Abstract
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.
Highlights
In recent years, interest in climate predictions on timescales from 1 year up to a decade has increased in the climate science community, since this time span falls within the planning horizon for a wide variety of decision makers (Meehl et al, 2009, 2014)
It is significant for most regions in western Europe in CCLM_b0 and large parts of southern Europe in CCLM_b1 (Fig. 2a and b). This is due to the strong positive trend in the observed temperature, which is predicted by the hindcasts but not captured by the climatology. Deviations between both ensembles are larger for precipitation (Fig. 2c and d), where the mean squared error skill score (MSESS) fields are distinctly patchier when compared to temperature (Fig. 2a and b)
No systematic conclusion can be stated for the delta_ACC, as the ensemble size dependency of the predictive skill depends on the variable and the considered MiKlip ensemble (Fig. 5d–f)
Summary
Interest in climate predictions on timescales from 1 year up to a decade has increased in the climate science community, since this time span falls within the planning horizon for a wide variety of decision makers (Meehl et al, 2009, 2014). The North Atlantic is a key region for decadal predictions and forecast skill is found for various quantities such as heat content and sea surface temperature Recent studies suggest that in particular the Atlantic multi-decadal variability, which is strongly linked to the Atlantic Meridional Overturning Circulation (AMOC), is a major source of decadal predictability (Smith et al, 2012; Pohlmann et al, 2013a). As such low-frequency variability patterns may affect the climate globally, perennial means of meteorological parameters might be predictable several years ahead. Few studies analyse storm tracks (Kruschke et al, 2014, 2016), Atlantic tropical cyclones (Dunestone et al, 2011), intense or extreme events (e.g. Benestad and Mezghani, 2015; Eade et al, 2012), or zoom into a certain region of the world (e.g. Guemas et al, 2015)
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