Leveraging machine learning to improve understanding and predictability of weather/climate extremes and the resilience of human systems
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Focal Area(s): Developing hybrid models for predicting weather/climate extremes at the intersection of the urban environment (focal area #2). Science Challenge: Limited by many sources of uncertainty, numerical models are unable to accurately simulate weather and climate processes and this problem is particularly acute for modeling extreme events, including hurricanes. Moreover, computational limits within these numerical models bound our ability to develop large ensembles to explore this uncertainty and the implications relative to characterization of risk and resilience within the human systems that are impacted by changes in extremes.
- Research Organization:
- Artificial Intelligence for Earth System Predictability (AI4ESP) Collaboration (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- DOE Contract Number:
- 35604.1
- OSTI ID:
- 1769737
- Report Number(s):
- AI4ESP-1007
- Country of Publication:
- United States
- Language:
- English
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