Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

DOE Call for White Papers Results in 155 Submissions

Papers will inform the design of workshops for new Artificial Intelligence for Earth System Predictability (AI4ESP)

This schematic details the model-experiment (MODEX) approach to scientific discovery (outer ring) and various DOE data, models, and analysis capabilities that should be linked as community resources based on open-science principles (inner sphere).
This schematic details the model-experiment (MODEX) approach to scientific discovery (outer ring) and various DOE data, models, and analysis capabilities that should be linked as community resources based on open-science principles (inner sphere).

At the close of 2020, the U.S. Department of Energy’s (DOE) Earth and Environmental Systems Sciences Division (EESSD) issued a call for white papers for the Artificial Intelligence for Earth System Predictability (AI4ESP).

White papers were solicited for the development and application of AI methods in areas relevant to EESSD research with an emphasis on quantifying and improving Earth system predictability, particularly related to the integrative water cycle and extreme events.

According to the DOE call, the white papers are intended to inform the design of workshops (conducted in 2021 to 2022) focused on answering the question of how DOE can directly leverage AI to engineer a substantial (paradigm-changing) improvement in earth system predictability.

The EESSD scientific communities responded with 155 white papers. Each may be reviewed on the AI4ESP website.

Planning for the AI4ESP workshop reflects a DOE vision to facilitate and accelerate a paradigm shift in AI methods and applications to address significant scientific challenges in the observation-modeling continuum.

Learn more about the AI4ESP initiative.

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