| NSF Org: |
AGS Division of Atmospheric and Geospace Sciences |
| Recipient: |
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| Initial Amendment Date: | June 2, 2022 |
| Latest Amendment Date: | June 2, 2022 |
| Award Number: | 2203000 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Mea S. Cook
mcook@nsf.gov (703)292-7306 AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences |
| Start Date: | July 1, 2022 |
| End Date: | June 30, 2026 (Estimated) |
| Total Intended Award Amount: | $260,330.00 |
| Total Awarded Amount to Date: | $260,330.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
845 N PARK AVE RM 538 TUCSON AZ US 85721 (520)626-6000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1040 E 4th St Tucson AZ US 85721-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Paleoclimate |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.050 |
ABSTRACT
The general goal of the research is to develop a new framework for advancing model representations of cloud and convective processes by integrating paleoclimate data and climate model simulations. Specifically, the research strategy consists of three main objectives: (1) conduct fully coupled, isotope-enabled simulations for the Last Glacial Maximum (LGM), mid-Holocene (MH), and pre-industrial (PI) time periods using a wide ensemble of cloud and convective parameter sets; (2) perform paleoclimate data assimilation on the perturbed parameter ensemble (PPE) using sea surface temperature (SST) and water isotope proxies, respectively; and (3) use the posteriors from the LGM, MH, and PI assimilations to identify which cloud and convection parameters provide the best match to the proxy data, then conduct present-day and doubled carbon dioxide (CO2) experiments with these parameter sets to calculate a narrowed estimate of equilibrium climate sensitivity.
Equilibrium climate sensitivity (ECS) is a key climate metric that quantifies the rise in global mean surface temperature in response to doubling of atmospheric CO2 relative to PI levels. Changes in hydroclimate, temperature extremes, and other aspects of the climate system in future projections are closely tied to a model?s ECS. For decades, estimates of ECS have remained wide despite improvements from using multiple lines of evidence. One persistent source of this spread is related to cloud and convective processes, which occur at scales too small to be explicitly resolved, and thus require parameterizations to be represented in climate models. This project seeks to address this issue.
The potential Broader Impacts include improvement in climate models, school term and summer internship experience for a high school teacher and graduate student in collaboration with NASA, involvement of undergraduate students in research through the Garden State Louis Stokes Alliance for Minority Participation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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