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T. Palmer, D. Anderson (1994)
The prospects for seasonal forecasting—A review paperQuarterly Journal of the Royal Meteorological Society, 120
Arun Kumar, M. Hoerling, M. Ji, A. Leetmaa, P. Sardeshmukh (1996)
Assessing a GCM's Suitability for Making Seasonal PredictionsJournal of Climate, 9
J. Murphy (1988)
The impact of ensemble forecasts on predictabilityQuarterly Journal of the Royal Meteorological Society, 114
R. Madden (1981)
A quantitative approach to long‐range predictionJournal of Geophysical Research, 86
A. Harzallah, R. Sadourny (1995)
Internal Versus SST-Forced Atmospheric Variability as Simulated by an Atmospheric General Circulation ModelJournal of Climate, 8
J. Charney, J. Shukla (1981)
Monsoon dynamics: Predictability of monsoons
R. Madden (1976)
Estimates of the Natural Variability of Time-Averaged Sea-Level PressureMonthly Weather Review, 104
J. Murphy (1990)
Assessment of the practical utility of extended range ensemble forecastsQuarterly Journal of the Royal Meteorological Society, 116
(1990)
Extended-range predictions with ECMWF models: Timelagged ensemble forecasting Predictability of seasonal atmospheric variations
M. Tracton, E. Kalnay (1993)
Operational Ensemble Prediction at the National Meteorological Center: Practical AspectsWeather and Forecasting, 8
W. Ebisuzaki (1995)
The Potential Predictability in a 14-Year GCM SimulationJournal of Climate, 8
N. Lau (1985)
Modeling the Seasonal Dependence of the Atmospheric Response to Observed El Niños in 1962–76Monthly Weather Review, 113
(1974)
Spectral modeling at GFDL
R. Chervin (1986)
Interannual Variability and Seasonal Climate PredictabilityJournal of the Atmospheric Sciences, 43
(1981)
Predictability of monsoons. Monsoon Dynamics
J. Wallace, D. Gutzler (1981)
Teleconnections in the Geopotential Height Field during the Northern Hemisphere WinterMonthly Weather Review, 109
S. Milton (1990)
Practical extended-range forecasting using dynamical modelsMeteorological Magazine, 119
W. Stern, K. Miyakoda (1995)
Feasibility of Seasonal Forecasts Inferred from Multiple GCM SimulationsJournal of Climate, 8
D. Shea, R. Madden (1990)
Potential for long-range prediction of monthly mean surface temperatures over North AmericaJournal of Climate, 3
M. Dàquà (1997)
Ensemble size for numerical seasonal forecastsTellus A, 49
A. Gill (1980)
Some simple solutions for heat‐induced tropical circulationQuarterly Journal of the Royal Meteorological Society, 106
Jeffrey Anderson (1996)
A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model IntegrationsJournal of Climate, 9
I. Smith (1995)
A GCM Simulation of Global Climate Interannual Variability: 1950–1988Journal of Climate, 8
T. Matsuno (1966)
Quasi-geostrophic motions in the equatorial areaJournal of the Meteorological Society of Japan, 44
Č. Branković, T. Palmer, F. Molteni, S. Tibaldi, U. Cubasch (1990)
Extended‐range predictions with ECMWF models: Time‐lagged ensemble forecastingQuarterly Journal of the Royal Meteorological Society, 116
Jeffrey Anderson, William Stern (1996)
Evaluating the Potential Predictive Utility of Ensemble ForecastsJournal of Climate, 9
N. Lau, M. Nath (1994)
A Modeling Study of the Relative Roles of Tropical and Extratropical SST Anomalies in the Variability of the Global Atmosphere-Ocean SystemJournal of Climate, 7
L. Ferranti, F. Molteni, Č. Branković, T. Palmer (1994)
Diagnosis of Extratropical Variability in Seasonal Integrations of the ECMWF ModelJournal of Climate, 7
Č. Branković, T. Palmer, L. Ferranti (1994)
Predictability of seasonal atmospheric variationsJournal of Climate, 7
N. Lau, M. Nath (1990)
A general circulation model study of the atmospheric response to extratropical SST anomalies observe
W. Gates (1992)
AMIP: The Atmospheric Model Intercomparison Project.Bulletin of the American Meteorological Society, 73
R. Mureau, F. Molteni, T. Palmer (1993)
Ensemble prediction using dynamically conditioned perturbationsQuarterly Journal of the Royal Meteorological Society, 119
(1984)
Predictability of time averages. Part II: The influence of the boundary forcing. Problems and Prospects in Long and Medium Range Weather Forecasting
C. Gordon, W. Stern (1982)
A Description of the GFDL Global Spectral ModelMonthly Weather Review, 110
(1974)
Spectral modeling at GFDL. The GARP Programme on Numerical Experimentation
M. Latif, J. Biercamp, H. Storch, M. Mcphaden, E. Kirk (1990)
Simulation of ENSO Related Surface Wind Anomalies with an Atmospheric GCM Forced by Observed SSTJournal of Climate, 3
J. Shukla (1984)
Predictability of Time Averages: Part II: The Influence of the Boundary Forcings
An approach to assess the potential predictability of the extratropical atmospheric seasonal variations in an ensemble of atmospheric general circulation model (AGCM) integrations has been proposed in this study by isolating reproducible forced modes and examining their contributions to the local ensemble mean. The analyses are based on the monthly mean output of an eight-member ensemble of 10-yr Atmospheric Model Intercomparison Project integrations with a T42L18 AGCM. An EOF decomposition applied to the ensemble anomalies shows that there exist some forced modes that are less affected by the internal process and thus appear to be highly reproducible. By reconstructing the ensemble in terms of the more reproducible forced modes and by developing a quantitative measure, the potential predictability index (PPI), which combines the reproducibility with the local variance contribution, the local ensemble mean over some selective geographic areas in the extratropics was shown to result primarily from reproducible forced modes rather than internal chaotic fluctuations. Over those regions the ensemble mean is potentially predictable. Extratropical potentially predictable regions are found mainly over North America and part of the Asian monsoon regions. Interestingly, the potential predictability over some preferred areas such as Indian monsoon areas and central Africa occasionally results primarily from non-ENSO-related boundary forcing, although ENSO forcing generally dominates over most of the preferred areas. The quantitative analysis of the extratropical potential predictability with PPI has shown that the preferred geographic areas have obvious seasonality. For the 850-hPa temperature, for example, potentially predictable regions during spring and winter are confined to Alaska, northwest Canada, and the southeast United States, the traditional PNA region, while during summer and fall they are favored over the middle part of North America. It has also been shown that the boreal summer season (June––August) possesses the largest potentially predictable area, which seems to indicate that it is a favored season for the extratropical potential predictability. On the contrary, boreal winter (December––February) appears to have a minimum area of extratropical potential predictability. The results have been compared with the more traditional statistical tests for potential predictability and with observations from the National Centers for Environmental Prediction reanalysis, which indicates that the PPI analysis proposed here is successful in revealing extratropical potential predictability determined by the external forcing.
Journal of Climate – American Meteorological Society
Published: Aug 27, 1997
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