Eric C. Itsweire OCE Division Of Ocean Sciences
GEO Directorate For Geosciences
March 1, 2013
February 28, 2018 (Estimated)
Awarded Amount to Date:
Gokhan Danabasoglu email@example.com (Principal Investigator)
Jeffrey Anderson (Co-Principal Investigator) Grant Branstator (Co-Principal Investigator) Keith Lindsay (Co-Principal Investigator) Joseph Tribbia (Co-Principal Investigator)
University Corporation For Atmospheric Res
3090 Center Green Drive
CR, Earth System Models
Program Reference Code(s):
Program Element Code(s):
Skillful decadal climate predictions have the potential to provide enormous social, economic, and environmental value. Such efforts, however, are in their infancy and many formidable scientific and technical challenges exist. Decadal prediction represents a combined initial value and boundary value problem in which prediction capabilities must be largely derived from the intrinsic variability of the climate system. In this project, through an interdisciplinary collaboration, the investigators seek i) to produce an improved and reliable decadal prediction system within the Community Earth System Model (CESM) framework, including predictive capabilities for marine ecosystems and biogeochemical constituents and ii) to advance the use of decadal prediction simulations in regional and societal impact studies. Attainment of these goals and developing a well-founded decadal prediction system will rely on improved understanding and technical capabilities in four fundamental areas. Thus, the research aims at (1) improving the understanding of intrinsic decadal variability and mechanisms; (2) evaluating the inherent predictability constraints of the current forecast model; (3) evaluating practical forecast system design methods; and (4) generating capabilities for incorporating fully-coupled data assimilation and ocean ecosystems and biogeochemistry into the NCAR decadal prediction system. The insights, knowledge, and capabilities developed from these objectives will then be used to establish a modeling and initialization strategy for making multi-decadal predictions. Regional and societal impact studies using the output from these decadal prediction experiments will be performed to advance the science of decadal prediction by pursuing and integrating research developments and insights across multiple relevant disciplines: climate dynamics, predictability, low- and high-resolution coupled climate modeling, data assimilation, biogeochemical and ecosystem modeling, regional weather forecasting, population dynamics, and fish habitats. The end result will be improved understanding of the limits and practical potential of decadal prediction, well-founded modeling and initialization strategies for making predictions, and advanced capabilities for downscaling and interpreting physical climate predictions for societal benefits.
This project will produce a well-founded decadal prediction system within the CESM framework that incorporates DART (Data Assimilation Research Testbed) and WRF (Weather Research and Forecast model). The prediction system, enhanced modeling capabilities, and results and data from our simulations will be made available to the broader research community via regular CESM and DART community releases as well as project web pages. These developments will serve as important community resources. This research project in its entirety is aimed at studying decadal climate variability in a socially relevant context. Specifically, the impacts of predicted decadal changes on winter storm events, summer heat waves, ocean ecosystems and biogeochemistry, human population, and fisheries' species ranges will be examined with a focus on North America and surrounding areas. Early career scientists, including a postdoc, will conduct much of the proposed work, and all the partnering institutions are are committed to mentoring activities to ensure success. In addition, two Ph. D. studies will include work from this proposal. Finally, at NCAR, the project team will host an annual student in the UCAR SOARS (Significant Opportunities in Atmospheric Research and Science; www.soars.ucar.edu) program to entrain a diverse community for the scientific workforce of the future.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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G. Branstator and H. Teng. "Is AMOC more predictable than North Atlantic heat content?," J. Climate, v.27, 2014, p. 3537.
Danabasoglu, Yeager, Kim, Karspeck, et al.. "North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability," Ocean Modelling, v.97, 2016, p. 65-90.
Karspeck, Yeager, Danabasoglu, Teng. "An evaluation of experimental decadal predictions using CCSM4," Climate Dynamics, v.44, 2015, p. 907-923.
Yeager, Karspeck, Danabasoglu. "Predicted slowdown in the rate of Atlantic sea ice loss," Geophys. Res. Lett., v.42, 2015.