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  • Palmer, Tim N.  (4)
  • 1
    Online Resource
    Online Resource
    Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty
    Wiley ; 2018
    In:  Quarterly Journal of the Royal Meteorological Society Vol. 144, No. 715 ( 2018-07), p. 1947-1964
    Details
    In: Quarterly Journal of the Royal Meteorological Society, Wiley, Vol. 144, No. 715 ( 2018-07), p. 1947-1964
    Abstract: Accurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten‐month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties.
    Type of Medium: Online Resource
    ISSN: 0035-9009 , 1477-870X
    URL: Issue
    URL: Article
    DOI: 10.1002/qj.2018.144.issue-715
    DOI: 10.1002/qj.3394
    RVK:
    UA 1000
    RVK:
    UA 7650
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 3142-2
    detail.hit.zdb_id: 2089168-4
    SSG: 14
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  • 2
    Online Resource
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    Stochastic Subgrid-Scale Ocean Mixing: Impacts on Low-Frequency Variability
    American Meteorological Society ; 2017
    In:  Journal of Climate Vol. 30, No. 13 ( 2017-07), p. 4997-5019
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 30, No. 13 ( 2017-07), p. 4997-5019
    Abstract: In global ocean models, the representation of small-scale, high-frequency processes considerably influences the large-scale oceanic circulation and its low-frequency variability. This study investigates the impact of stochastic perturbation schemes based on three different subgrid-scale parameterizations in multidecadal ocean-only simulations with the ocean model NEMO at 1° resolution. The three parameterizations are an enhanced vertical diffusion scheme for unstable stratification, the Gent–McWilliams (GM) scheme, and a turbulent kinetic energy mixing scheme, all commonly used in state-of-the-art ocean models. The focus here is on changes in interannual variability caused by the comparatively high-frequency stochastic perturbations with subseasonal decorrelation time scales. These perturbations lead to significant improvements in the representation of low-frequency variability in the ocean, with the stochastic GM scheme showing the strongest impact. Interannual variability of the Southern Ocean eddy and Eulerian streamfunctions is increased by an order of magnitude and by 20%, respectively. Interannual sea surface height variability is increased by about 20%–25% as well, especially in the Southern Ocean and in the Kuroshio region, consistent with a strong underestimation of interannual variability in the model when compared to reanalysis and altimetry observations. These results suggest that enhancing subgrid-scale variability in ocean models can improve model variability and potentially its response to forcing on much longer time scales, while also providing an estimate of model uncertainty.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-16-0539.1
    DOI: 10.1175/JCLI-D-16-0539.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2017
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 3
    Online Resource
    Online Resource
    Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2
    Copernicus GmbH ; 2019
    In:  Geoscientific Model Development Vol. 12, No. 7 ( 2019-07-19), p. 3099-3118
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 12, No. 7 ( 2019-07-19), p. 3099-3118
    Abstract: Abstract. We introduce and study the impact of three stochastic schemes in the EC-Earth climate model: two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic Earth system model in atmosphere-only mode. Stochastic parametrization have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as El Niño–Southern Oscillation (ENSO), North Atlantic weather regimes, and the Indian monsoon. Stochasticity in the land component has been shown to improve the variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied. It is shown that the inclusion of all three schemes notably changes the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to significant changes in the model's energy budget and atmospheric circulation. This implies that in order to maintain the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    DOI: 10.5194/gmd-12-3099-2019
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2456725-5
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  • 4
    Online Resource
    Online Resource
    Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model
    Copernicus GmbH ; 2017
    In:  Geoscientific Model Development Vol. 10, No. 3 ( 2017-03-31), p. 1383-1402
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 10, No. 3 ( 2017-03-31), p. 1383-1402
    Abstract: Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    DOI: 10.5194/gmd-10-1383-2017
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2456725-5
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