StrateGieS
REVOLUTION IN CLIMATE PREDICTION IS
BOTH NECESSARY AND POSSIBLEa Declaration at the World Modelling
Summit for Climate Prediction
BY J. SHUKLA, R. HAGEDORN, B. HOSKINS, J. KINTER, J. MAROTZKE, M. MILLER, T. N. PALMER, AND J. SLINGO

Thanks to the assessments by the IPCC, the world
recognizes that humans are contributing to a
global climate change that is among the mostimportant threats we face. The climate science community now faces a major new challenge of providing
society with reliable regional climate predictions.
Adapting to climate change while pursuing sustainable development will require accurate and reliablepredictions of changes in regional weather systems,
especially extremes. Investments of trillions of dollars worldwide may be necessary to avoid the worst
consequences of climate change. Yet, current climate
models have serious limitations in simulating regional weather variations and therefore in generating
the requisite information about regional changes
with a level of confidence required by society. Useof high-resolution regional models to downscaleregional climate change is questionable if the global
models from which lateral boundary conditions areprescribed are not realistic. In short, the limitationsof current modeling methods are forcing the climate

AFFILIATIONS: S HUKLA—George Mason University, Institute of Global Environment and Society, Calverton, Maryland;
HAGEDORN, MILLER, AND PALMER—European Centre for MediumRange Weather Forecasts, Reading, England; HOSKINS —Grantham
Institute, Imperial College and Department of Meteorology,
University of Reading, Reading, England; KINTER—Center for
Ocean–Land–Atmosphere Studies, Calverton, Maryland;
MAROTZKE —Max Planck Institute for Meteorology, Hamburg,Germany; S LINGO —The Walker Institute, University of Reading,Reading, England
CORRESPONDING AUTHOR: J. Shukla, Distinguished University Professor, George Mason University/President, Institute of
Global Environment & Society, 4041 Powder Mill Rd., Suite 302,Calverton, MD 20705-3106
E-mail: shukla@cola.iges.org

DOI:10.1175/2008BAMS2759.1©2009 American Meteorological Society

aMerICaN MeTeOrOLOGICaL SOCIeTy

science community to consider fundamental changes
in its approach to meeting the urgent demands of aconcerned society.
In this context, the World Climate Research Programme (WCRP) held a World Modelling Summitfor Climate Prediction on 6–9 May 2008 in Reading,England, to develop a strategy to revolutionize prediction of the climate to address global climate change,
particularly at regional scales.
The primary emphasis of the summit was on thesimulation and prediction of the physical climatesystem. Since advances in climate modeling and prediction build strongly on those in weather forecasting,and because the inclusion of biogeochemical cycles
in longer-term projections of climate change requires
improved representations of the physical system, thesummit was cosponsored by the World Weather Research Programme (WWRP) and the International
Geosphere–Biosphere Programme (IGBP).
The deliberations by about 150 scientists from anumber of disciplines embarked from the notion ofclimate and weather as a seamless problem. As such,use of numerical weather forecasting methods canhelp quantify and reduce uncertainty in climate predictions. Taking advantage of this experience to meetthe demands of regional climate change information
will require confronting the increasing challenges ofresolution, complexity, length and numbers of simulations, and assimilating observational data.
The Japanese experience of simulating global
climate with horizontal resolution of 3.5–10 km
has established the basis for wider experimentation
with—and application of—very high-resolution models. Thus, the experts at the summit concluded thatclimate modeling will need—and is ready—to moveto fundamentally new high-resolution approaches tocapitalize on the seamlessness of the weather–climatecontinuum.
This impending revolution raises issues of parameterization, regional modeling, and the balances
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Summit Statement: The Climate Prediction Project
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Considerably improved predictions of the changes in thestatistics of regional climate, especially of extreme events andhigh-impact weather, are required to assess the impacts of climate change and variations, and to develop adaptive strategies
to ameliorate their effects on water resources, food security,energy, transport, coastal integrity, environment, and health.
Investing today in climate science will lead to significantly reduced costs of coping with the consequences of climate change
tomorrow.
Despite tremendous progress in climate modeling and thecapability of high-end computers in the past 30 years, ourability to provide robust estimates of the risk to society,particularly from possible catastrophic changes in regional
climate, is constrained by limitations in computer power andscientific understanding. There is also an urgent need to build
a global scientific workforce that can provide the intellectual
power required to address the scientific challenges of predicting climate change and assessing its impacts with the level ofconfidence required by society.
Climate prediction is among the most computationally demanding problems in science. It is both necessary and possible torevolutionize regional climate prediction—necessary becauseof the challenges posed by the changing climate, and possible bybuilding on the past accomplishments of prediction of weather
and climate. However, neither the necessary scientific expertise nor the computational capability is available in any singlenation. A comprehensive international effort is essential.
The Summit strongly endorsed the initiation of a Climate Prediction Project coordinated by the World Climate Research
Programme, in collaboration with the World Weather Research
Programme and the International Geosphere–Biosphere Programme, and involving the national weather and climate centers
as well as the wider research community. The goal of the projectis to provide improved global climate information to underpin
global mitigation negotiations and for regional adaptation anddecision making in the twenty-first century.
The success of the Climate Prediction Project will criticallydepend on significantly enhancing the capacity of the world’s
existing weather and climate research centers for predictionof weather and climate variations, including the prediction ofchanges in the probability of occurrence of regional high-impact
weather. This is particularly true for the developing countries
whose national capabilities need to be increased substantially.
An important and urgent initiative of the Climate Prediction
Project will be a world climate research facility for climate
prediction that will enable the national centers to accelerate
progress in improving operational climate prediction at all timescales, especially at decadal to multidecadal lead times. This
will be achieved by increasing understanding of the climate
system, building global capacity, developing a trained scientificworkforce, and engaging the global user community.
The central component of this world facility will be one ormore dedicated high-end computing facilities that will enable climate prediction at the model resolutions and levels ofcomplexity considered essential for the most advanced andreliable representations of the climate system that technology

176 |February 2009and our scientific understanding of the problem can deliver.
This computing capability acceleration, leading to systems
at least a thousand times more powerful than the currently
available computers, will permit scientists to strive towardkilometer-scale modeling of the global climate system, which is
crucial to more reliable prediction of the change of convective
precipitation, especially in the tropics.
8. Access to significantly increased computing capacity will enable scientists across the world to advance understanding
and representation of the physical processes responsible forclimate variability and predictability, and provide a quantum
leap in the exploration of the limits in our ability to reliably
predict climate with a level of detail and complexity that is notpossible now. It will also facilitate exploration of biogeochemical processes and feedbacks that currently represent a major
impediment to our ability to make reliable climate projections
for the twenty-first century.
9. Sustained, long-term, global observations are essential to initialize, constrain, and evaluate the models. Well-documented andsustained model data archives are also essential for enabling acomprehensive assessment of climate predictions. An importantcomponent of the Climate Prediction Project will therefore bean accessible archive of observations and model data with appropriate user interface and knowledge-discovery tools.
10. To estimate the quality of a climate prediction requires anassessment of how accurately we know and understand thecurrent state of natural climate variability, with which anthropogenic climate change interacts. All aspects of estimating theuncertainty in climate predictions pose an extreme burden on
computing resources, on the availability of observational data,and on the need for attribution studies. The Climate PredictionProject will enable the climate research community to makebetter estimates of model uncertainties and assess how they
limit the skill of climate predictions.
11. Advances in climate prediction will require close collaboration between the weather and climate-prediction researchcommunities. It is essential that decadal and multidecadal
climate prediction models accurately simulate the key modesof natural variability on the seasonal and subseasonal timescales. Climate models will need to be tested in subseasonaland multiseasonal prediction mode also including use of theexisting and improved data assimilation and ensemble prediction systems. This synergy between the weather and climate
prediction efforts will further motivate the development of
seamless prediction systems.
12. The Climate Prediction Project will help humanity’s efforts
to cope with the consequences of climate change. Because
the intellectual challenge is so large, there is great excitement
within the scientific community, especially among the young
who want to contribute to make the world a better place. It
is imperative that the world’s corporations, foundations, andgovernments embrace the Climate Prediction Project. This
project will help sustain the excitement of the young generation, build global capacity (especially in developing countries),and prepare humanity to adapt to—and mitigate the consequences of—climate change.

required and/or implied between the use of available
computing power for higher resolution on the one
hand and the inclusion of complex biogeochemical
processes on the other.
Much higher resolution of the major model components (e.g., atmosphere, ocean, and land) is a fundamental prerequisite for a more realistic representationof the climate system and more relevant predictions(e.g., extremes, convection, and tropical variability),
and thus regional and local applications. Improving
the basic model physics is also important, whether
through observationally inspired development, muchhigher resolutions, or stochastic concepts. Amongthe many advantages of very high-resolution studies
is the improvement of the prediction of the tropicalclimate and its variability. This would dramatically
improve predictions for some of the most populated
and poorest areas of the globe.
To achieve such advances, summit discussions
converged on a proposal for a world Climate Prediction Project and associated climate research facility(see sidebar). The overwhelming view of the group
was that the project must have a strong focus on thescientific aspects of climate prediction, and the facility should have the character of a scientific enterprise.
Such a project could dramatically accelerate progressby focusing on experiments that are two or more generations ahead of national efforts and that cannot be
carried out by individual centers. Among the featuresof the project would be:• Hardware—Flexible hardware that can support•

research on developing models with much higher
resolution is needed. The cost and power requirements for a multipetaflop climate computer are
such that an “off the shelf” supercomputer could
be sufficient for the community’s needs. On theother hand, the use of probabilistic chips now indevelopment might introduce stochastic processes
into models at the chip level. A radical new design
based on cell phone chip technology may also beof interest for climate modeling. These intriguing
developments should be monitored, but tailoring aspecific machine for a particular class of algorithm
should not be emphasized, because the development cost is very high.
Software—Because supercomputers of the next
generation will contain millions of processors, newmethods of highly parallel programming will berequired. The project will require more software
engineers in the field.

AMERICAN METEOROLOGICAL SOCIETY• Models—During the past 30 years, computational

power has increased by a factor of 1 million, but theresolution of climate models has increased only bya factor of two. There are atmospheric GCMs currently in use at 50-km resolution that can run 1,000times faster than real time. With the existing andprojected technology, models with 25-km resolution
are within reach in the next 3 years or so. However,multidecadal climate simulation with global nonhydrostatic cloud system resolving models of theatmosphere using 2–5-km grids (with comparable
resolution in the ocean) are not likely to be attained
within the next 5 years. As models reach 2–5-kmscale resolutions, they will generate aggregate
output data on the order of hundreds of exabytes,
stored at widely distributed modeling centers.

The summit tried to identify issues that required
computing resources significantly beyond what iscurrently available. These grand (computational)
challenges can be grouped into the following areas:• Process-based model evaluation—The effects of•••using different cloud parameterizations and varying the parameters in those parameterizations
should be evaluated not only against global-scalesatellite data, but also against what is known aboutbasic cloud processes. High-resolution model experiments are required for developing and testing
parameterizations.
Data assimilation, analysis, and initialization—The methods of data assimilation andinitialization, which have been crucial for thesuccess of numerical weather prediction, must
be extended to coupled models to obtain physical consistency. Observing system experimentsare required to develop rational strategies fordefining the most effective and efficient data
streams. Model bias must be reduced and corrected in assimilation.
Detection and attribution of climate events—Do
climate models correctly simulate major climate
signals, and if not, how much is due to inherent unpredictability rather than model deficiencies? The
mechanisms for observed climate signals should
be well understood, and metrics that quantify
the fidelity of climate prediction models should
be defined, so that we can assess the reliability ofclimate predictions.
Ensembles—Large ensembles of high-resolution
simulations are required for the quantification ofFebruary 2009| 177

forecast skill. This computing challenge is particularly acute at the decadal prediction scale.
The challenge of providing improved information on extremes and high-impact climate
and weather variations requires a concerted,international response to significantly increasedmodel resolution. While the proposal for a Climate
Prediction Project intends to expedite computing capabilities of 2–3 orders of magnitude above
what is currently available nationally, the summit
underscored strong support for national centersand for maintaining model diversity—a healthyelement of competition.
A global facility could provide substantial
benefits to national activities by developing thenext-generation numerical cores and by providing a significantly enhanced computing capacity
to scientists around the world to perform climate
predictions with a range of models at resolutions
that are not possible using national facilities. A
global facility can also provide a focal point for

178 |February 2009

advanced computational science and support a
program of training and capacity building fordeveloping countries.
There was some limited discussion on how
to obtain resources for the project. The private
sector and nonprofit foundations were proposed
as possible sources. The importance of stressing
the global, humanitarian aspects was noted when
making the case for new and substantial investment. Based on the summit deliberations, thetheme leaders (B. Hoskins, J. Kinter, J. Marotzke,
M. Miller, and J. Slingo), with substantial input
from R. Hagedorn, T. Palmer, J. Shukla, and othermembers of the organizing committee (M. Beland,
C. Bitz, G. Brunet, V. Eyring, C. Jakob, H. LeTreut,T. Matsuno, G. Meehl, J. Mitchell, A. Navarra, C.
Nobre, V. Ramaswamy, D. Randall, and K. Trenberth), prepared a Summit Statement. To realize
the revolution in climate prediction that is bothnecessary and possible, the Summit Statement
proposes a Climate Prediction Project and a world
climate research facility (see sidebar).