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Summary
I
nformation about climate1 is used to make decisions every day. From farmers decid-
ing which crops to plant next season to mayors in large cities deciding how to pre-
pare for future heat waves, and from an insurance company assessing future flood
risks to a national security planner assessing future conflict risks from the impacts of
drought, users of climate information span a vast array of sectors in both the public
and private spheres. Each of these communities has different needs for climate data,
with different time horizons (see Box S.1) and different tolerances for uncertainty.
Over the next several decades, climate change and its myriad consequences will be
further unfolding and possibly accelerating, increasing the demand for climate infor-
mation. Society will need to respond and adapt to impacts, such as sea-level rise, a
seasonally ice-free Arctic, and large-scale ecosystem changes. Historical records are no
longer likely to be reliable predictors of future events; climate change will affect the
likelihood and severity of extreme weather and climate events, which are a leading
cause of economic and human losses with total losses in the hundreds of billions of
dollars over the past few decades.2
Computer models that simulate the climate are an integral part of providing climate
information, in particular for future changes in the climate. Overall, climate modeling
has made enormous progress in the past several decades, but meeting the informa-
tion needs of users will require further advances in the coming decades.
In an effort to improve the United States’ capabilities to simulate present and future
climate on local to global scales and at decadal to centennial time scales, the National
Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space
Administration, the Department of Energy, the National Science Foundation, and the
intelligence community requested that the National Research Council (NRC) produce a
strategic framework to guide progress in the nation’s climate modeling enterprise over
the next 10-20 years. In response, the NRC appointed the Committee on a National
Strategy for Advancing Climate Modeling with the task to engage key stakeholders in
1 Climate is conventionally defined as the long-term statistics of the weather (e.g., temperature, precipi-
tation, and other meteorological conditions) that characteristically prevail in a particular region.
2 Total losses from weather- and climate-related disasters are estimated to exceed $700 billion for the
time period of 1980-2009 and to exceed $50 billion in 2011 alone from the more than 14 weather- and
climate-related disasters in that year. See http://www.noaa.gov/extreme2011 (accessed October 11, 2012).
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BOX S.1 INFORMATION FROM CLIMATE MODELS
Climate models skillfully reproduce important, global- to continental-scale features of the
present climate, including the simulated seasonal-mean surface air temperature (within 3°C of
observed [IPCC, 2007c], compared to an annual cycle that can exceed 50°C in places), the simu-
lated seasonal-mean precipitation (typical errors are 50 percent or less on regional scales of 1,000
km or larger that are well resolved by these models [Pincus et al., 2008]), and representations of
major climate features such as major ocean current systems like the Gulf Stream (IPCC, 2007c) or
the swings in Pacific sea-surface temperature, winds, and rainfall associated with El Niño (Achuta-
Rao and Sperber, 2006; Neale et al., 2008). Climate modeling also delivers useful forecasts for
some phenomena from a month to several seasons ahead, such as seasonal flood risks (Figure 1).
FIGURE 1 Climate models can deliver useful forecasts for some phenomena a month to several seasons
ahead, such as this spring flood risk outlook from NOAA’s National Weather Service for 2011. See Chapter
1 for more details. SOURCE: http://www.noaa.gov/extreme2011/mississippi_flood.html (accessed October
11, 2012).
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BOX S-1 CONTINUED
Beyond these advances, however, the climate modeling community aspires to make sub-
stantial further progress in the quality of climate projections, especially on regional space scales
and decadal time scales, to deliver the types of climate projections with sufficient resolution and
accuracy needed by users. For example, Figure 2 shows projected changes to water runoff for
later this century.
FIGURE 2 Longer-time-scale climate projections can assist in long-term planning. The figure shows pro-
jected changes in annual average runoff by the middle of the 21st century. See Chapter 1 for more details.
SOURCE: USGCRP, 2009.
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a discussion of the status and future of climate modeling in the United States over the
next decade and beyond; to describe the existing landscape of domestic and interna-
tional climate modeling efforts; to discuss, in broad terms, the observational, basic, and
applied research, infrastructure, and other requirements of current and possible future
climate modeling efforts; and to provide conclusions and/or recommendations for de-
veloping a comprehensive and integrated national strategy for climate modeling over
the next decade and beyond (see Appendix A for the statement of task and Box S.2 for
a description of the committee’s activities).
A NATIONAL STRATEGY FOR ADVANCING CLIMATE MODELING
The U.S. climate modeling community is diverse and contains several large global cli-
mate modeling efforts and many smaller groups running regional climate models. As
a critical step toward making more rapid, efficient, and coordinated progress, the com-
mittee envisions an evolutionary change in U.S. climate modeling institutions away
from developing multiple completely independent models toward a collaborative ap-
proach. A collaborative approach does not mean only one center of modeling; rather it
means that different groups pursue different niches or methodologies where scientifi-
cally justified, but within a single common modeling framework in which software,
data standards and tools, and even model components are shared by all major model-
ing groups nationwide. An overarching thread of the committee’s vision is to promote
unification of the decentralized U.S. climate modeling enterprise—across modeling
efforts, across a hierarchy of model types, across modeling communities focused on
different space and time scales, and across model developers and model output users.
BOX S.2 THE COMMITTEE’S REPORT PROCESS
The committee held five information-gathering meetings over the course of a year, including
a large community workshop, to interact with a range of stakeholders from government labs,
federal agencies, academic institutions, international organizations, and the broad user com-
munity. The committee examined previous reports on how to improve climate modeling in the
United States and interviewed key officials and scientists (see Appendix B for a complete list)
to help draw lessons from these reports. The charge to the committee emphasized decadal to
centennial time scales, but because of the overlap of issues between decadal and intraseasonal
to interannual (ISI) time scales, as well as the potential benefits of testing climate models at
shorter time scales, the committee believed it was important to extend the focus of the report
to shorter time scales, including ISI time scales.
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FIGURE S.1 Driven by the growing need for climate information and the coming transition to radi-
cally new computing hardware, a new generation of climate models will be needed to address a wide
spectrum of climate information needs. A national strategy consisting of four key unifying elements and
several other recommendations can help to achieve this vision.
The committee recommends a national strategy for advancing the climate modeling
enterprise in the next two decades, consisting of four main new components and five
supporting elements that, while less novel, are equally important (Figure S.1). The na-
tion should
1. Evolve to a common national software infrastructure that supports a diverse
hierarchy of different models for different purposes, and which supports a
vigorous research program aimed at improving the performance of climate
models on extreme-scale computing architectures;
2. Convene an annual climate modeling forum that promotes tighter coordina-
tion and more consistent evaluation of U.S. regional and global models, and
helps knit together model development and user communities;
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3. Nurture a unified weather-climate modeling effort that better exploits the
synergies between weather forecasting, data assimilation, and climate model-
ing; and
4. Develop training, accreditation, and continuing education for “climate inter-
preters” who will act as a two-way interface between modeling advances and
diverse user needs.
At the same time, the nation should nurture and enhance ongoing efforts to
5. Sustain the availability of state-of-the-art computing systems for climate
modeling;
6. Continue to contribute to a strong international climate observing system ca-
pable of comprehensively characterizing long-term climate trends and climate
variability;
7. Develop a training and reward system that entices the most talented com-
puter and climate scientists into climate model development;
8. Enhance the national and international information technology (IT) infrastruc-
ture that supports climate modeling data sharing and distribution; and
9. Pursue advances in climate science and uncertainty research.
The elements of this strategy are described in more detail below. If adopted, this strat-
egy provides a path for the United States to move forward into the next generation of
climate models to provide the best possible climate information for the nation.
ELEMENTS OF A NATIONAL STRATEGY FOR ADVANCING CLIMATE MODELING
Evolve to Shared Software Infrastructure
The entire climate modeling enterprise is computationally intensive. Over the past 15
years, major climate modeling groups have been forced to devote increasing attention
to software engineering. One catalyst was a disruptive hardware transition in the late
1990s from vector to parallel supercomputing. It was viewed with trepidation but the
climate modeling community adapted well, in part by moving toward common soft-
ware infrastructure for basic operations like data regridding and coupling between
model components.
All indications are that increases in computing performance through the next decade
will arrive not in the form of faster chips, but by connecting far more of them, requir-
ing new approaches optimized for massively parallel computing and customized to
particular computer designs. A renewed and aggressive commitment to innovatively
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designed common infrastructure across the U.S. climate and weather modeling com-
munities is needed to successfully navigate this transition without massive duplication
of effort that greatly slows overall progress.
This idea of a common software infrastructure is not new or controversial. More than a
decade ago, approaches such as the Earth System Modeling Framework were pio-
neered for this purpose and have become influential and fairly widely used, but no
one approach has become a nationally adopted standard. Individual U.S. modeling
centers have developed different forms of such infrastructure, upon which they now
depend, and have learned from those experiences.
Now is the time to aggressively develop a new common software infrastructure to be
adopted across all major U.S. climate modeling efforts. Such an infrastructure could be
an important tool in facilitating a more integrated plan for U.S. climate modeling. The
committee’s vision is that, in a decade, all major U.S. climate models—global and re-
gional—will share a single common software infrastructure that allows interoperabil-
ity of model components (e.g., atmosphere, land, ocean, or sea ice), even when devel-
oped by different centers, and that supports a common data interface. The proposed
infrastructure would
• facilitate the migration of models to new, possibly radically different comput-
ing platforms (Figure S.2);
• support a research effort to develop high-end global models that execute ef-
ficiently on such platforms, enabling cloud-resolving atmospheric resolutions
(~2-4 km) and eddy-resolving ocean resolutions (~5 km) within as little as a
decade;
• allow centers to easily share model components and design hierarchical
model frameworks with individual components simplified or specialized as
needed for applications such as paleoclimate or weather forecasting and data
assimilation (Figure S.2 and Box S.3);
• allow the academic community, other external modeling groups, and core
modeling centers to work together more easily, because different model con-
figurations could be run using very similar scripts; and
• harmonize outputs and file structures from all models, benefiting the model
analysis and applications communities.
Decades of experience have shown that a full palette of modeling tools—a “model
hierarchy”—is required across various scales and with different degrees of complex-
ity with respect to their representation of the Earth system. The common software
infrastructure is envisioned as a tool for linking together a model hierarchy, making it
portable to a variety of computer architectures and user friendly for education, aca-
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FIGURE S.2 The development of a common software infrastructure that interfaces between the climate
modeling computer code and the computing hardware has two important advantages: (1) it will facilitate
the migration of models to the next generation of computing platforms by isolating the climate model-
ing computer code from the changes in hardware and (2) it will allow the interoperability of climate
model components, for example to enable the testing of two different atmospheric component models,
without having to adapt the component models to different hardware platforms.
demic research, and exploratory science. Within this hierarchy, potential new mod-
eling and evaluation approaches can be tested and compared, and improvements
from one type of model can be easily transitioned to other models. It is a manageable
investment (at least on a national scale) to carefully design, document, and refine one
software infrastructure, and once users have learned it, their experience is transferable
to using other model configurations and their output data structures. The committee
recommends a community-based design and implementation process for achieving a
national common software infrastructure. Although this goal has risks, costs, and insti-
tutional hurdles, the committee believes they are far outweighed by its benefits.
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BOX S.3
SOFTWARE INFRASTRUCTURE ANALOGY TO
OPERATING SYSTEM ON A SMARTPHONE
The software infrastructure described in this report can be thought of as similar to the
operating system on a smartphone. The software infrastructure is designed to run on a specific
hardware platform (analogous to a specific phone), and climate modelers develop model com-
ponents (analogous to apps) to run in the software infrastructure to simulate parts of the climate
system such as the atmosphere or ocean.
Currently, different modeling centers in the United States have different software infrastruc-
tures (operating systems) that run on different pieces of hardware; this is similar to comparing
the iPhone to the Android. This means that climate model components (apps) written for one
software infrastructure will not work with another (similar to how iPhone apps will not work
directly on an Android).
Ultimately, the vision is that the U.S. modeling community could evolve to use the same
common software infrastructure (operating system), so that model components (apps) could
be interchanged and tested versus one another directly. This would also mean that when the
hardware (phone) advances, the software infrastructure (operating system) can be updated
to continue to work with the new hardware without having to completely rewrite the climate
model components (apps).
The common software infrastructure alone will not allow climate models to take
full advantage of the advances in computation of the next 10-20 years. A vigorous
research program is needed to improve the performance of climate models on the
highly concurrent computer architectures that will be the way forward in the com-
ing decade. The common infrastructure will facilitate the sharing of such an advance
across models and modeling centers and thus support this national effort to push the
computational frontiers of climate science.
Convene a National Climate Modeling Forum
To help bring together the nation’s diverse and decentralized modeling communi-
ties and implement the new common software infrastructure, the committee recom-
mends the establishment of an annual U.S. climate modeling forum in which scientists
engaged in both global and regional climate model development and analysis from
across the United States, as well as interested users, would gather to focus on timely
and important cross-cutting issues related to U.S. climate modeling. While modelers
can learn about each other’s progress at conferences and through scholarly journals,
this can be slow, haphazard, and inefficient. The goal of the proposed forum is to
promote better coordination among scientists involved in major global and regional
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modeling efforts across the United States and the user, applications, and analysis com-
munities. These forums could
• serve as a mechanism for informing the community of the current and
planned activities at the core modeling centers;
• provide a venue for fostering important interactions among scientists in the
core modeling efforts and those at other institutions, including universities;
• facilitate a more coordinated approach to global and regional model develop-
ment and use in the United States, including the design of common experi-
ments using multiple models and the formation of joint development teams;
• provide an important vehicle to enhance and accelerate communication
among climate modeling groups at research and operational modeling
centers;
• offer an opportunity to facilitate the development and implementation of a
shared national software infrastructure through sustained, regular interactions
between the infrastructure software developers and model developers and
users;
• offer a vital opportunity for end users of climate model information to both
learn about the strengths and limitations of models, and provide input to
modelers on the critical needs of end users that could feed back into the
model development and application process; and
• provide an opportunity for regular broad-based discussion of strategic priori-
ties for the national climate modeling enterprise.
The development of this approach would benefit greatly from additional resources
specifically targeted to such integrative activities, and from support from a strong
coordinating institution to integrate activities across multiple agencies. Organizations
such as the American Meteorological Society (AMS), the American Geophysical Union
(AGU), or the World Climate Research Program could in theory serve this role, but the
U.S. Global Change Research Program might be a natural choice for organizing the
forum given its mission to coordinate climate research activities in the United States.
Nurture a Unified Weather-Climate Modeling Effort
Unified weather-climate prediction models are increasingly an important part of the
spectrum of climate models. Testing a climate model in a “weather forecast” mode,
with initial conditions taken from a global analysis from a particular time, allows evalu-
ation of rapidly evolving processes such as cloud properties that are routinely ob-
served. Such simulations are short enough to test model performance over a range of
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grid resolutions relevant not only to current but also to prospective climate simulation
capabilities. Transitioning to a unified weather-climate prediction approach is a major
effort that requires substantial infrastructure. This approach is being successfully used
by the UK Met Office, a leading international modeling center. In the United States, no
weather or climate modeling center has yet fully embraced this philosophy, though
several centers have some capability for weather forecasting, climate simulation, and
data assimilation.
The committee recommends an accelerated national modeling effort that spans
weather to climate time scales. One method to achieve this would be nurturing at
least one U.S. unified weather-climate prediction system capable of state-of-the-
art forecasts from days to decades, climate-quality data assimilation, and reanalysis.
This prediction system would be but one effort within the U.S. climate modeling
endeavor. It would be most effective if it involved a collaboration among operational
weather forecast centers, data assimilation centers, climate modeling centers, and the
external research community, which would need to work together to define a unified
modeling strategy and initial implementation steps. To facilitate cross-fertilization
with other climate modeling efforts, this effort should take advantage of the common
software infrastructure and community-wide code and data accessibility described
in the rest of this committee’s strategy. Its success would be judged by simultaneous
improvement of forecast skill metrics on all time scales.
Develop a Program for Climate Model Interpreters
By improving climate models, the scientific community has made considerable prog-
ress in the past decades in its capability to project future climate and its impacts.
Nonetheless, important details about future climate remain uncertain. Simultaneously,
addressing the wide spectrum of user climate information needs is outpacing the
limited capacity of people within the climate modeling community. Effective commu-
nication about climate change and its uncertainty to science managers and decision
makers is a crucial part of advancing our national climate modeling capability. There
is no simple formulaic way to communicate uncertainty; as climate models and their
available outputs become more sophisticated, those looking to use this information
struggle to keep up.
Climate information is already being provided by a number of public and private enti-
ties in various capacities, and there have been numerous other calls for the provision
of more extensive government-run climate information services. The committee chose
to not weigh in on the debate about the appropriate role for the federal government
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in providing climate services. Rather, the committee notes the need for qualified indi-
viduals who can provide credible information to end users based on current climate
models, wherever they work.
To address this need, the committee recommends developing a national education
and accreditation program for “climate model interpreters” who can take technical
findings and output from climate models, including quantified uncertainties, and use
them in a diverse range of private- and public-sector applications. The education com-
ponent could be a degree or certificate program offered by universities with adequate
expertise in climate science and modeling, and the accreditation could be through
a national organization that has a broad reach and is independent of any agency or
modeling center, such as the AMS or the AGU. The training of climate interpreters is
not envisioned as the solution to address all user needs for climate information, but
rather as a crucial step that benefits any system for any of the various mechanisms
that bridge the climate modeling and user communities.
Supporting Recommendations
Sustain State-of-the-Art Computing Systems for Climate Modeling
Climate simulation is difficult because it involves many physical processes interacting
over a large range of space and time scales. Past experience shows that increasing the
range of scales resolved by the model grid ultimately leads to more accurate mod-
els and informs the development of lower-resolution models. Therefore, to advance
climate modeling, U.S. climate science will need the best possible computing platform
and models.
The committee recommends a two-pronged approach that involves the continued
use and upgrading of dedicated computing resources at the existing modeling cen-
ters, complemented by research into more efficient exploitation of the highly concur-
rent computer architectures that are expected in the next 10-20 years.
The community has been able to exploit other extreme-scale computing facilities
that are not solely dedicated to climate as resources of opportunity. Continuing to do
so will likely prove useful, but access to these external systems can be unreliable, and
they often have operating protocols that are not suited to the very long simulations
often needed for climate models. The committee debated whether the current com-
bination of institution-specific computing and use of external computer resources of
opportunity was the best national strategy for climate computing. The pros and cons
of a national climate computing facility were weighed, and it was concluded that such
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a facility would be beneficial only if it were created in addition to the current comput-
ing capabilities at the modeling centers. An expensive new national climate comput-
ing facility would be most attractive and least risky in an environment of sustained
budget growth for climate science and modeling, which would allow it to be pursued
in parallel with other critical investments in climate modeling.
Continue to Contribute to a Strong International Climate Observing System
Observations are critical for monitoring and advancing understanding of the pro-
cesses driving the variability and trajectory of the climate system. The evaluation and
improvement of climate and Earth system models is thus fundamentally tied to the
quality of the observing system for climate. A national strategy for climate modeling
would be incomplete without a well-maintained climate observing system capable
of comprehensively characterizing long-term climate trends and climate variability.
Maintaining a climate observing system is an international enterprise but requires
strong U.S. support that has come under serious threat. Over the next several decades,
it is imperative to maintain existing long-term data sets of essential climate variables,
in tandem with innovative new measurements that illuminate Earth system processes
that are still poorly characterized.
Develop a Training and Reward System for Climate Model Developers
Model development is among the most challenging tasks in climate science, because
it demands synthetic knowledge of climate physics, biogeochemistry, numerical
analysis, and computing environments as well as the ability to work effectively in a
large group. The committee recommends enticing high-caliber computer and climate
scientists to become climate model developers using graduate fellowships in model-
ing centers, extended postdoctoral traineeships of 3-5 years, and rewards for model
advancement through clear well-paid career tracks, institutional recognition, quick
advancement, and adequate funding opportunities.
Enhance the National IT Infrastructure That Supports Climate
Modeling Data Sharing and Distribution
The growth rate of climate model data archives is exponential, and maintaining access
to these data is a growing challenge. Observational data about the Earth system are
also becoming much more voluminous and diverse. The climate research community,
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decision makers, and other user communities desire to analyze and use both types
of data in increasingly sophisticated ways. These trends imply growth in resource
demands that cannot be managed in an ad hoc way. Instead, the data-sharing infra-
structure for supporting international and national model intercomparisons and other
simulations of broad interest—including archiving and distributing model outputs
to the research and user communities—should be systematically supported as an
operational backbone for climate research and serving the user community. Beyond
stabilizing support for current efforts, the United States should develop a national IT
infrastructure for Earth system climate observations and model data that builds from
existing efforts, so as to facilitate and accelerate data display, visualization, and analysis
both for experts and for the broader user community. Without substantial research
effort into new methods of storage, data dissemination, data semantics, and visualiza-
tion, all aimed at bringing analysis and computation to the data, rather than trying to
download the data and perform analysis locally, it is likely that the data might become
frustratingly inaccessible to users.
Pursue Advances in Climate Science and Uncertainty Research
To meet the national need for improved information and guidance over the coming
decades, U.S. climate models will have to address an expanding breadth of scientific
problems while improving the fidelity of predictions and projections from intrasea-
sonal to centennial time scales. The committee finds that climate modeling in the
United States can make significant progress through a combination of increasing
model resolution, advances in observations and process understanding, improved
representations in models of unresolved but climate-relevant processes, and more
complete representations of the Earth system in climate models. As a general guide-
line for most effectively meeting future climate information needs, climate modeling
activities should focus on problems whose solution will help climate models better
inform societal needs, and for which progress is likely given adequate resources. With
such focus, advances in Earth system modeling may yield significant progress in the
next decade or two for a number of scientific questions, including sea-ice loss, ice-
sheet stability, land-ocean ecosystem and carbon-cycle change, regional precipitation
changes and extremes, cloud-climate interaction, and climate sensitivity.
As these challenges are faced and models grow in complexity, they are likely to exhibit
an increasingly rich range of behavior, full of surprises and unexpected results. There-
fore, the committee emphasizes that it is unwise to promise that successive genera-
tions of models will invariably result in firmer predictive capability. Progress on these
challenges is important, however, to develop a fuller understanding of the climate
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system, reducing the likelihood of unanticipated changes and improving climate mod-
els in the long term.
Uncertainty is a significant aspect of climate modeling and needs to be properly
addressed by the climate modeling community. To facilitate this, the United States
should more vigorously support research on uncertainty, including understanding
and quantifying climate projection uncertainty, automating approaches to optimiza-
tion of uncertain parameters within models, communicating uncertainty to both users
of climate model output and decision makers, and developing deeper understanding
on the relationship between uncertainty and decision making.
FINAL COMMENTS
Climate models are among the most sophisticated simulation tools developed by
mankind and the “what-if” questions we are asking of them involve a mind-boggling
number of connected systems. As the scope of climate models has expanded, so has
the need to validate and improve them. Enormous progress has been made in the past
several decades in improving the utility and robustness of climate models, but more
is needed to meet the desires of decision makers who are increasingly relying on the
information from climate models.
The committee believes that the best path forward is a strategy centered around the
integration of the decentralized U.S. climate modeling enterprise—across modeling
efforts, across a hierarchy of model types, across modeling communities focused on
different space and time scales, and between model developers and model output us-
ers. A diversity of approaches is necessary for progress in many areas of climate mod-
eling and is vital for addressing the breadth of users’ needs. If adopted, this strategy of
increased unification amidst diversity will allow the United States to more effectively
meet the climate information needs of the nation in the coming decades and beyond.
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