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Next Generation Earth System Prediction: Strategies for Subseasonal to Seasonal Forecasts (2016)

Chapter: Appendix A: Committee's Statement of Task

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Suggested Citation:"Appendix A: Committee's Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2016. Next Generation Earth System Prediction: Strategies for Subseasonal to Seasonal Forecasts. Washington, DC: The National Academies Press. doi: 10.17226/21873.
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APPENDIX A

Committee’s Statement of Task

An ad hoc committee will conduct a study that will identify opportunities to increase forecasting skill on subseasonal to seasonal (S2S) timescales based on the 2010 NRC report Assessment of Intraseasonal to Interannual Climate Prediction and Predictability and progress since. The report will describe a strategy to increase the nation’s scientific capability for research on S2S forecasting. The committee will develop a 10 year scientific research agenda to accelerate progress on extending prediction skill for weather and ocean forecasts from currently operational meso/synoptic scales to higher spatial and longer temporal resolutions to aid in decision making at medium and extended lead times. The committee’s report will cover

  • Identification of potential sources of predictability and assessment of their relative value for advancing predictive skill;
  • Identification of process studies for incorporating new sources of predictability into models;
  • Application and advancement of ocean-atmosphere-ice-land coupled models;
  • Key observations needed for model initialization and verification of S2S forecasts;
  • Uncertainty quantification and verification of probabilistic products;
  • Approaches to communicating this type of prediction in a way that is useful to and understandable by decision makers; and
  • Computational and data storage and visualization infrastructure requirements.
Suggested Citation:"Appendix A: Committee's Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2016. Next Generation Earth System Prediction: Strategies for Subseasonal to Seasonal Forecasts. Washington, DC: The National Academies Press. doi: 10.17226/21873.
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Suggested Citation:"Appendix A: Committee's Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2016. Next Generation Earth System Prediction: Strategies for Subseasonal to Seasonal Forecasts. Washington, DC: The National Academies Press. doi: 10.17226/21873.
×
Page 317
Suggested Citation:"Appendix A: Committee's Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2016. Next Generation Earth System Prediction: Strategies for Subseasonal to Seasonal Forecasts. Washington, DC: The National Academies Press. doi: 10.17226/21873.
×
Page 318
Next: Appendix B: Details of Seasonal and Subseasonal Forecast Systems »
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As the nation’s economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices.

Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation’s S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.

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