Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-351-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-351-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Jan 2018
Model description paper |
| 25 Jan 2018
| 25 Jan 2018
Parametric decadal climate forecast recalibration (DeFoReSt 1.0)
Alexander Pasternack
CORRESPONDING AUTHOR
Institute of Meteorology, Freie Universität Berlin, Berlin, Germany
Jonas Bhend
Federal Office of Meteorology and Climatology (MeteoSwiss), Zürich, Switzerland
Mark A. Liniger
Federal Office of Meteorology and Climatology (MeteoSwiss), Zürich, Switzerland
Henning W. Rust
Institute of Meteorology, Freie Universität Berlin, Berlin, Germany
Wolfgang A. Müller
Max-Planck-Institute for Meteorology, Hamburg, Germany
Uwe Ulbrich
Institute of Meteorology, Freie Universität Berlin, Berlin, Germany
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Cited
16 citations as recorded by crossref.
- Embedding trend into seasonal temperature forecasts through statistical calibration of GCM outputs Y. Shao et al. 10.1002/joc.6788
- Impact of ocean data assimilation on climate predictions with ICON-ESM H. Pohlmann et al. 10.1007/s00382-022-06558-w
- Recent applications and potential of near-term (interannual to decadal) climate predictions T. O'Kane et al. 10.3389/fclim.2023.1121626
- Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe H. Feldmann et al. 10.1080/16000870.2019.1618678
- A quantile mapping approach‐based bias correction in Coupled Model Intercomparison Project Phase 5 models for decadal temperature predictions over India J. Patel et al. 10.1002/joc.7376
- The effects of bias, drift, and trends in calculating anomalies for evaluating skill of seasonal-to-decadal initialized climate predictions G. Meehl et al. 10.1007/s00382-022-06272-7
- Predicting the global temperature with the Stochastic Seasonal to Interannual Prediction System (StocSIPS) L. Del Rio Amador & S. Lovejoy 10.1007/s00382-019-04791-4
- Using regional scaling for temperature forecasts with the Stochastic Seasonal to Interannual Prediction System (StocSIPS) L. Del Rio Amador & S. Lovejoy 10.1007/s00382-021-05737-5
- CanStoc: A Hybrid Stochastic–GCM System for Monthly, Seasonal and Interannual Predictions S. Lovejoy & L. Del Rio Amador 10.3390/meteorology2040029
- Recalibrating decadal climate predictions – what is an adequate model for the drift? A. Pasternack et al. 10.5194/gmd-14-4335-2021
- Calibrating large-ensemble European climate projections using observational data C. O'Reilly et al. 10.5194/esd-11-1033-2020
- Introduction to Freva – A Free Evaluation System Framework for Earth System Modeling C. Kadow et al. 10.5334/jors.253
- Bias adjustment for decadal predictions of precipitation in Europe from CCLM J. Li et al. 10.1007/s00382-019-04646-y
- The regional MiKlip decadal prediction system for Europe: Hindcast skill for extremes and user‐oriented variables J. Moemken et al. 10.1002/joc.6824
- The DWD climate predictions website: Towards a seamless outlook based on subseasonal, seasonal and decadal predictions A. Paxian et al. 10.1016/j.cliser.2023.100379
- High-Resolution Decadal Drought Predictions for German Water Boards: A Case Study for the Wupper Catchment A. Paxian et al. 10.3389/fclim.2022.867814
15 citations as recorded by crossref.
- Embedding trend into seasonal temperature forecasts through statistical calibration of GCM outputs Y. Shao et al. 10.1002/joc.6788
- Impact of ocean data assimilation on climate predictions with ICON-ESM H. Pohlmann et al. 10.1007/s00382-022-06558-w
- Recent applications and potential of near-term (interannual to decadal) climate predictions T. O'Kane et al. 10.3389/fclim.2023.1121626
- Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe H. Feldmann et al. 10.1080/16000870.2019.1618678
- A quantile mapping approach‐based bias correction in Coupled Model Intercomparison Project Phase 5 models for decadal temperature predictions over India J. Patel et al. 10.1002/joc.7376
- The effects of bias, drift, and trends in calculating anomalies for evaluating skill of seasonal-to-decadal initialized climate predictions G. Meehl et al. 10.1007/s00382-022-06272-7
- Predicting the global temperature with the Stochastic Seasonal to Interannual Prediction System (StocSIPS) L. Del Rio Amador & S. Lovejoy 10.1007/s00382-019-04791-4
- Using regional scaling for temperature forecasts with the Stochastic Seasonal to Interannual Prediction System (StocSIPS) L. Del Rio Amador & S. Lovejoy 10.1007/s00382-021-05737-5
- CanStoc: A Hybrid Stochastic–GCM System for Monthly, Seasonal and Interannual Predictions S. Lovejoy & L. Del Rio Amador 10.3390/meteorology2040029
- Recalibrating decadal climate predictions – what is an adequate model for the drift? A. Pasternack et al. 10.5194/gmd-14-4335-2021
- Calibrating large-ensemble European climate projections using observational data C. O'Reilly et al. 10.5194/esd-11-1033-2020
- Introduction to Freva – A Free Evaluation System Framework for Earth System Modeling C. Kadow et al. 10.5334/jors.253
- Bias adjustment for decadal predictions of precipitation in Europe from CCLM J. Li et al. 10.1007/s00382-019-04646-y
- The regional MiKlip decadal prediction system for Europe: Hindcast skill for extremes and user‐oriented variables J. Moemken et al. 10.1002/joc.6824
- The DWD climate predictions website: Towards a seamless outlook based on subseasonal, seasonal and decadal predictions A. Paxian et al. 10.1016/j.cliser.2023.100379
Saved (final revised paper)
Latest update: 20 Nov 2024
Short summary
We propose a decadal forecast recalibration strategy (DeFoReSt) which simultaneously adjusts unconditional and conditional bias, as well as the ensemble spread while considering the typical setting of decadal predictions, i.e., model drift and a climate trend. We apply DeFoReSt to decadal toy model data and surface temperature forecasts from the MiKlip system and find consistent improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.
We propose a decadal forecast recalibration strategy (DeFoReSt) which simultaneously adjusts...
