ENSEMBLES: A new multi‐model ensemble for seasonal‐to‐annual predictions—Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs

By Antje Weisheimer, Francisco J. Doblas-Reyes, Tim N. Palmer, A. Alessandri, Alberto Arribas, Michel Déqué, N. Keenlyside, M. Macvean, Antonio Navarra, P. Rogel. 2009

283 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/11393a0c01cd9490977b0572aef8e9a26de9c676

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Tim N. Palmer
2. Michael K. Tippett
3. Martin Leutbecher
4. Francisco J. Doblas-Reyes
5. T. Delsole
6. Duane Waliser
7. Roberto Buizza
8. Antje Weisheimer

In Global and Planetary Change

1. Tim N. Palmer
2. Michael K. Tippett
3. Martin Leutbecher
4. T. Delsole
5. Francisco J. Doblas-Reyes
6. Duane Waliser
7. Roberto Buizza
8. Antje Weisheimer

In Oceanography

1. Duane Waliser
2. T. Delsole
3. Francisco J. Doblas-Reyes
4. Xiaosong Yang
5. June‐Yi Lee
6. Michael K. Tippett
7. J. M. Neena
8. Roberto Buizza

Citations in the corpus

• Stochastic parametrization and model uncertainty (2009, background): “In ENSEMBLES, 5 coupled climate models from different institutions across Europe have completed a set of 7-month long seasonal hindcasts over the period 1960–2005 with 4 start dates per year (Weisheimer et al., 2009).”
• Assessment of representations of model uncertainty in monthly and seasonal forecast ensembles (2011, result): “This is in agreement with the findings of Weisheimer et al. [2009a] and”
• Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts? (2018, methodology): “On the other hand, seasonal forecasts were obtained from four of the GCMs contributing to the ENSEMBLES multimodel seasonal hindcast (Weisheimer et al. 2009), which were produced at the following centres: The European Centre for MediumRange Weather Forecasts (ECMWF), the Leibniz Institute of Marine ”
• Seasonal predictions of precipitation over Africa using coupled ocean-atmosphere general circulation models: skill of the ENSEMBLES project multimodel ensemble forecasts (2011, background): “Further details may be found in Weisheimer et al. (2009).”
• Is unequal weighting significantly better than equal weighting for multi‐model forecasting? (2013, methodology): “Further details of these data can be found in Weisheimer et al. (2009).”
• Predictability and prediction skill of the boreal summer intraseasonal oscillation in the Intraseasonal Variability Hindcast Experiment (2015, background): “In statistically consistent ensembles, the standard deviation of ensembles (i.e. ensemble spread) should match the root-mean square error (RMSE) of the ensemble-mean (e.g. Talagrand et al. 1999; Buizza et al. 2005; Eckel and Mass 2005; Weisheimer et al. 2009, 2011).”