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New workshop report: high resolution modeling has potential to improve climate predictions but more experimentation is needed


A new report summarizes key findings from the joint NOAA and U.S. Department of Energy (DOE) high resolution modeling workshop held at the NOAA Center for Weather and Climate Prediction in College Park, Maryland on September 30th through October 2nd. Overall, the workshop report states that there have been some promising efforts in the climate predictions (weeks to seasons) and long-term projections communities to explore using high resolution to improve climate models and prediction. However, a systematic exploration of high resolution issues and benefits is still lacking. The scientists recognized that high resolution is not a cure-all, some biases and errors persist or even worsen with increases in model resolution, so experimentation with a range of resolutions, adequate physical modeling, and different modeling systems is needed.
Coarse resolution climate models do not reliably simulate complex physical processes and fine-scale phenomenon at local to regional scales. Recently, there has been a growing demand for more accurate predictions from weeks to seasons at these spatial scales through higher resolution coupled modeling. Given this need, the NOAA-DOE high resolution modeling workshop aimed to enhance communication, to summarize the current status of the research, and to develop a potential experimental research framework for addressing major questions while considering computing resource requirements. The workshop brought together key national and international participants who have been experimenting with cutting edge high-resolution modeling and predictions, including representatives of key operational prediction centers. Addressing the needs and challenges of fine-scale climate prediction could improve forecasts of extremes and regional seasonal predictions, and ultimately planning for resiliency.
Learn more: High Resolution Workshop
View report: High Resolution Workshop Report

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