Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods

Polkova, Iuliia; Brune, Sebastian; Kadow, Christopher; Romanova, V.; Gollan, Gereon; Baehr, Johanna; Glowienka-Hense, Rita; Greatbatch, Richard John; Hense, Andreas; Illing, Sebastian; Köhl, Armin; Kröger, Jürgen; Müller, Wolfgang A.; Pankatz, Klaus; Stammer, Detlef

doi:10.1029/2018ms001439

Cited by 40 publications

(46 citation statements)

References 81 publications

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“…For an analysis of the MPI-ESM performance with respect to its resolution see (Müller et al 2018). The MPI-ESM in similar configuration was recently used for decadal predictions (Marotzke et al 2016;Kröger et al 2018;Polkova et al 2019). The historical simulations that are used as input for the EOF analysis were forced using the CMIP5 solar irradiance data, aerosol and greenhouse gas concentrations (Taylor et al 2012).…”

Section: Model and Input For The Eof Analysismentioning

confidence: 99%

“…Based on the long-standing experience gained in shortterm climate predictions (Rosati et al 1997;Sugiura et al 2008;Balmaseda and Anderson 2009), it can be expected that initial conditions respecting the model's dynamics should lead to the best prediction skill also in decadal predictions (Counillon et al 2014;Liu et al 2017;Mochizuki et al 2016;Polkova et al 2019). From a theoretical point of view, it appears obvious that only a dynamically consistent assimilation approach for generating initial conditions applied to the same coupled model that is being used to perform the predictions can lead to a best prediction skill through a reduced initial model adjustment shock.…”

Section: Introductionmentioning

confidence: 99%

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Climate-mode initialization for decadal climate predictions

2019

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In the context of decadal climate predictions, a climate-mode initialization method is being tested by which ocean ORAS4 reanalysis is projected onto dominant modes of variability of the Earth System Model from the Max Planck Institute for Meteorology (MPI-ESM). The method aims to improve the prediction skill of the model by filtering out dynamically unbalanced noise during the initialization step. Used climate modes are calculated as statistical 3-D modes based on the bivariate empirical orthogonal function (EOF) analysis applied to temperature and salinity anomalies from an ensemble of historical simulations from the MPI-ESM. The climate-mode initialization method shows improved surface temperature skill, particularly over the tropical Pacific Ocean at seasonal-to-interannual timescales associated with the improved zonal momentum balance. There, the new initialization somewhat outperforms the surface temperature skill of the anomaly initialization also for lead years 2-5. In other parts of the world ocean, both initialization methods currently are equivalent in skill. However, only 44% of variance in the original ORAS4 reconstruction remains after the projection on model modes, suggesting that the ORAS4 modes are not fully compatible with the model modes. Moreover, we cannot dismiss the possibility that model modes are not sufficiently sampled with the data set underlying the EOF analysis. The full potential of the climate-mode initialization method for future decadal prediction systems therefore still needs to be quantified based on improved modal representation.

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Section: Model and Input For The Eof Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Climate-mode initialization for decadal climate predictions

2019

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“…It means verifying the analysis is statistically indistinguishable from the ensemble members in a perfect EPS (Toth et al ., ). However, it is also possible if the ensemble has no sharpness, meaning that the temporal variance of the ensemble mean is much smaller than the ensemble mean of the temporal variance of the single realizations (Polkova et al ., ). The present authors calculated the ratio between the temporal variance of the ensemble mean and time mean of variance between ensemble members (data not shown).…”

Section: Comparison Of the New Neps (22 Member) With The Old Neps (44mentioning

confidence: 99%

Medium‐range global ensemble prediction system at 12 km horizontal resolution and its preliminary validation

Mamgain

Sarkar

Rajagopal

2019

Meteorological Applications

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Forecasts of high‐impact weather systems require sufficiently high resolution of state‐of‐the‐art numerical models in order to resolve the small‐scale features. At the National Centre for Medium Range Weather Forecasting (NCMRWF) in India, a global ensemble prediction system (EPS—called the NEPS) has been implemented operationally at 12 km horizontal grid size. The NEPS configuration is based on the UK Met Office Global and Regional Ensemble Prediction System (MOGREPS). Initial condition perturbations are generated by the ensemble transform Kalman filter (ETKF) method. Model uncertainties are taken care of by stochastic kinetic energy backscatter (SKEB) and random parameters (RP) schemes. Forecast perturbations obtained from 6 hr short forecasts of 22 ensemble members are updated by the ETKF four times a day (0000, 0600, 1200 and 1800 UTC). Perturbations of surface parameters such as sea‐surface temperature, soil moisture content and soil temperature are also included in the new NEPS. The NEPS aims to provide 10 day probabilistic long forecasts using 23 ensemble members (22 perturbed plus one control). The long forecast provided at 0000 UTC is the combination of 11 members from the 0000 UTC cycle and lagged 11 members from the 1200 UTC cycle. The new NEPS shows improvements in terms of forecast agreement among the members in comparison with the previously operational NEPS that was running at 33 km horizontal grid size with 44 perturbed members. The ratio between the root mean square error of the ensemble mean and ensemble spread as a function of lead time has improved in both the Northern and Southern Hemispheres in the new NEPS.

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“…The ocean component is run with 1.5 • L40. A general skill assessment of decadal predictions performed with the LR system can be found in Polkova et al (2019). The higher resolution version (MPI-ESM-HR, termed HR hereafter) uses T127 (0.9375 • ) and 95 vertical levels for the atmosphere, and 0.4 • L40 for the ocean (Müller et al, 2018).…”

Section: Forecast System and Skill Measuresmentioning

confidence: 99%

Improvement in the decadal prediction skill of the northern hemisphere extra-tropical winter circulation through increased model resolution

Schuster¹,

Grieger²,

Richling³

et al. 2019

Preprint

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Abstract. In this study the latest version of the MiKlip decadal hindcast system is analyzed and the effect of different horizontal and vertical resolutions on the prediction skill of the northern hemisphere extra-tropical atmospheric circulation is assessed. Four metrics – the stormtrack, blocking frequencies, cyclone frequencies and windstorm frequencies – are analyzed with respect to the anomaly correlation of their winter averages. The model bias and hindcast skill are evaluated in both, a lower resolution version (LR, atm: T63L47, ocean: 1.5° L40) and a higher resolution version (HR, atm: T127L95, ocean: 0.4° L40) of the MPI-ESM system, for the lead years 2–5 using initializations between 1978 and 2012. While the LR version shows common shortcomings of lower resolution climate models, e.g. a too zonal stormtrack and a negative bias of blocking frequencies over the eastern North Atlantic and Europe, the HR version works against these biases. As a result, a functional chain of significantly improved decadal prediction skill between all four metrics is found with the increase of the spatial resolution. While the stormtrack, is significantly improved primarily over the main source region of synoptic activity – the North Atlantic Current, the other extra-tropical measures experience a significant improvement downstream thereof. Thus, the skill of the cyclone frequencies is significantly improved over the central North Atlantic and Northern Europe, the skill of the blocking frequencies is significantly improved over the Mediterranean, Scandinavia and Eastern Europe and the skill of the windstorms is significantly improved over Newfoundland and Central Europe. Not only is the skill improved with the increase in resolution, but the HR system itself exhibits significant skill over large areas of the North Atlantic and European sector for all four circulation metrics. These results are particularly promising regarding the high socio-economic impact of European winter windstorms and blocking situations.

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Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods

Cited by 40 publications

References 81 publications

Climate-mode initialization for decadal climate predictions

Climate-mode initialization for decadal climate predictions

Medium‐range global ensemble prediction system at 12 km horizontal resolution and its preliminary validation

Improvement in the decadal prediction skill of the northern hemisphere extra-tropical winter circulation through increased model resolution

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