The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

• Published in: NASA Center for AeroSpace Information (CASI). Misc. Resources
• Main Authors: Kirtman, Ben P, Min, Dughong, Peng, Peitao, Tripp, Patrick, Huang, Jin, DeWitt, David G, Tippett, Michael K, Barnston, Anthony G, Li, Shuhua, Rosati, Anthony, Schubert, Siegfried D, Rienecker, Michele, Infanti, Johnna M, Suarez, Max, Li, Zhao E, Marshak, Jelena, Lim, Young-Kwon, Tribbia, Joseph, Pegion, Kathleen, Merryfield, William J, Denis, Bertrand, Wood, Eric F, Kinter, James L, Paolino, Daniel A, Zhang, Qin, vandenDool, Huug, Saha, Suranjana, Mendez, Malaquias Pena, Becker, Emily
• Format: Web Resource
• Language: English
• Published: Hampton NASA/Langley Research Center 01.01.2013
• Subjects: Climate; Collaboration; Delivery scheduling; Predictions; Uncertainty; Workshops

The recent US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multi-model ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) then any single model ensemble. This multi-model approach is the basis for several international collaborative prediction research efforts, an operational European system and there are numerous examples of how this multi-model ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test Bed (CTB) NMME workshops (February 18, and April 8, 2011) a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data is readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (http://origin.cpc.ncep.noaa.gov/products/people/wd51yf/NMME/index.html). Moreover, the NMME forecast are already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, presents an overview of the multi-model forecast quality, and the complementary skill associated with individual models.