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1. Predicting Near-Term Changes in the Earth System: A Large Ensemble of Initialized Decadal Prediction Simulations Using the Community Earth System Model

   https://doi.org/10.1175/BAMS-D-17-0098.1  

   Yeager, S. G. ; Danabasoglu, G. ; Rosenbloom, N. A. ; Strand, W. ; Bates, S. C. ; Meehl, G. A. ; Karspeck, A. R. ; Lindsay, K. ; Long, M. C. ; Teng, H. ; et al ( September 2018 , Bulletin of the American Meteorological Society)
2. Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model: CHEMICAL MECHANISMS IN GEOS

   https://doi.org/10.1002/2017MS001011  

   Nielsen, J. Eric ; Pawson, Steven ; Molod, Andrea ; Auer, Benjamin ; da Silva, Arlindo M. ; Douglass, Anne R. ; Duncan, Bryan ; Liang, Qing ; Manyin, Michael ; Oman, Luke D. ; et al ( December 2017 , Journal of Advances in Modeling Earth Systems)
3. The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2

   https://doi.org/10.5194/gmd-15-6451-2022  

   Yeager, Stephen G. ; Rosenbloom, Nan ; Glanville, Anne A. ; Wu, Xian ; Simpson, Isla ; Li, Hui ; Molina, Maria J. ; Krumhardt, Kristen ; Mogen, Samuel ; Lindsay, Keith ; et al ( January 2022 , Geoscientific Model Development)

   Abstract. The potential for multiyear prediction of impactful Earthsystem change remains relatively underexplored compared to shorter(subseasonal to seasonal) and longer (decadal) timescales. In this study, weintroduce a new initialized prediction system using the Community EarthSystem Model version 2 (CESM2) that is specifically designed to probepotential and actual prediction skill at lead times ranging from 1 month outto 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of acollection of 2-year-long hindcast simulations, with four initializations peryear from 1970 to 2019 and an ensemble size of 20. A full suite of output isavailable for exploring near-term predictability of all Earth systemcomponents represented in CESM2. We show that SMYLE skill for ElNiño–Southern Oscillation is competitive with other prominent seasonalprediction systems, with correlations exceeding 0.5 beyond a lead time of 12months. A broad overview of prediction skill reveals varying degrees ofpotential for useful multiyear predictions of seasonal anomalies in theatmosphere, ocean, land, and sea ice. The SMYLE dataset, experimentaldesign, model, initial conditions, and associated analysis tools are allpublicly available, providing a foundation for research on multiyearprediction of environmental change by the wider community. 

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4. A global coupled ensemble data assimilation system using the Community Earth System Model and the Data Assimilation Research Testbed

   https://doi.org/10.1002/qj.3308  

   Karspeck, Alicia R. ; Danabasoglu, Gokhan ; Anderson, Jeffrey ; Karol, Svetlana ; Collins, Nancy ; Vertenstein, Mariana ; Raeder, Kevin ; Hoar, Tim ; Neale, Richard ; Edwards, Jim ; et al ( December 2018 , Quarterly Journal of the Royal Meteorological Society)
5. Tropical and Midlatitude Impact on Seasonal Polar Predictability in the Community Earth System Model

   https://doi.org/10.1175/JCLI-D-19-0088.1  

   Blanchard-Wrigglesworth, Edward ; Ding, Qinghua ( September 2019 , Journal of Climate)

   Abstract The impact on seasonal polar predictability from improved tropical and midlatitude forecasts is explored using a perfect-model experiment and applying a nudging approach in a GCM. We run three sets of 7-month long forecasts: a standard free-running forecast and two nudged forecasts in which atmospheric winds, temperature, and specific humidity (U, V, T, Q) are nudged toward one of the forecast runs from the free ensemble. The two nudged forecasts apply the nudging over different domains: the tropics (30°S–30°N) and the tropics and midlatitudes (55°S–55°N). We find that the tropics have modest impact on forecast skill in the Arctic or Antarctica both for sea ice and the atmosphere that is mainly confined to the North Pacific and Bellingshausen–Amundsen–Ross Seas, whereas the midlatitudes greatly improve Arctic winter and Antarctic year-round forecast skill. Arctic summer forecast skill from May initialization is not strongly improved in the nudged forecasts relative to the free forecast and is thus mostly a “local” problem. In the atmosphere, forecast skill improvement from midlatitude nudging tends to be largest in the polar stratospheres and decreases toward the surface. 

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