Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Meteorologists in the energy industry increasingly draw upon the potential for enhanced sub‐seasonal predictability of European surface weather following anomalous states of the winter stratospheric polar vortex (SPV). How the link between the SPV and the large‐scale tropospheric flow translates into forecast skill for surface weather in individual countries – a spatial scale that is particularly relevant for the energy industry – remains an open question. Here we quantify the effect of anomalously strong and weak SPV states at forecast initial time on the probabilistic extended‐range reforecast skill of the European Centre for Medium‐Range Weather Forecasts (ECMWF) in predicting country‐ and month‐ahead‐averaged anomalies of 2 m temperature, 10 m wind speed, and precipitation. After anomalous SPV states, specific surface weather anomalies emerge, which resemble the opposing phases of the North Atlantic Oscillation. We find that forecast skill is, to first order, only enhanced for countries that are entirely affected by these anomalies. However, the model has a flow‐dependent bias for 2 m temperature (T2M): it predicts the warm conditions in Western, Central and Southern Europe following strong SPV states well, but is overconfident with respect to the warm anomaly in Scandinavia. Vice versa, it predicts the cold anomaly in Scandinavia following weak SPV states well, but struggles to capture the strongly varying extent of the cold air masses into Central and Southern Europe. This tends to reduce skill (in some cases significantly) for Scandinavian countries following strong SPV states, and most pronounced, for many Central, Southern European, and Balkan countries following weak SPV states. As most of the weak SPV states are associated with sudden stratospheric warmings (SSWs), our study thus advices particular caution when interpreting sub‐seasonal regional T2M forecasts following SSWs. In contrast, it suggests that the model benefits from enhanced predictability for a considerable part of Europe following strong SPV states

Year-round sub-seasonal forecast skill for Atlantic-European weather regimes

Weather regime forecasts are a prominent use case of sub‐seasonal prediction in the midlatitudes. A systematic evaluation and understanding of year‐round sub‐seasonal regime forecast performance is still missing, however. Here we evaluate the representation of and forecast skill for seven year‐round Atlantic–European weather regimes in sub‐seasonal reforecasts from the European Centre for Medium‐Range Weather Forecasts. Forecast calibration improves regime frequency biases and forecast skill most strongly in summer, but scarcely in winter, due to considerable large‐scale flow biases in summer. The average regime skill horizon in winter is about 5 days longer than in summer and spring, and 3 days longer than in autumn. The Zonal Regime and Greenland Blocking tend to have the longest year‐round skill horizon, which is driven by their high persistence in winter. The year‐round skill is lowest for the European Blocking, which is common for all seasons but most pronounced in winter and spring. For the related, more northern Scandinavian Blocking, the skill is similarly low in winter and spring but higher in summer and autumn. We further show that the winter average regime skill horizon tends to be enhanced following a strong stratospheric polar vortex (SPV), but reduced following a weak SPV. Likewise, the year‐round average regime skill horizon tends to be enhanced following phases 4 and 7 of the Madden–Julian Oscillation (MJO) but reduced following phase 2, driven by winter but also autumn and spring. Our study thus reveals promising potential for year‐round sub‐seasonal regime predictions. Further model improvements can be achieved by reduction of the considerable large‐scale flow biases in summer, better understanding and modeling of blocking in the European region, and better exploitation of the potential predictability provided by weak SPV states and specific MJO phases in winter and the transition seasons.The overall sub‐seasonal forecast performance (biases and skill) for predicting seven year‐round Atlantic–European weather regimes is highest in winter and lowest in summer. The year‐round skill horizon is shortest for the European Blocking and longest for the Zonal Regime and Greenland Blocking (see figure). Furthermore, the winter skill horizon tends to be enhanced following a strong stratospheric polar vortex but reduced following a weak one. Madden–Julian Oscillation phases 4 and 7 tend to increase and phase 2 to decrease the year‐round skill horizon.Helmholtz‐Gemeinschaft http://dx.doi.org/10.13039/50110000165

Potential Vorticity Diagnostics to Quantify Effects of Latent Heating in Extratropical Cyclones: Methodology and Application to Idealized Climate Change Simulations

Extratropical cyclones develop due to baroclinic instability, but their intensification is often substantially amplified by diabatic processes, most importantly latent heating (LH) through cloud formation. Although this amplification is well understood for individual cyclones, there is still need for a systematic and quantitative investigation of how LH affects cyclone intensification in different, particularly warmer and moister climates predicted for the future. In this thesis, we thus introduce a simple diagnostic method to quantify the contribution of LH to cyclone intensification within the potential vorticity (PV) framework. The two leading terms in the PV tendency equation, diabatic PV modification and vertical advection, are used to derive a diagnostic equation to explicitly calculate the fraction of a cyclone's positive lower-tropospheric PV anomaly caused by LH. The strength of this anomaly is strongly coupled to cyclone intensity and the associated impacts in terms of surface weather. To evaluate the performance of the diagnostic, sensitivity simulations of 12 Northern Hemisphere cyclones with artificially modified LH are carried out with a numerical weather prediction model. Based on these simulations, we demonstrate that the PV diagnostic captures the mean sensitivity of the cyclones' PV structure to LH as well as parts of the large case-to-case variability, which is a particular benefit for climatological applications. The simple and purely diagnostic characteristics of the PV diagnostic allow for a versatile application to cyclones in weather and climate model output as well as in reanalysis data, independent of their spatial and temporal resolution.It is still unclear how enhanced LH in a warmer and moister climate will affect cyclones, mainly because its intensifying effect is expected to partly counteract the effects of further changes in the meridional temperature gradient and static stability. We thus use our PV diagnostic to study the role of LH for cyclones in different idealized climate change experiments. In a first step, we perform high-resolution surrogate climate change simulations of a set of moderate and intense Northern Hemisphere cyclones, in which temperatures are spatially homogeneously increased by 4 K, keeping relative humidity constant and thus increasing specific humidity. With our PV diagnostic we can demonstrate that enhanced LH associated with the higher moisture content is the main driver for an increase in intensity and impacts of all cyclones: it amplifies their positive lower-tropospheric PV anomaly by intensifying diabatic PV generation. This amplification leads to a stronger intensification of the cyclones by enhancing cyclonic circulation in the lower troposphere, which, in most cases, results in higher cyclone intensities, stronger wind gusts at the surface, and, in combination with the higher moisture content, more precipitation. This correlation is most robust from an average perspective, but also the strong case-to-case variability of the changes can partly be explained by consistent changes in LH and thus diabatic PV generation. The experiments further indicate that extreme diabatically-driven cyclones of a present-day climate have the potential to be substantially more devastating if occurring in a warmer climate.In a second step, we investigate the role of LH for cyclones in different climates, in which changes in the thermodynamic background state are not anymore limited to an increase in temperature and thus moisture. To this end, an idealized general circulation model (GCM) in an aquaplanet setup is used to simulate a set of very cold to very warm climates, in which cyclones are identified and tracked based on their local sea level pressure minimum. With our PV diagnostic we can demonstrate that diabatic PV generation due to LH intensifies with increasing global mean surface air temperature, yielding a maximum lower-tropospheric PV anomaly in very warm climates. This increase in diabatic PV generation is stronger for intense than for moderate cyclones, and extends into the middle and upper troposphere in very warm climates. The intensity of moderate cyclones, measured in terms of lower-tropospheric relative vorticity, peaks in a climate slightly warmer than present-day and decreases toward very warm climates, which demonstrates that the increase in LH toward warmer climates is too weak to overcompensate counteracting changes in the meridional temperature gradient and static stability. In contrast, the intensity of intense cyclones peaks in a climate substantially warmer than present-day, in which also the lower-tropospheric PV anomaly reaches its maximum. The intensification of LH in intense cyclones is thus strong enough to overcompensate counteracting changes in the meridional temperature gradient and static stability, and hence drives their increase in intensity toward warmer climates.This thesis not only provides a versatile diagnostic tool to quantify the effects of LH on cyclones but also suggests enhanced LH to increase the intensity of intense cyclones in a future climate. Improving predictions of future storm track changes thus requires a better representation of LH processes in GCMs

Blended Learning in der Ausbildung von Lehrpersonen

Die Lehrerinnen- und Lehrerbildung bemüht sich vielerorts um flexiblere Studienformen mit geringeren Präsenzanteilen. Mit Ansätzen des Blended Learning können Studierende beim stärker selbstregulierten Studium unterstützt werden. Verschiedene Möglichkeiten werden vorgestellt und am Beispiel des flexiblen Studiums an der PH Zentralschweiz in Schwyz konkretisiert.Teaching education in many areas is striving towards more flexible forms of study with reduced hours of attendance. With Blended Learning approaches, students can be supported through more self-regulated periods of study. In the following various options will be presented and an example of a flexible study programme in the PH Schwyz, Central Switzerland concretized

Potential Vorticity Diagnostics to Quantify Effects of Latent Heating in Extratropical Cyclones. Part I: Methodology

Extratropical cyclones develop because of baroclinic instability, but their intensification is often substantially amplified by diabatic processes, most importantly, latent heating (LH) through cloud formation. Although this amplification is well understood for individual cyclones, there is still need for a systematic and quantitative investigation of how LH affects cyclone intensification in different, particularly warmer and moister, climates. For this purpose, the authors introduce a simple diagnostic to quantify the contribution of LH to cyclone intensification within the potential vorticity (PV) framework. The two leading terms in the PV tendency equation, diabatic PV modification and vertical advection, are used to derive a diagnostic equation to explicitly calculate the fraction of a cyclone’s positive lower-tropospheric PV anomaly caused by LH. The strength of this anomaly is strongly coupled to cyclone intensity and the associated impacts in terms of surface weather. To evaluate the performance of the diagnostic, sensitivity simulations of 12 Northern Hemisphere cyclones with artificially modified LH are carried out with a numerical weather prediction model. Based on these simulations, it is demonstrated that the PV diagnostic captures the mean sensitivity of the cyclones’ PV structure to LH as well as parts of the strong case-to-case variability. The simple and versatile PV diagnostic will be the basis for future climatological studies of LH effects on cyclone intensification

Multi‐model assessment of sub‐seasonal predictive skill for year‐round Atlantic–European weather regimes

AbstractThe prediction skill of sub‐seasonal forecast models is evaluated for seven year‐round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA‐Interim reanalysis. Results show that predicting weather regimes as a proxy for the large‐scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year‐round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so‐called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi‐model assessment of year‐round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision‐making.This study is the first sub‐seasonal multi‐model assessment of seven year‐round weather regimes in the Atlantic–European domain. Greenland blocking tends to have the longest year‐round skill horizon for all models, especially in winter. The skill is lowest for the European blocking regime for all models, followed by Scandinavian blocking. Variability in the occurrence of no regime partly explains the predictability gap between the transition seasons and winter and summer. Helmholtz Association http://dx.doi.org/10.13039/501100001656AXPO Solutions AGN/

Multi-model assessment of sub-seasonal predictive skill for year-round Atlantic-European weather regimes

The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA-Interim reanalysis. Results show that predicting weather regimes as a proxy for the large-scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year-round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so-called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi-model assessment of year-round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision-making.ISSN:0035-9009ISSN:1477-870

Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Meteorologists in the energy industry increasingly draw upon the potential for enhanced sub‐seasonal predictability of European surface weather following anomalous states of the winter stratospheric polar vortex (SPV). How the link between the SPV and the large‐scale tropospheric flow translates into forecast skill for surface weather in individual countries – a spatial scale that is particularly relevant for the energy industry – remains an open question. Here we quantify the effect of anomalously strong and weak SPV states at forecast initial time on the probabilistic extended‐range reforecast skill of the European Centre for Medium‐Range Weather Forecasts (ECMWF) in predicting country‐ and month‐ahead‐averaged anomalies of 2 m temperature, 10 m wind speed, and precipitation. After anomalous SPV states, specific surface weather anomalies emerge, which resemble the opposing phases of the North Atlantic Oscillation. We find that forecast skill is, to first order, only enhanced for countries that are entirely affected by these anomalies. However, the model has a flow‐dependent bias for 2 m temperature (T2M): it predicts the warm conditions in Western, Central and Southern Europe following strong SPV states well, but is overconfident with respect to the warm anomaly in Scandinavia. Vice versa, it predicts the cold anomaly in Scandinavia following weak SPV states well, but struggles to capture the strongly varying extent of the cold air masses into Central and Southern Europe. This tends to reduce skill (in some cases significantly) for Scandinavian countries following strong SPV states, and most pronounced, for many Central, Southern European, and Balkan countries following weak SPV states. As most of the weak SPV states are associated with sudden stratospheric warmings (SSWs), our study thus advices particular caution when interpreting sub‐seasonal regional T2M forecasts following SSWs. In contrast, it suggests that the model benefits from enhanced predictability for a considerable part of Europe following strong SPV states.ISSN:0035-9009ISSN:1477-870