Challenges and Social Learning at the Climate Science-Policy Interface

2014 ◽  
Vol 44 (5) ◽  
pp. 435-469 ◽  
Author(s):  
Nils Randlev Hundebøl ◽  
Kristian H. Nielsen
Keyword(s):  
Model Evaluation ◽  
Policy Making ◽  
General Circulation ◽  
Climate Modeling ◽  
Climate Science ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Social Experiment ◽  
Science And Politics ◽  
Science Policy Interface

The Model Evaluation Consortium for Climate Assessment (MECCA) from 1990–95 was an international consortium involving industry partners as well as research institutions in the dual attempt to advance basic science and to impact public and industrial policy-making. Led by the Electric Power Research Institute (EPRI) and the University Corporation for Atmospheric Research (UCAR), MECCA sponsored many numerical experiments on a CRAY-YMP supercomputer dedicated to climate modeling and produced information material with particular emphasis on assessing uncertainties involved in climate modeling for a range of potential users of climate predictions. As it turned out, it was difficult to align the goals of the climate modeling community with those of the climate impacts assessment community. Modelers primarily wanted to advance state-of-the-art General Circulation Models (GCMs). Impact analysts were interested in model evaluation in order to improve confidence levels in impacts predictions. An unconventional organizational scheme in climate science, MECCA also was a “social experiment” in bringing together diverse communities and overcoming mutual skepticism. Climate scientists were skeptical about the policy-making ambitions of MECCA and about industry’s motivation for getting involved in climate science, while industry doubted whether the scientists really made efforts to direct their work toward policy-relevant research questions. MECCA taught some scientists key lessons about the interactions between science and politics, but MECCA as such provided no effective answers to some of the basic skepticisms in the climate regime and consequently failed to reduce uncertainty on climate change issues.

scholarly journals The cloud–aerosol–radiation (CAR) ensemble modeling system

2013 ◽  
Vol 13 (16) ◽  
pp. 8335-8364 ◽  
Author(s):  
X.-Z. Liang ◽  
F. Zhang
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Climate Model ◽  
Climate Modeling ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Sensitivity Analyses ◽  
General Description ◽  
Ensemble Modeling ◽  
Uncertainty Range

Abstract. A cloud–aerosol–radiation (CAR) ensemble modeling system has been developed to incorporate the largest choices of alternate parameterizations for cloud properties (cover, water, radius, optics, geometry), aerosol properties (type, profile, optics), radiation transfers (solar, infrared), and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world's leading general circulation models (GCMs). CAR provides a unique framework to determine (via intercomparison across all schemes), reduce (via optimized ensemble simulations), and attribute specific key factors for (via physical process sensitivity analyses) the model discrepancies and uncertainties in representing greenhouse gas, aerosol, and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud–aerosol–radiation interactions. For demonstration purposes, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol, and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.

scholarly journals Cloud-Aerosol-Radiation (CAR) ensemble modeling system

2013 ◽  
Vol 13 (4) ◽  
pp. 10193-10261 ◽  
Author(s):  
X.-Z. Liang ◽  
F. Zhang
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Climate Model ◽  
Climate Modeling ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Sensitivity Analyses ◽  
General Description ◽  
Ensemble Modeling ◽  
Uncertainty Range

Abstract. A Cloud-Aerosol-Radiation (CAR) ensemble modeling system has been developed to incorporate the largest choices of alternative parameterizations for cloud properties (cover, water, radius, optics, geometry), aerosol properties (type, profile, optics), radiation transfers (solar, infrared), and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world leading general circulation models (GCMs). The CAR provides a unique framework to determine (via intercomparison across all schemes), reduce (via optimized ensemble simulations), and attribute specific key factors for (via physical process sensitivity analyses) the model discrepancies and uncertainties in representing greenhouse gas, aerosol and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud-aerosol-radiation interactions. For demonstration purpose, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.

scholarly journals Coupled ice sheet–climate modeling under glacial and pre-industrial boundary conditions

2014 ◽  
Vol 10 (5) ◽  
pp. 1817-1836 ◽  
Author(s):  
F. A. Ziemen ◽  
C. B. Rodehacke ◽  
U. Mikolajewicz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Climate Modeling ◽  
Ice Sheets ◽  
Ice Sheet ◽  
General Circulation Models ◽  
Quasi Equilibrium ◽  
Ice Streams ◽  
Ice Stream ◽  
First Results

Abstract. In the standard Paleoclimate Modelling Intercomparison Project (PMIP) experiments, the Last Glacial Maximum (LGM) is modeled in quasi-equilibrium with atmosphere–ocean–vegetation general circulation models (AOVGCMs) with prescribed ice sheets. This can lead to inconsistencies between the modeled climate and ice sheets. One way to avoid this problem would be to model the ice sheets explicitly. Here, we present the first results from coupled ice sheet–climate simulations for the pre-industrial times and the LGM. Our setup consists of the AOVGCM ECHAM5/MPIOM/LPJ bidirectionally coupled with the Parallel Ice Sheet Model (PISM) covering the Northern Hemisphere. The results of the pre-industrial and LGM simulations agree reasonably well with reconstructions and observations. This shows that the model system adequately represents large, non-linear climate perturbations. A large part of the drainage of the ice sheets occurs in ice streams. Most modeled ice stream systems show recurring surges as internal oscillations. The Hudson Strait Ice Stream surges with an ice volume equivalent to about 5 m sea level and a recurrence interval of about 7000 yr. This is in agreement with basic expectations for Heinrich events. Under LGM boundary conditions, different ice sheet configurations imply different locations of deep water formation.

scholarly journals PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

scholarly journals Mathematics applied to the climate system: outstanding challenges and recent progress

2013 ◽  
Vol 371 (1991) ◽  
pp. 20120518 ◽  
Author(s):  
Paul D. Williams ◽  
Michael J. P. Cullen ◽  
Michael K. Davey ◽  
John M. Huthnance
Keyword(s):  
General Circulation ◽  
Recent Progress ◽  
Initial Conditions ◽  
Global Climate ◽  
Climate Science ◽  
General Circulation Models ◽  
Climate System ◽  
Future Research ◽  
Theme Issue ◽  
Physically Based

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions.

scholarly journals Boreal Summer Synoptic-Scale Waves over the Western North Pacific in Multimodel Simulations

2016 ◽  
Vol 29 (12) ◽  
pp. 4487-4508 ◽  
Author(s):  
Haikun Zhao ◽  
Xianan Jiang ◽  
Liguang Wu
Keyword(s):  
Spatial Pattern ◽  
North Pacific ◽  
General Circulation ◽  
Western North Pacific ◽  
Climate Model ◽  
Climate Modeling ◽  
Active Role ◽  
General Circulation Models ◽  
Boreal Summer ◽  
Synoptic Scale

During boreal summer, vigorous synoptic-scale wave (SSW) activity, often evident as southeast–northwest-oriented wave trains, prevails over the western North Pacific (WNP). In spite of their active role for regional weather and climate, modeling studies on SSWs are rather limited. In this study, a comprehensive survey on climate model capability in representing the WNP SSWs is conducted by analyzing simulations from 27 recent general circulation models (GCMs). Results suggest that it is challenging for GCMs to realistically represent the observed SSWs. Only 2 models out of the 27 GCMs generally well simulate both the intensity and spatial pattern of the observed SSW mode. Plausible key processes for realistic simulations of SSW activity are further explored. It is illustrated that GCM skill in representing the spatial pattern of the SSW is highly correlated to its skill in simulating the summer mean patterns of the low-level convergence associated with the WNP monsoon trough and conversion from eddy available potential energy (EAPE) to eddy kinetic energy (EKE). Meanwhile, simulated SSW intensity is found to be significantly correlated to the amplitude of 850-hPa vorticity, divergence, and conversion from EAPE to EKE over the WNP. The observed modulations of SSW activity by the Madden–Julian oscillation are able to be captured in several model simulations.

The Advent of Climate Science

2020 ◽  
Author(s):  
Deborah R. Coen
Keyword(s):  
Research Program ◽  
General Circulation ◽  
Modern Science ◽  
Climate Science ◽  
General Circulation Models ◽  
World War ◽  
The Past ◽  
Measurement And Analysis ◽  
History Of ◽  
Definition Of

The advent of climate science can be defined as the historical emergence of a research program to study climate according to a modern definition of climate. Climate in this sense: (1) refers not simply to the average state of the atmosphere but also to its variability; (2) is multiscalar, concerned with phenomena ranging from the very small and fast to the very large and slow; and (3) is understood to be influenced by the oceans, lithosphere, cryosphere, and biosphere. Most accounts of the history of climate science to date have focused on the development of computerized general circulation models since World War Two. However, following this definition, the advent of climate science occurred well before the computer age. This entry therefore seeks to dispel the image of climate science as a recent invention and as the preserve of an exclusive, North American elite. The historical roots of today’s knowledge of climate change stretch surprisingly far back into the past and clear across the world, though the geographic focus here is on Europe and North America. The modern science of climate emerged out of interactions between learned and vernacular knowledge traditions, and has simultaneously appropriated and undermined traditional and indigenous forms of climate knowledge. Important precedents emerged in the 17th and 18th centuries, and it was in the late 19th century that a modern science of climate coalesced into a coordinated research program in part through the unification of divergent knowledge traditions around standardized techniques of measurement and analysis.

Local Regimes of Atmospheric Variability: A Case Study of Southern California

2006 ◽  
Vol 19 (17) ◽  
pp. 4308-4325 ◽  
Author(s):  
Sebastien Conil ◽  
Alex Hall
Keyword(s):  
Spatial Structure ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Spatial Scales ◽  
Surface Wind ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Atmospheric Variability ◽  
Composite Surface

Abstract The primary regimes of local atmospheric variability are examined in a 6-km regional atmospheric model of the southern third of California, an area of significant land surface heterogeneity, intense topography, and climate diversity. The model was forced by reanalysis boundary conditions over the period 1995–2003. The region is approximately the same size as a typical grid box of the current generation of general circulation models used for global climate prediction and reanalysis product generation, and so can be thought of as a laboratory for the study of climate at spatial scales smaller than those resolved by global simulations and reanalysis products. It is found that the simulated circulation during the October–March wet season, when variability is most significant, can be understood through an objective classification technique in terms of three wind regimes. The composite surface wind patterns associated with these regimes exhibit significant spatial structure within the model domain, consistent with the complex topography of the region. These regimes also correspond nearly perfectly with the simulation’s highly structured patterns of variability in hydrology and temperature, and therefore are the main contributors to the local climate variability. The regimes are approximately equally likely to occur regardless of the phase of the classical large-scale modes of atmospheric variability prevailing in the Pacific–North American sector. The high degree of spatial structure of the local regimes and their tightly associated climate impacts, as well as their ambiguous relationship with the primary modes of large-scale variability, demonstrate that the local perspective offered by the high-resolution model is necessary to understand and predict the climate variations of the region.

scholarly journals PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment

2014 ◽  
Vol 7 (1) ◽  
pp. 433-451 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS (Planet Simulator coupled with the efficient numerical terrestrial scheme). Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and non-CO2 radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

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