range of different outcomes and somecharacterization of scenario and model uncertainty, and theirconduciveness to exploring policy questions (impacts, avoided impacts,effects of choosing specific targets).
• Needs vary between the two groups, but share a common core: a subsetof variables relevant to impacts, coherence across space and time (i.e.,the preservation of spatial and temporal correlations within each variableand of the covariances between different variables), information not onlyabout the projected forced changes but also about future characteristics ofvariability and extremes, and in some cases fully probabilisticcharacterization of future changes.
There is a need to conduct a comprehensive survey of variables (both primary and derived), spatial and time scales of interest to different user groups, and acceptable levels of accuracy.
• An initial table of variables important to impacts research was produced ina breakout group, and plans were made to extend it through formalsurveys conducted either within the on-going activities of the NationalClimate Assessment or other international projects (AVOID2, for example).
• Desirable extensions to a table of needed variables include anassessment of the ability of current emulation methods to provide theinformation, an assessment of the confidence in climate models’ ability to
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simulate the same quantity, a specification of the type of forcing/scenario under which the results could be more or less trusted, and a list of methodological issues that are relevant to individual variables (e.g., non-linear behavior, different time scales, different components interacting to produce the change, etc.).
Work is needed on characterizing the sensitivity of projected impacts to variations in both the input climate information and the choice of impacts models.
• Understanding sensitivities of impacts to changes in different variables, including non-climate factors, can help prioritize variables for emulation, and help define the desired accuracy and time/space resolution of emulation.
3.3 What is the outlook for progress in areas that do not yet work well? What new ESM simulations would be useful?
A systematic review of approaches to emulation is needed.
• A review of current approaches was planned that would catalogue different methods, including naive pattern scaling, the use of alternative scaling variables (in place of global mean warming), response-function methods and complex statistical emulators. It would also identify which variables have been made the object of emulation in addition to the commonly treated average temperature and precipitation (e.g., extremes, sea level rise) and review methods of PS/E evaluation.
A coordinated effort to evaluate alternative methods should be undertaken.
• A set of evaluation benchmarks should be established that would allow comparison of alternative approaches, or a robust assessment of the “fitness-for-purpose” of a given solution.
• A group of participants showed interest in leading such an effort. This group would limit its focus to answering statistically defined questions about the size of the error of the emulation compared to the original model output emulated, and how that compares for example to the multi-model spread in the same output.
• In order to achieve effective evaluation, it will be necessary for Earth System Modelling groups to run a wide range of emissions scenarios. This may be an ideal application for ESMs configured at relatively low resolution. "Perfect model" approaches might be useful as well. The larger and thornier question of “how good is good enough” for individual applications is much more challenging, and application-driven (as discussed briefly in section 3.2 below), but it should be a necessary conditions that the question be addressed by climate scientists before offering these methods for use to the IAV/IAM communities.
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• An understanding of the physical and dynamical processes behind the emergence of patterns, or their variability, should be at the basis of any development of pattern scaling and emulators, and their evaluation.
Improved methods are needed for representation of unforced internal variability at yearly, monthly and daily scales.
• Information on variability is required by the impacts community, but most PS/E methods address only climate means or, when providing measures of internal variability have not been fully verified. Similarly, few studies have evaluated PS/E for measures of climate extremes.
• These shortcomings of current PS/E approaches should be communicated to the research community.
Idealized climate model experiments are needed to facilitate improvement of PS/E methods.
• Such simulations would help the analysis of patterns of climate response to individual forcings other than well-mixed greenhouse gases (land-use, aerosols, other short-lived and regionally-specific forcings). Some of these simulations will likely be carried out by LUMIP and AerChemMIP.
• Other idealized experiments could assist in characterizing and understanding the evolution of patterns under wide forcing ranges (e.g., business-as-usual through aggressive mitigation at 2100), or under different rates of forcing change (including stabilization or decline of forcings).
• There is a need for a more comprehensive analysis of the role of non-linearities and differences in time scales, and a model intercomparison project addressing some of these needs is being proposed (NonlinMIP, P. Good).
3.4 How should emulation techniques be incorporated in integrated scenario development and in the planning of future climate model experiments?
Pattern scaling or model emulation has not yet been demonstrated to provide sufficiently accurate and complete information to meet the needs of IAM and IAV users for the main set of variables and time/space resolutions required. Therefore, it cannot yet be concluded that such techniques can be used to significantly reduce the number of GCM simulations needed for scenario-based research.
• Although PS/E approaches have been used in many IAM and IAV applications, as discussed in section 3.1 the accuracy of these approaches has generally not been formally demonstrated. It is possible that for some limited IAM/IAV applications current approaches are
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sufficient (if undemonstrated); however it is clear that the full suite of variables needed for impact assessment (see Appendix 3 for an initial list), at the necessary time and space resolution, cannot yet be successfully emulated.
Guidance on the use of PS/E approaches and results would be helpful.
• Guidance could include the production of good practice examples in addition to assessments of performance and errors and the compilation of a review of current approaches.
A systematic review of applications of emulation methods to impact and IAM studies is needed.
• A review of current applications of emulation was planned that would catalogue different uses, emulation methods and emulated variables.
4. Next steps Discussions throughout the meeting and in the final wrap-up session led to a number of planned or desirable follow-up steps. We summarize them here, separated into short- and longer-term activities. It was also noted that follow-up on this topic could leverage a number of international activities (e.g., CMIP6, WCRP- WGRC/CORDEX, GFCS, IAMC, PROVIA, TGICA) which should be kept in mind when pursuing these objectives. In the short term, besides the production of this meeting report:
• Produce peer reviewed papers describing the state-of-the-art in PS/E approaches, methodological needs, user needs and applications;
• An AGU session is being organized on Pattern scaling and emulation techniques and their relevance for the scenario process;
• Communicate results of this meeting to the scenario process through planned sessions at a series of meetings at Breckenridge (CESM), Snowmass (IAM community), and Aspen (ScenarioMIP, LUMIP, AerChemMIP);
• Develop a proposal for experiments that would test the ability of PS/E to replace need for ESMs, for possible inclusion in other MIPs (ScenarioMIP, LUMIP, AerChemMIP, NonlinMIP).
In the longer term:
• Catalogue methods and software tools for pattern scaling/emulation; • Develop benchmark tests and apply them to evaluate PS methods;
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• Survey IAM, IAV, and decision-support communities for better assessment of user needs;
• Develop guidance for users of pattern scaling methods; • Assess sensitivity of impacts to climate outcomes vs other factors; • Possibly organize a follow up meeting on PS/E approaches.
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Appendix 1 Participants
Stacey Alexeeff NCAR IMAGe Aavudai Anandhi Kansas State University Roger Barry University of Colorado, Boulder Adeline Bichet University of Toronto Franco Biondi Harvard Forest Kimberly Brumble Indiana University, Bloomington Melissa Bukovsky NCAR IMAGe Kate Calvin JGCRI/PNNL Tim Carter Finnish Environment Institute (SYKE), Helsinki Stefano Castruccio King Abdullah University of Science and Technology Peter Challenor University of Exeter Won Chang The Pennsylvania State University Jens Christensen Danish Meteorological Institute Ole Bøssing Christensen Danish Meteorological Institute
Jean-Louis Dufresne CNRS-UMPC LMD/IPSL, France
Veronika Eyring German Aerospace Center (DLR), Germany
Katja Frieler Carlos Gaitan Diego Garzena Peter Good Dorit Hammerling Dehlia Hannah Glen Harris Corinne Hartin Birgit Hassler Nadja Herger Phil Holden Yasuhiro Ishizaki
Postdam Institute for Climate Impact Research (PIK) University of Oklahoma & NOAA-GFDL University of Turin/ NCAR MetOffice, Exeter NCAR IMAGe University of Wisconsin-Milwaukee MetOffice, Hadley Centre JGCRI/PNNL CIRES/NOAA, Boulder ETH, Zurich Open University, UK National Institute for Environmental Studies (NIES), Japan
Gardar Johannesson Lawrence Livermore National Laboratory Andrew Jones Lawrence Berkeley National Laboratory Baird Langenbrunner UCLA Nathan Lenssen NCAR IMAGe Jared Lewis Bodeker Scientific, New Zealand
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Ana Lopez Oxford University Jason Lowe MetOffice, Exeter Vyacheslav Lyubchich University of Waterloo
Linda Mearns NCAR IMAGe Jerry Meehl NCAR CGD Erwan Monier Massachusetts Institute of Technology Richard Moss JCGRI/PNNL/UMD James Murphy MetOffice, Exeter Robert Nicholas The Pennsylvania State University Doug Nychka NCAR IMAGe Brian O'Neill NCAR CGD Tim Osborn University of East Anglia, UK Andrew Poppick University of Chicago Benjamin Quesada Karlsruhe Institute of Technology, Germany Joeri Rogelj ETH, Zurich Steve Sain NCAR IMAGe Nathalie Schaller University of Oxford Adam Schlosser Massachusetts Institute of Technology Hideo Shiogama National Institute for Environmental Studies (NIES), Japan
Kaoru Tachiiri Japan Agency for Marine-earth Science and Technology (JAMSTEC)
Karl Taylor PCMDI, LLNL Claudia Tebaldi NCAR CGD
Junichi Tsutsui Central Research Institute of Electric Power Industry (CRIEPI), Japan
Rachel Warren University of East Anglia, UK Ian Watterson CSIRO Marine and Atmospheric Research Tom Wigley NCAR/ University of Adelaide Daniel Williamson University of Exeter, UK
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Appendix 2: Meeting Agenda The meeting agenda can also be found at https://www2.image.ucar.edu/event/PS2014/agenda Talks are available at https://www2.image.ucar.edu/event/PS2014/archive Pattern Scaling, Climate Model Emulators and their Application to
the New Scenario Process
Agenda Day 1 (April 23) Welcome and Introductions 9:00-‐9:10 Welcome
Al Kellie, CISL; Bill Large, CGD 9:10-‐9:30 Introduction/Motivation/Goals
Claudia Tebaldi & Brian O’Neill 9:30-‐10:00 Overview: New Scenario Process and the need for Pattern
Scaling/Emulators Brian O’Neill
10:00-‐10:30 Discussion 10:30-‐11:00 Break
Pattern Scaling/Emulation Methodology I 11:00-‐11:20 Overview: Pattern Scaling/Emulation Methodology
James Murphy & Claudia Tebaldi 11:20-‐11:30 Discussion 11:30-‐11:50 Why patterns evolve and what we might do about it
Peter Good 11:50-‐12:10 Emission scenario dependency of scaling patterns and linear additivity
of climate forcing-‐response relationship Hideo Shiogama
12:10-‐12:30 Development of probabilistic projections based on climate model ensembles using scaling Ian Watterson
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12:30-‐1:00 Discussion 1:00-‐2:00 Lunch Break
User Needs I
2:00-‐2:20 Overview: User needs – IAM and Impact modelers Tim Carter & Brian O’Neill
2:20-‐2:30 Discussion 2:30-‐2:50 Pattern scaling in integrated assessments: utility, futility and
opportunity Adam Schlosser
2:50-‐3:10 Closing the loop: The need for scaling Katja Frieler
3:10-‐3:30 Pattern scaling using ClimGen: user needs, changing precipitation variability and interaction between global and regional responses Tim Osborn
3:30-‐4:00 Discussion 4:00-‐4:30 Break 4:30-‐5:00 Day wrap-‐up. Poster session introduction
Reception, Poster Session and Keynote Presentation 5:00-‐6:00 Reception + Poster session 6:00-‐6:30 Evening Presentation: Accounting for aerosol forcing in pattern scaling
Tom Wigley 6:30-‐7:30 Q&A, continued reception & poster session
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Day 2 (April 24) Pattern Scaling/Emulation Methodology II 9:00-‐9:15 Using perturbed parameter ensembles, emulation and scaling
techniques to improve sampling of uncertainties in regional climate change Glen Harris
9:15-‐9:30 Aspects of the linearity in the climate response to idealised single forcing GCM simulations Nathalie Schaller
9:30-‐9:45 Sea surface temperatures response to anthropogenic forcing: evaluation of the methods Adeline Bichet
9:45-‐10:00 PLASIM-‐ENTSem: a spatio-‐temporal climate emulator for impacts assessment Phil Holden
10:00-‐10:30 Discussion 10:30-‐11:00 Break User Needs II 11:00-‐11:20 Scaling and spatial correlation of regional temperature and
precipitation change over Europe Ole Bøssing Christensen and Jens Christensen
11:20-‐11:40 Pattern scaling changes in sea-‐level: Challenge and approaches Jason Lowe
11:40-‐12:00 Robustness of pattern scaled climate change scenarios for adaptation decision support Ana Lopez
12:00-‐12:30 Discussion 12:30-‐1:30 Lunch Break Break-‐out Groups 1:30-‐4:00 Group 1 and 2 will address methodological issues:
Chairs: Jens Christensen and James Murphy. Rapporteurs: Ana Lopez and Erwan Monier Group 3 will address user needs: Chair: Richard Moss. Rapporteur: Rachel Warren Questions to address include: • To what extent does pattern scaling or other forms of emulators
work well (which variables, at what geographic and time
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resolution, for what time horizons, with what uncertainties) and what is the outlook for progress in areas that do not yet work well?
• What are current and near-‐future needs from impact and IAM communities (which variables, at what geographic and time resolution, for what time horizons, with what uncertainties and measures of reliability)?
• How should emulation techniques be incorporated in integrated scenario development and in the planning of future climate model experiments?
4:00-‐4:30 Break 4:30-‐6:00 Report back to plenary Day 3 (April 25) Synthesis and Discussion
9:00-‐9:30 Pattern scaling/emulation methodology 9:30-‐10:00 User needs 10:00-‐10:30 Scenario process 10:30-‐11:00 Break Wrap-‐up, Next Steps 11:00-‐12:30 Forward Looking:
1) CMIP6 perspective 2) Perspective from specific MIPs 3) Following-‐up on research agenda 4) Plans for producing paper
5) Other topics/outcomes Adjourn
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Appendix 3: Pattern scaled or emulated variables of potential interest to users. This list is based on presentations in the workshop and expert judgment. Note that entries are indicative, and are not intended to cover all possible user needs. Primary variables
Impact model Resolution PS/Emulated Climate Change
Spatial Temporal Temporal Resolution
Other information
Tmax, Tmin, Tmean
Grid Daily Monthly/seasonal Variability change
Precipitation Grid Daily Monthly/seasonal Variability change
Solar radiation
Grid Daily Monthly/seasonal Variability change
Humidity Grid Daily Monthly/seasonal Variability change
Wind Grid Daily Monthly/seasonal Variability change
SST Grid Daily/Monthly Monthly/seasonal Variability change
Salinity Grid/depths Annual? Seasonal/annual Depths
Sea level Coastline; location
Period-mean; storm surge
Annual
……..
22
Derived variables
Impact model resolution PS/Emulated Climate Change
Spatial Temporal Temporal Resolution
Other information
SPI6/12; PDSI
Grid Annual Monthly/seasonal
PET Grid Seasonal Monthly/seasonal
HDD Grid/regions Annual/seasonal Monthly/seasonal
CDD Grid/regions Annual/seasonal Monthly/seasonal
Runoff Grid/regions Annual/seasonal Monthly/seasonal
