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

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Added Value ◽  
Prediction System ◽  
Decadal Prediction ◽  
Ensemble Size ◽  
Size Dependency ◽  
Predictive Skill

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

2019 ◽  
Vol 10 (1) ◽  
pp. 171-187 ◽  
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.

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

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.

scholarly journals Predicting Climate Change over the multi-annual range: a perspective from CMCC Decadal Prediction System

2021 ◽  
Author(s):  
Dario Nicolì ◽  
Alessio Bellucci ◽  
Paolo Ruggieri ◽  
Panos Athanasiadis ◽  
Giusy Fedele ◽  
...  
Keyword(s):  
Climate Change ◽  
North Atlantic ◽  
Decadal Variability ◽  
Climate Prediction ◽  
Added Value ◽  
Prediction System ◽  
Decadal Prediction ◽  
Predictive Skill ◽  
Annual Range ◽  
Decadal Climate

<p>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.</p><p>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.</p><p>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.</p><p>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.</p>

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

2019 ◽  
Vol 71 (1) ◽  
pp. 1618678 ◽  
Author(s):  
Hendrik Feldmann ◽  
Joaquim g. Pinto ◽  
Natalie Laube ◽  
Marianne Uhlig ◽  
Julia Moemken ◽  
...  
Keyword(s):  
Added Value ◽  
Prediction System ◽  
Decadal Prediction

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

2014 ◽  
Vol 27 (20) ◽  
pp. 7550-7567 ◽  
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.

A large ensemble decadal prediction system with MPI-ESM

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

<p>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.</p>

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

2012 ◽  
Vol 39 (22) ◽  
pp. n/a-n/a ◽  
Author(s):  
W. A. Müller ◽  
J. Baehr ◽  
H. Haak ◽  
J. H. Jungclaus ◽  
J. Kröger ◽  
...  
Keyword(s):  
Forecast Skill ◽  
Prediction System ◽  
Decadal Prediction ◽  
Max Planck

scholarly journals NAO predictability from external forcing in the late 20th century

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jeremy M. Klavans ◽  
Mark A. Cane ◽  
Amy C. Clement ◽  
Lisa N. Murphy
Keyword(s):  
North Atlantic ◽  
Radiative Forcing ◽  
Climate Models ◽  
North Atlantic Ocean ◽  
Signal To Noise Ratio ◽  
Prediction System ◽  
Signal To Noise ◽  
Late 20Th Century ◽  
The North ◽  
Predictive Skill

AbstractThe North Atlantic Oscillation (NAO) is predictable in climate models at near-decadal timescales. Predictive skill derives from ocean initialization, which can capture variability internal to the climate system, and from external radiative forcing. Herein, we show that predictive skill for the NAO in a very large uninitialized multi-model ensemble is commensurate with previously reported skill from a state-of-the-art initialized prediction system. The uninitialized ensemble and initialized prediction system produce similar levels of skill for northern European precipitation and North Atlantic SSTs. Identifying these predictable components becomes possible in a very large ensemble, confirming the erroneously low signal-to-noise ratio previously identified in both initialized and uninitialized climate models. Though the results here imply that external radiative forcing is a major source of predictive skill for the NAO, they also indicate that ocean initialization may be important for particular NAO events (the mid-1990s strong positive NAO), and, as previously suggested, in certain ocean regions such as the subpolar North Atlantic ocean. Overall, we suggest that improving climate models’ response to external radiative forcing may help resolve the known signal-to-noise error in climate models.

scholarly journals Merits of a 108-Member Ensemble System in ENSO and IOD Predictions

2019 ◽  
Vol 32 (3) ◽  
pp. 957-972 ◽  
Author(s):  
Takeshi Doi ◽  
Swadhin K. Behera ◽  
Toshio Yamagata
Keyword(s):  
Seasonal Prediction ◽  
Ensemble Prediction ◽  
Economic Losses ◽  
Prediction System ◽  
Ensemble Size ◽  
Ensemble Prediction System ◽  
Skill Scores ◽  
Operational Systems ◽  
The Indian Ocean ◽  
Climate Events

This paper explores merits of 100-ensemble simulations from a single dynamical seasonal prediction system by evaluating differences in skill scores between ensembles predictions with few (~10) and many (~100) ensemble members. A 100-ensemble retrospective seasonal forecast experiment for 1983–2015 is beyond current operational capability. Prediction of extremely strong ENSO and the Indian Ocean dipole (IOD) events is significantly improved in the larger ensemble. It indicates that the ensemble size of 10 members, used in some operational systems, is not adequate for the occurrence of 15% tails of extreme climate events, because only about 1 or 2 members (approximately 15% of 12) will agree with the observations. We also showed an ensemble size of about 50 members may be adequate for the extreme El Niño and positive IOD predictions at least in the present prediction system. Even if running a large-ensemble prediction system is quite costly, improved prediction of disastrous extreme events is useful for minimizing risks of possible human and economic losses.

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

2018 ◽  
Author(s):  
Daniel Senftleben ◽  
Veronika Eyring ◽  
Axel Lauer ◽  
Mattia Righi
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Prediction System ◽  
Decadal Prediction
Sign in / Sign up

Export Citation Format

Share Document