Expert Report

A National Strategy for Advancing Climate Modeling (2012)

Each report is produced by a committee of experts selected by the Academy to address a particular statement of task and is subject to a rigorous, independent peer review; while the reports represent views of the committee, they also are endorsed by the Academy. Learn more on our expert consensus reports.

Climate models will need to evolve substantially to deliver climate projections at the scale and level of detail desired by decision makers, this report finds. As climate change has pushed climate patterns outside of historic norms, the need for detailed projections is growing across all sectors, including agriculture, insurance, and emergency preparedness planning.

Despite much recent progress in developing reliable climate models, there are still efficiencies to be gained across the large and diverse U.S. climate modeling community. Evolving to a more unified climate modeling enterprise—in particular by developing a common software infrastructure shared by all climate researchers, and holding an annual climate modeling forum—could help speed progress.

Learn more about A National Strategy for Advancing Climate Modeling by watching a free webinar, featuring presentations by the report's authoring committee and a question and answer session on the report's findings.

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To learn more about climate models and how they work, visit our Climate Modeling 101 site.

Key Messages

  • The U.S. climate modeling community is diverse, consisting of several large global climate modeling efforts and many smaller groups running regional climate models. This diversity allows multiple research groups to tackle complex climate modeling problems in parallel, enabling more rapid progress—but can also lead to duplication of effort, and makes it more difficult to prioritize limited human and computational resources.
  • Promoting unification in some aspects of the U.S. climate modeling enterprise could enable more efficient, coordinated progress. This does not mean establishing only one U.S. center for climate modeling; instead, different climate modeling institutions could pursue their own methodologies but work within a common modeling framework in which software, data standard, tools, and model components are shared by all major modeling groups nationwide.
  • Decision makers often desire climate data based on model projections at higher spatial resolutions and on more specific time scales than currently available. To provide these data, more powerful computing hardware will be needed. This will most likely be achieved not through developing faster computer chips, but by connecting far more computer chips together in parallel—a very different hardware infrastructure than the one currently in use. It will take significant effort to ensure that climate modeling software is compatible with this new hardware.
  • Evolving to a shared software infrastructure for building, configuring, running, and analyzing climate models could help scientists navigate the transition to more complex computer hardware. The U.S. supports several climate models, each conceptually similar but with components assembled with slightly different software and data output standards. If all U.S. climate models employed a single software system, it could simplify testing and migration to new computing hardware, and allow scientists to compare and interchange climate model components, such as land surface or ocean models.
  • An annual U.S. climate modeling forum would help bring the nation's diverse modeling communities together with the users of climate data. This would provide climate model data users with an opportunity to learn more about the strengths and limitations of models and provide input to modelers on their needs and provide a venue for discussions of priorities for the national modeling enterprise, and bring disparate climate science communities together to design common modeling experiments.
  • Many physical and chemical processes can affect both climate and weather, but because climate varies over such long time periods, it takes longer to collect observational data to test the models thoroughly. Developing models that function across both weather and climate timescales would allow the testing of climate models on weather timescales where there is more abundant observational data. These efforts would be most successful if they involved collaboration among operational weather forecast centers, data assimilation centers, climate modeling centers, and the external research community.
  • Meeting the diverse needs of climate data users—which vary over time and range from local to global scales—involves ensuring that climate data are useful and easily understandable to all users. There are organizations (public and private) that currently translate the output of climate models for users, but there are no mechanisms for assuring the quality of the information provided. Developing a national education and accreditation program to train climate model interpreters to use technical findings and output from climate model in a range of applications could help ensure the accuracy and appropriateness of climate information, as well as help communicate users needs back to climate model developers.
  • To address the computing needs of the climate modeling community, the report suggests a two-pronged approach that involves the continued use and upgrading of existing climate-dedicated computing resources at modeling centers, together with research on how to effectively exploit the more complex computer hardware systems expected over the next 10 to 20 years.
  • Sustained observational data on factors such as temperature, precipitation, clouds, snow and ice, and ecosystem change is critical for advancing understanding of the processes that drive the climate system. Over the next several decades, it will be important to maintain existing long-term datasets of essential climate variables, and to launch innovative new climate measurements that help characterize Earth system processes.
  • Model development is among the most challenging tasks in climate science. Indications are that the number of climate model developers is not growing in the United States. Graduate fellowships in modeling centers, extended postdoctoral traineeships of three to five years, and rewards for model advancement through well-paid career tracks could help entice high caliber computer and climate scientists to become climate model developers.
  • Ever larger amounts of climate model and observational data are being generated. Facilitating broad access to these data for researchers, data users, and decision makers is challenging but increasingly important. Beyond stabilizing support for current data infrastructure efforts, the United States should develop a national information technology infrastructure that builds on existing efforts to facilitate and accelerate data display, visualization, and analysis, for experts and the wider user community.
  • To meet national needs for improved climate information over the next several decades, U.S. climate modelers will need to address an expanding breadth of scientific problems while striving to make predictions and projections more accurate. Progress toward this goal can be made through a combination of increasing model resolution, advances in observations, improved model physics, and more complete representations of the Earth system. As a general guideline, priority should be given to climate modeling activities that focus on addressing societal needs and where progress is likely, given adequate resources.