V. Program Frontiers for NCAR

Informing Climate Change Adaptation and Mitigation

Over the next one to five years, governments, corporations, foundations, advocacy groups, consulting firms, and science labs will be involved in many overlapping decision processes on adaptation and mitigation. We have two near-term opportunities for constructive engagement that build on our strengths in modeling and simulation and include cooperation with universities and other collaborators with complementary expertise.

The first is to use our newly developed Nested Regional Climate Model (NRCM) to provide very-high-resolution (4 km) predictions of climate change over the next 50 years for the United States and possibly other regions, to support consistent local, regional, and national adaptation planning. (An atmospheric resolution of about 150 km was considered high resolution until recently.) Such simulations would help a wide variety of users with assessing vulnerability and potential impacts and developing strategies to respond. The model holds great promise for investigating the relationship of climate change to hurricanes. It also offers many possibilities for exciting collaborations with the hydrological, ecological, and human health communities, especially if additional atmospheric chemistry is incorporated. Specific actions would include

  • Produce very-high-resolution (4 km) regional-scale predictions of climate change and impacts with NRCM, including detailed characterizations of prediction uncertainty
  • Develop new partnerships focused on analysis of climate impacts on human health, ecosystems, and water resources
  • Partner regionally with scientists and involve stakeholders end to end in creating regional assessments of vulnerability and adaptation options

Our second opportunity is to further develop and apply the Integrated Population-Economy-Technology-Science (iPETS) model to evaluate alternative climate change response strategies. This effort can provide fundamental insights about the coupling of human and natural systems. It can also provide useful information for national-scale decision makers on mitigation and adaptation through integrated analysis of the atmospheric, environmental, and economic consequences of different policy, economic, and technological choices. The use of this medium- scale tool could also inform and be informed by analyses using CCSM. NCAR's computing resources would enable a large number of experimental simulations on a very rapid timescale and would facilitate exploration of couplings to CCSM. We plan to

  • Add and refine components of the iPETS model, including improved representation of spatial land use change, emissions, and mitigation of non-CO2 greenhouse gases, and more detailed representation of key energy technologies
  • Design and execute new simulations to evaluate different mitigation strategies and emissions pathways
  • Explore new ways of linking integrated assessment models to Earth system models and incorporate impacts and adaptation into integrated assessment models

Water Resource Planning

Water and water resources in many areas of the world are particularly sensitive to climate change. The water-limited regions such as the southwestern United States are a case in point. These regions are also experiencing rapid population growth and consequent competing demands for those limited water resources. As a result, water managers, western governors, and the general public are keenly interested in how the water cycle will change as the climate warms and what they might do to cope with such change. We see two topics as particularly important: (1) the potential that the mountain snowpack (the main water reservoir for the western United States) will decrease under climate change, changing the seasonal patterns of runoff and river flow; and (2) the threat of increasing drought under climate change and consequent societal vulnerability and response. To investigate these issues, we plan to

  • Determine the principal controls (large-scale dynamics, moisture sources, orography, convective processes, etc.) on precipitation character (seasonality, frequency, intensity, and phase) in western North America and how these will respond to a changing climate
  • Diagnose, in models and observations, the partitioning of precipitation among runoff, evapotranspiration, and groundwater recharge across western North America and define how this partitioning will change in response to climate change and landscape disturbance (e.g. forest dieback, shrubland succession, fire, urbanization)
  • Improve model physics parameterizations (convection, microphysics, land surface, snow processes, planetary boundary layer) to enable credible climate model simulations of the water cycle over western North America
  • Improve characterization of uncertainty in climate model simulations, through statistical and dynamical downscaling and multi-model ensemble processing (as in the North American Regional Climate Change Assessment Program, or NARCCAP) for the western North American water cycle
  • Work with partners to examine the impact of climate change on groundwater storage (such as in the Ogallala Aquifer).
  • Improve the characterization and parameterization of the impact of the water cycle on biogeochemical cycles through the BEACHON project
  • Determine the leading drivers of societal vulnerability and adaptive capacity to changes in water availability in western North America and determine how state-of-the-art model scenarios can best inform decisions about water resources
  • Develop modeling scenarios to explore how changes in population size and location, economic development, land use, and infrastructure impact water resource management, and how these processes are influenced by climate change

The resulting improvements to climate models and the inclusion of societal vulnerability and adaptation in model development and applications will benefit many other parts of the world, especially those with comparable vulnerabilities.

Tools for Integrating Measurements into Models

Effectively synthesizing multi-scale Earth and Sun system model output with measurements is at the core of much NCAR science. Observations are used to develop theories, confront model results, and, through assimilation techniques, adjust those results. Remote sensing from space now provides essential global-scale information on the atmosphere, and novel sensor networks are being developed that will provide new unique and dense observations, supplementing traditional observations. Model representation of difficult-to-observe processes can be improved by examining the mismatch between models and corresponding forecasts based on assimilation of observational data, particularly satellite observations and spectrally resolved images of the Sun and its magnetic field.

There is an emerging opportunity for NCAR to serve the community by developing and supporting numerical tools and strategies for integrating measurements and models. This process relies on new, flexible methods of data assimilation in which heterogeneous sets of physical measurements can be combined with geophysical models to both yield better predictions and detect model biases. This activity has two distinct benefits: models can augment the often-sparse coverage of observations, and high-resolution observations can diagnose strengths and weaknesses of a physical model and its supporting parameterizations. This frontier will also support new instrument design by providing a framework in which the community can assess the ability of novel observations to improve prediction or elucidate imperfectly understood physical processes. We plan to

  • Confront climate models, solar simulation models, and their components with observations via data assimilation and extensive diagnostic analysis. Extend data assimilation procedures to the upper atmosphere (such as the regions covered by WACCM), and to geospace modeling
  • Develop and distribute tools that promote the integration of remote sensing data with models via data assimilation, and map science questions onto measurement and instrument requirements
  • Develop a prototype system for chemical weather analysis and prediction by combining remote sensing and other observations with data assimilation and a prediction system
  • Exploit the capabilities of NSF aircraft and other airborne observing systems in model and satellite validation and provide tools for comparing measurements with corresponding model representations
  • Develop ensemble data assimilation methods to address sets of bounded observations such as atmospheric concentrations or Doppler radar reflectivity
  • Develop and test assimilation approaches for initialization of decadal-scale and longer climate predictions
  • With the university community, continue to assemble observations of the carbon and nitrogen cycles for the evaluation and improvement of biogeochemical models through testing against observational constraints

New Grid-Based Computing for the Community

NCAR's research, service, and educational activities involve extensive partnerships with individuals and institutions all over the world. Reliable and easy-to-use cyberinfrastructure (CI) is increasingly important to sustaining these collaborative endeavors. Continued advances in advanced grid-based technologies hold significant promise for accelerating scientific progress by making high-performance computing and analysis tools widely and easily available; permitting remote access to and use of scientific instruments; and greatly easing the flow of, access to, and storage of data and information. NCAR is deeply involved in supporting high-performance CI services and tools, observing systems, and atmospheric and related science and education. We are thus very well positioned for a leadership role in the development of advanced grids for scientific research and education. Our near-term objectives are to

  • Develop next-generation science gateway infrastructure and other grid-based technologies to enhance the development of virtual organizations for research and education in the atmospheric and related sciences
  • Continue as a resource partner in the TeraGrid, at least through April 2011, and participate in the proposed TeraGrid data replication service, if funded, as an archive resource partner through September 2013
  • Help define, implement, and improve the next-generation research grid through participation in the NSF eXtreme Digital (XD) Program
  • Investigate and evaluate methods for remote examination and analysis of very large or heterogeneous data sets
  • Explore future grid environments that will allow NCAR and other sites (e.g., universities) to see and be seen through NSF's XD infrastructure
  • Apply the urgent-computing paradigm to weather forecasting applications in a production grid environment
  • Improve the effectiveness and availability of tools for computation, data analysis, workflow, and visualization and of services for researchers and students
  • Develop and deploy a virtual operations center that increases the connectivity of field experiments to researchers, students, and high-end data analysis and modeling facilities

Predict Weather and Impacts of Energy Technologies

Shifting the nation's energy portfolio toward renewable energy sources, such as wind, solar power, and biofuels, is a national priority. Atmospheric science has a role in developing these resources: important meteorological and climatic factors influence the amount of energy available from these sources, and renewable energy developments themselves can have climate and environmental impacts.

There are a number of atmospheric research frontiers of particular relevance. Improved understanding of the atmospheric boundary layer and the interaction of flow regimes with variable topography is crucial for developing wind resources. There is now widespread recognition that poor characterization of the atmospheric conditions in which wind turbines operate is hindering the development of their energy-generation potential: wind farms are under-producing by 15-20%, and turbines that are designed for a 20-year lifetime are failing in less than five years. The efficiency of future power grids can be substantially improved by using accurate and detailed short-term weather predictions to control renewable power generation systems. New sensors and weather prediction systems are needed for future grids that may include energy storage components. Finally, in the area of biofuels, cultivating new crops for scaled up production could significantly change land-use patterns, which, in turn, could negatively impact soil erosion, water resources, and regional climate. NCAR has significant expertise in all of these areas. We plan to

  • Work with collaborators to develop weather and climate research programs focused on infrastructure planning and management, such as boundary layer studies and characterization of land use interactions with regional climate
  • Develop partnerships with the National Renewable Energy Laboratory and utilities that are investing in wind power system to develop, evaluate, and improve sensor technology, observational systems, and short-term wind prediction models
  • Investigate the potential value of improved short-term and seasonal weather prediction for determining energy demands, management of energy supply, pricing and markets, system operations and regulatory compliance, and minimization of economic risk