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Computer Modeling Capabilities + Challenges for Earth System Predictions

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Gokhan Danabasoglu, Senior Scientist and Community Earth System Model Chief Scientist, National Center for Atmospheric Research (NCAR)

UCAR Congressional Briefing - April 2018

Published in: Science
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Computer Modeling Capabilities + Challenges for Earth System Predictions

  1. 1. Computer Modeling Capabilities and Challenges for Earth System Predictions Hosted by the University Corporation for Atmospheric Research • April 24, 2018 Gokhan Danabasoglu, NCAR Senior Scientist and CESM Chief Scientist
  2. 2. THE OCEANS & FORECASTING • 2018 Outline • Importance of predictions • Role of Earth System Models • Examples of promising predictions • Challenges and summary
  3. 3. THE OCEANS & FORECASTING • 2018 Predictions: Societal Relevance • Days to a week • Weather forecasts • Subseasonal • Natural hazards preparedness • Seasonal-to-interannual • Shifts in likelihood of weather regimes • Resource management (e.g., water, fire, agriculture) • Transportation changes (e.g., Arctic shipping routes) • Decadal • Long-term resource management (e.g., water, fire, agriculture, forests) • Infrastructure investment • Natural hazard mitigation and adaptation • Demographic and socioeconomic strains • (Re)-insurance
  4. 4. THE OCEANS & FORECASTING • 2018 Building Blocks of Predictions Computer Models Advanced simulations of the Earth System run on supercomputers Observations Satellite, buoys, hydrographic, etc. Initial Conditions Advanced techniques to incorporate current weather / climate state into the models, i.e., a data assimilation system
  5. 5. THE OCEANS & FORECASTING • 2018 The primary tools to make future predictions of weather and climate variability Global Earth System Models The models use physical equations to simulate key fields in the atmosphere, ocean, land, and sea-ice, such as temperature and humidity.
  6. 6. THE OCEANS & FORECASTING • 2018 Global Earth System Models Community Earth System Model
  7. 7. THE OCEANS & FORECASTING • 2018 Yeager et al. (2018, BAMS) Kirtman et al. (2014, BAMS) Subseasonal-Seasonal Predictions Decadal Predictions Coupled Model Inter- Comparison Project (CMIP) Decadal Climate Prediction Project (DCPP) Community Climate Prediction Efforts
  8. 8. THE OCEANS & FORECASTING • 2018 Surface Air Temperature Predictions over North America with CESM on Monthly Time Scales 01 January starts; verifying January-means for 1982-2010 Courtesy of Kirtman Old version New Version Skill Score betterworse Better models and better (ocean) initial conditions lead to better surface temperature predictions over land
  9. 9. THE OCEANS & FORECASTING • 2018 CESM prediction of ice loss Satellite observations Prediction of 10-year Trends in Arctic Winter Sea Ice with CESM Yeager et al. (2015, GRL) observations; predictions; hindcast 1997-2006 period
  10. 10. THE OCEANS & FORECASTING • 2018 • Observational data limitations Observations for initializing ocean, land surface, sea ice are limited • Model quality / fidelity Spatial resolution; representation of processes • Forecasting method limitations • Resource requirements People, computational, and storage Challenges for Predictions
  11. 11. THE OCEANS & FORECASTING • 2018 Summary • Global Earth System Models are the primary tools for future predictions of weather and climate variability • Existing prediction efforts show promising results that are beneficial to the society on multiple time scales • To improve predictions: • Better models and better / more observations are needed to produce better initialization of predictions; • It is crucial to sustain efforts in both observations and model developments

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