This program has been archived.
Decadal and Regional Climate Prediction using Earth System Models (EaSM) Crosscutting Programs NSF Wide Programs
|Eric C. Itsweire||William J. Wiseman|
|Anjuli S. Bamzai||GEO/OAD||Peter Milne||GEO/OPP|
|Michael Steuerwalt||Thomas F. Russell|
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 22-1), is effective for proposals submitted, or due, on or after October 4, 2021. Please be advised that, depending on the specified due date, the guidelines contained in NSF 22-1 may apply to proposals submitted in response to this funding opportunity.
The consequences of climate variability and change are becoming more immediate and profound than previously anticipated. Over recent decades, the world has witnessed the onset of prolonged droughts on several continents, increased frequency of floods, loss of agricultural and forest productivity, degraded ocean and permafrost ecosystems, global sea level rise and the rapid retreat of ice sheets and glaciers, loss of arctic sea ice, and changes in ocean currents. These important impacts highlight that climate variability and change can have significant effects on decadal and shorter time scales, with significant consequences for plant, animal, human, and physical systems.
The EaSM funding opportunity enables interagency cooperation on one of the most pressing problems of the millennium: climate change and how it is likely to affect our world. It allows the partner agencies -- National Science Foundation (NSF) and U.S. Department of Agriculture (USDA) -- to combine resources to identify and fund the most meritorious and highest-impact projects that support their respective missions, while avoiding duplication of effort and fostering collaboration between agencies and the investigators they support.
This interdisciplinary scientific challenge calls for the development and application of next-generation Earth System Models that include coupled and interactive representations of such components as ocean and atmospheric currents, agricultural working lands and forests, biogeochemistry, atmospheric chemistry, the water cycle and land ice. This solicitation seeks to attract scientists from the disciplines of geosciences, agricultural sciences, mathematics and statistics. Successful proposals will develop intellectual excitement in the participating disciplinary communities and engage diverse interdisciplinary teams with sufficient breadth to achieve the scientific objectives. We encourage proposals that have strong broader impacts, including public access to data and other research products of general interest, as well as educational, diversity, or societal impacts.
The long-term goals of this solicitation are to improve on and extend current Earth System modeling capabilities to:
- Achieve comprehensive, reliable global and regional predictions of decadal climate variability and change through advanced understanding of the coupled interactive physical, chemical, biological, and human processes that drive the climate system, including as they pertain to agriculture , forestry or land cover/use.
- Quantify the impacts of climate variability and change on natural and human systems, and identify and quantify feedback loops.
- Maximize the utility of available observational and model data for impact, vulnerability/resilience, and risk assessments through up/downscaling activities and uncertainty characterization.
- Effectively translate climate predictions and associated uncertainties into the scientific basis for policy and management decisions related to human interventions and adaptation to the projected impacts of climate change.
The EaSM-3 solicitation focuses primarily on Goal 1 (above) with the following specific areas of interest related to decadal scales: (i) Research that has the potential to dramatically improve predictive capabilities; (ii) Prediction and attribution studies; (iii) Development and applications of metrics, methods, and tools for testing and evaluating climate and climate impact predictions and characterizing their uncertainty.
These subareas of particular interest are described in greater detail below under Program Description: Areas of interest.