Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe

After the early pioneering studies during the 2000s, and the first coordinated multi-model effort within the framework of the 5th Coupled Model Inter-comparison Project (CMIP5) in early 2010s, decadal climate predictions are now entering a more mature phase of their historical development. Near-term climate prediction activities have been recently endorsed by the World Climate Research Programme (WCRP) as one of the Grand Challenges in climate science research, and the Lead Centre for Annual-to-Decadal Climate Prediction, collecting hindcasts and forecasts from several contributing centres worldwide has been established by the WMO.Here we present results from the CMIP6 DCPP-A decadal hindcasts produced with the CMCC decadal prediction system (CMCC DPS), based on the fully-coupled CMCC-CM2-SR5 dynamical model. A 10-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2019, is performed using a full-field initialization strategy.The predictive skill for key quantities is assessed and compared with a non-initialized historical simulation, so as to verify the added value of initialization. In particular, the CMCC DPS is capable to skilfully reproduce past-climate surface temperature over the North Atlantic ocean, the Indian ocean and the Western Pacific ocean, as well as over most part of the continents. Beyond the contribution of the climate change, predictive skill emerges, among other regions, for the subpolar North Atlantic sea-surface temperatures, resembling the imprint of the extra-tropical part of the Atlantic Multidecadal Variability.In terms of precipitation, CMCC DPS is able to capture most of the decadal variability over the Northern part of the Eurasian continent. Indeed, a set of regional diagnostics is aimed to investigate the process at stake behind this high predictive skill.

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Development and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependency

Earth System Dynamics ◽

10.5194/esd-10-171-2019 ◽

2019 ◽

Vol 10 (1) ◽

pp. 171-187 ◽

Cited By ~ 3

Author(s):

Mark Reyers ◽

Hendrik Feldmann ◽

Sebastian Mieruch ◽

Joaquim G. Pinto ◽

Marianne Uhlig ◽

...

Keyword(s):

Forecast Accuracy ◽

Coupled Model ◽

Horizontal Resolution ◽

Added Value ◽

Southern Europe ◽

Prediction System ◽

Decadal Prediction ◽

Ensemble Size ◽

Predictive Skill ◽

General Potential

Abstract. The current state of development and the prospects of the regional MiKlip decadal prediction system for Europe are analysed. The MiKlip regional system consists of two 10-member hindcast ensembles computed with the global coupled model MPI-ESM-LR downscaled for the European region with COSMO-CLM to a horizontal resolution of 0.22∘ (∼25 km). Prediction skills are computed for temperature, precipitation, and wind speed using E-OBS and an ERA-Interim-driven COSMO-CLM simulation as verification datasets. Focus is given to the eight European PRUDENCE regions and to lead years 1–5 after initialization. Evidence of the general potential for regional decadal predictability for all three variables is provided. For example, the initialized hindcasts outperform the uninitialized historical runs for some key regions in Europe, particularly in southern Europe. However, forecast skill is not detected in all cases, but it depends on the variable, the region, and the hindcast generation. A comparison of the downscaled hindcasts with the global MPI-ESM-LR runs reveals that the MiKlip prediction system may distinctly benefit from regionalization, in particular for parts of southern Europe and for Scandinavia. The forecast accuracy of the MiKlip ensemble is systematically enhanced when the ensemble size is increased stepwise, and 10 members is found to be suitable for decadal predictions. This result is valid for all variables and European regions in both the global and regional MiKlip ensemble. The present results are encouraging for the development of a regional decadal prediction system.

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Development and prospects of the regional MiKlip decadal prediction system over Europe: Predictive skill, added value of regionalization and ensemble size dependency

10.5194/esd-2017-70 ◽

2017 ◽

Author(s):

Mark Reyers ◽

Hendrik Feldmann ◽

Sebastian Mieruch ◽

Joaquim G. Pinto ◽

Marianne Uhlig ◽

...

Keyword(s):

Forecast Accuracy ◽

Coupled Model ◽

Horizontal Resolution ◽

Added Value ◽

Prediction System ◽

Decadal Prediction ◽

Ensemble Size ◽

Predictive Skill ◽

Current State ◽

General Potential

Abstract. The current state of development and prospects of the regional MiKlip decadal prediction system for Europe are analysed. The Miklip regional system consists of two 10-member hindcast ensembles computed with the global coupled model MPI-ESM-LR downscaled for the European region with COSMO-CLM to a horizontal resolution of 0.22° (~ 25 km). Prediction skills are computed for temperature, precipitation, and wind speed using E-OBS and an ERA-Interim driven COSMO-CLM simulation as verification datasets. Focus is given to the eight European PRUDENCE regions and to lead 20 years 1–5 after initialization. Evidence of the general potential for regional decadal predictability for all three variables is provided. For example, the initialized hindcasts outperform the uninitialized historical runs for some key regions in Europe and for some variables both in terms of accuracy and reliability. However, forecast skill is not detected in all cases, but it depends on the variable, the region, and the hindcast generation. A comparison of the downscaled hindcasts with the global MPI-ESM-LR runs reveals that the MiKlip prediction system may distinctly benefit from regionalization, in particular for 25 parts of Southern Europe and for Scandinavia. The forecast accuracy and the reliability of the MiKlip ensemble is systematically enhanced when the ensemble size is stepwise increased, and a number of 10 members is found to be suitable for decadal predictions. This result is valid for all variables and European regions in both the global and regional MiKlip ensemble. The predictive skill improves distinctly, particularly for temperature, when retaining the long-term trend in the time series. The present results are encouraging towards the development of a regional decadal prediction system.

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Forecast skill of multi-year seasonal means in the decadal prediction system of the Max Planck Institute for Meteorology

Geophysical Research Letters ◽

10.1029/2012gl053326 ◽

2012 ◽

Vol 39 (22) ◽

pp. n/a-n/a ◽

Cited By ~ 48

Author(s):

W. A. Müller ◽

J. Baehr ◽

H. Haak ◽

J. H. Jungclaus ◽

J. Kröger ◽

...

Keyword(s):

Forecast Skill ◽

Prediction System ◽

Decadal Prediction ◽

Max Planck

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Temperature and sea ice hindcast skill of the MiKlip decadal prediction system in the Arctic

Meteorologische Zeitschrift ◽

10.1127/metz/2018/0871 ◽

2018 ◽

Author(s):

Daniel Senftleben ◽

Veronika Eyring ◽

Axel Lauer ◽

Mattia Righi

Keyword(s):

Sea Ice ◽

The Arctic ◽

Prediction System ◽

Decadal Prediction

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High predictability of terrestrial carbon fluxes from an initialized decadal prediction system

Environmental Research Letters ◽

10.1088/1748-9326/ab5c55 ◽

2019 ◽

Vol 14 (12) ◽

pp. 124074 ◽

Cited By ~ 3

Author(s):

Nicole S Lovenduski ◽

Gordon B Bonan ◽

Stephen G Yeager ◽

Keith Lindsay ◽

Danica L Lombardozzi

Keyword(s):

Carbon Fluxes ◽

Prediction System ◽

Decadal Prediction ◽

Terrestrial Carbon ◽

High Predictability

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Predictions of Climate Several Years Ahead Using an Improved Decadal Prediction System

Journal of Climate ◽

10.1175/jcli-d-14-00069.1 ◽

2014 ◽

Vol 27 (20) ◽

pp. 7550-7567 ◽

Cited By ~ 16

Author(s):

Jeff R. Knight ◽

Martin B. Andrews ◽

Doug M. Smith ◽

Alberto Arribas ◽

Andrew W. Colman ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Climate Projections ◽

Prediction System ◽

Decadal Prediction ◽

Decadal Time Scale ◽

Predictive Skill ◽

Decadal Climate ◽

Prediction Systems ◽

Hadley Centre

Abstract Decadal climate predictions are now established as a source of information on future climate alongside longer-term climate projections. This information has the potential to provide key evidence for decisions on climate change adaptation, especially at regional scales. Its importance implies that following the creation of an initial generation of decadal prediction systems, a process of continual development is needed to produce successive versions with better predictive skill. Here, a new version of the Met Office Hadley Centre Decadal Prediction System (DePreSys 2) is introduced, which builds upon the success of the original DePreSys. DePreSys 2 benefits from inclusion of a newer and more realistic climate model, the Hadley Centre Global Environmental Model version 3 (HadGEM3), but shares a very similar approach to initialization with its predecessor. By performing a large suite of reforecasts, it is shown that DePreSys 2 offers improved skill in predicting climate several years ahead. Differences in skill between the two systems are likely due to a multitude of differences between the underlying climate models, but it is demonstrated herein that improved simulation of tropical Pacific variability is a key source of the improved skill in DePreSys 2. While DePreSys 2 is clearly more skilful than DePreSys in a global sense, it is shown that decreases in skill in some high-latitude regions are related to errors in representing long-term trends. Detrending the results focuses on the prediction of decadal time-scale variability, and shows that the improvement in skill in DePreSys 2 is even more marked.

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Evaluation of the MiKlip decadal prediction system using satellite based cloud products

Meteorologische Zeitschrift ◽

10.1127/metz/2015/0602 ◽

2016 ◽

Vol 25 (6) ◽

pp. 695-707

Author(s):

Thomas Spangehl ◽

Marc Schröder ◽

Sophie Stolzenberger ◽

Rita Glowienka-Hense ◽

Alex Mazurkiewicz ◽

...

Keyword(s):

Prediction System ◽

Decadal Prediction

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A large ensemble decadal prediction system with MPI-ESM

10.5194/egusphere-egu21-9263 ◽

2021 ◽

Author(s):

Sebastian Brune ◽

Vimal Koul ◽

David Marcolino Nielsen ◽

Laura Hövel ◽

Holger Pohlmann ◽

...

Keyword(s):

North Atlantic ◽

Prediction Skill ◽

Ensemble Prediction ◽

Prediction System ◽

Decadal Prediction ◽

Ensemble Size ◽

Large Ensemble ◽

Ensemble Prediction System ◽

Atlantic Sector ◽

Ensemble Mean

Current state-of-the-art decadal ensemble prediction systems are run with an ensemble size of 10 to 40 members, their retrospective forecasts of the past are used to assess the system's prediction skill. Here, we present an attempt for a large ensemble decadal prediction system for the time period 1960-today, with an ensemble size of 80 members, based on the low resolution version of the Max Planck Institute Earth system model (MPI-ESM-LR). The ensemble is forced with CMIP6 conditions and initialized every year in November through a weakly coupled assimilation using atmospheric reanalyses via nudging and observed oceanic temperature and salinity profiles via a 16-member ensemble Kalman filter. To generate ensemble members beyond 16, we use additional physical perturbations at stratospheric height. The analysis of our large ensemble prediction system presented here aims for answering two questions: (1) How does the ensemble mean deterministic prediction skill for global and North Atlantic key climate indices change with ensemble size? (2) How well may the 80-member ensemble serve as a basis for a robust statistical analysis of probabilities of extremes in the North Atlantic sector? Preliminary results for global and regional air surface temperature show that in terms of ensemble mean ACC and full ensemble CPRSS with reference data, the 80-member ensemble leads to similar prediction skill as the 16-member ensemble. This indicates that the additional ensemble members may lead to a better sampling of the distribution of model trajectories, paving the way for a more robust statistical probabilistic analysis.

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