together with an initialization procedure and a model evaluation system. This paper 31 summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern 32 strategies and structures of research that targets future operational use. 33Three prediction-system generations have been constructed, characterized by 34 alternative initialization strategies; the later generations show a marked improvement in 35 hindcast skill for surface temperature. Hindcast skill is also identified for multi-year-mean 36European summer surface temperatures, extra-tropical cyclone tracks, the Quasi-Biennial 37Oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly 38 enhances the skill in European surface temperature inherited from the global model and also 39 displays hindcast skill for wind-energy output. A new volcano code package permits rapid 40 modification of the predictions in response to a future eruption. 41MiKlip has demonstrated the efficacy of subjecting a single global prediction system 42 to a major research effort. The benefits of this strategy include the rapid cycling through the 43 prediction-system generations, the development of a sophisticated evaluation package usable 44 by all MiKlip researchers, and regional applications of the global predictions. Open research 45 questions include the optimal balance between model resolution and ensemble size, the 46 appropriate method for constructing a prediction ensemble, and the decision between full-47 field and anomaly initialization. 48

Our decadal climate prediction system, which is based on the Max-Planck-Institute Earth System Model, is initialized from a coupled assimilation run that utilizes nudging to selected state parameters from reanalyses. We apply full-field nudging in the atmosphere and either full-field or anomaly nudging in the ocean. Full fields from two different ocean reanalyses are considered. This comparison of initialization strategies focuses on the North Atlantic Subpolar Gyre (SPG) region, where the transition from anomaly to full-field nudging reveals large differences in prediction skill for sea surface temperature and ocean heat content (OHC). We show that nudging of temperature and salinity in the ocean modifies OHC and also induces changes in mass and heat transports associated with the ocean flow. In the SPG region, the assimilated OHC signal resembles well OHC from observations, regardless of using full fields or anomalies. The resulting ocean transport, on the other hand, reveals considerable differences between full-field and anomaly nudging. In all assimilation runs, ocean heat transport together with net heat exchange at the surface does not correspond to OHC tendencies, the SPG heat budget is not closed. Discrepancies in the budget in the cases of full-field nudging exceed those in the case of anomaly nudging by a factor of 2-3. The nudging-induced changes in ocean transport continue to be present in the free running hindcasts for up to 5 years, a clear expression of memory in our coupled system. In hindcast mode, on annual to inter-annual scales, ocean heat transport is the dominant driver of SPG OHC. Thus, we ascribe a significant reduction in OHC prediction skill when using full-field instead of anomaly initialization to an initialization shock resulting from the poor initialization of the ocean flow.

Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system "Mittelfristige Klimaprognose" (MiKlip). Among the tested methods, three tackle aspects of model-consistent initialization using the ensemble Kalman filter, the filtered anomaly initialization, and the initialization method by partially coupled spin-up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter corrects each ensemble member with the ensemble mean during model integration. And the bred vectors perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low-resolution configuration (Preop-LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop-LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the ensemble Kalman filter and filtered anomaly initialization show the most distinct improvements over Preop-LR for surface temperatures and upper ocean heat content, followed by the bred vectors, the ensemble dispersion filter, and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin-wide long-term mean and variability and with respect to the temporal evolution at the 26 • N latitude.

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Abstract. Marine cold air outbreaks (MCAOs) in the northeastern North Atlantic occur due to the advection of extremely cold air over an ice-free ocean. MCAOs are associated with a range of severe weather phenomena, such as polar lows, strong surface winds and intense cooling of the ocean surface. Given these extreme impacts, the identification of precursors of MCAOs is crucial for improved long-range prediction of associated impacts on Arctic infrastructure and human lives. MCAO frequency has been linked to the strength of the stratospheric polar vortex, but the study of connections to the occurrence of extreme stratospheric events, known as sudden stratospheric warmings (SSWs), has been limited to cold extremes over land. Here, the influence of SSW events on MCAOs over the North Atlantic ocean is studied using reanalysis datasets. Overall, SSW events are found to be associated with more frequent MCAOs in the Barents Sea and the Norwegian Sea compared to climatology and less frequent MCAOs in the Labrador Sea. In particular, SSW events project onto an anomalous dipole pattern of geopotential height 500 hPa, which consists of a ridge anomaly over Greenland and a trough anomaly over Scandinavia. By affecting the variability of the large-scale circulation patterns in the North Atlantic, SSW events contribute to the strong northerly flow over the Barents and Norwegian seas and thereby increase the likelihood of MCAOs in these regions. In contrast, the positive geopotential height anomaly over Greenland reduces the probability of MCAOs in the Labrador Sea after SSW events. As SSW events tend to have a long-term influence on surface weather, these results are expected to benefit the predictability of MCAOs in the Nordic Seas for winters with SSW events.

Marine cold-air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large-scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA-Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis.

Based on decadal hindcasts initialized every five years over the period 1960–2000, the predictive skill of annual-mean regional steric sea level and associated mechanisms are investigated. Predictive skill for steric sea level is found over large areas of the World Ocean, notably over the subtropical Atlantic and Pacific Oceans, along the path of the North Atlantic Current, and over the Indian and Southern Oceans. Mechanisms for the predictability of the thermosteric and halosteric contributions to the steric signal are studied by separating these components into signals originating from processes within and beneath the mixed layer. Contributions originating from below the mixed layer are further decomposed into density-related (isopycnal motion term) and density-compensated (spice term) changes. In regions of the subtropical Pacific and Atlantic Oceans, predictive skill results from the interannual variability associated with the contribution from isopycnal motion to thermosteric sea level. Skill related to thermosteric mixed layer processes is found to be important in the subtropical Atlantic, while the spice contribution shows skill over the subpolar North Atlantic. In the subtropics, the high predictive skill can be rationalized in terms of westward-propagating baroclinic Rossby waves for a lead time of 2–5 yr, as demonstrated using an initialized Rossby wave model. Because of the low Rossby wave speed in high latitudes, this process is not separable from the persistence there.

Abstract. Marine cold air outbreaks (MCAOs) in the Arctic are associated with a range of severe weather phenomena, such as polar lows, strong surface winds and intense cooling of the ocean surface. While MCAO frequency has been linked to the strength of the stratospheric polar vortex, a connection to the occurrence of extreme stratospheric events, known as sudden stratospheric warmings (SSWs), has dominantly been investigated with respect to cold extremes over land. Here, the influence of SSW events on MCAOs in the Barents Sea is studied using observational and reanalysis datasets. Overall, more than a half of SSW events lead to more frequent MCAOs in the Barents Sea. SSW events with an enhanced MCAO response in the Barents Sea are associated with a ridge over Greenland and a trough over Scandinavia, leading to an anomalous dipole pattern of 500-hPa geopotential height and strong northerly flow over the Norwegian Sea. As SSW events tend to have a long-term influence on surface weather, these results can shed light on the predictability of MCAOs in the Arctic for winters with SSW events.