Zukünftige Änderungen der Windenergie-Potentiale über Europa in einem großen CMIP5 Multi-Modell Ensemble

KlimafolgenIn dieser Studie wird ein statistisch-dynamisches (SDD) Regionalisierungs-Verfahren verwendet, welches es ermöglicht regionale Windenergie-Potenziale (WEP) für das gegenwärtige und das zukünftige Klima aus einem sehr großen GCM Ensemble zu bestimmen. Das SDD benutzt zum einen eine Wetterlagen-Klassifizierung, und zum anderen das Regional-Modell COSMO-CLM (0.22°) um regionale Windfelder einzelner Repräsentanten dieser Wetterlagen zu simulieren. Insgesamt werden 22 CMIP5 Modelle in dieser Studie betrachtet. Zukünftige Änderungen der WEP über Europa in diesen 22 CMIP5 Modellen werden für die kommenden Jahrzehnte (2021-2060) sowie für die zweite Hälfte des 21. Jahrhunderts (2061-2100) in einem RCP4.5 und einem RCP8.5 Szenario bestimmt. Das CMIP5 Ensemble-Mittel weist für beide zukünftigen Zeiträume und Szenarien auf eine Zunahme der jährlichen WEP über Nord- und Mitteleuropa und auf eine Abnahme über Südeuropa hin. Große Unterschiede zeigen sich bei der Betrachtung der einzelnen Modelle, sowohl im Hinblick auf die Stärke als auch auf das Vorzeichen der Änderung. Eindeutigere Ergebnisse zeigen sich hingegen für spezielle Jahreszeiten. Vor allem für die 2. Hälfte des 21. Jahrhunderts wird für die meisten Modelle über Nord- und Zentraleuropa mehr WEP im Winter und weniger WEP im Sommer festgestellt. Dies hätte eine starke Zunahme der intra-annualen Variabilität zur Folge. Generell sind die genannten Änderungen für 2061-2100 und dem RCP8.5 Szenario stärker als für 2021-2060 und dem RCP4.5 Szenario. Sehr große Unsicherheiten zwischen den CMIP5 Modellen herrschen bezüglich der inter-annualen Variabilität von WEP in einem zukünftigen Klima. Die Zukunfts-Prognosen variieren je nach Modell zwischen einer Abnahme der Variabilität um mehr als 40% und einer Zunahme von knapp 50%. Auch innerhalb einzelner Modelle zeigen sich je nach zukünftigem Zeitraum oder Szenario zum Teil gegenteilige Trends. Insgesamt zeigt diese Studie, dass eine generelle Änderung der WEP über Europa in einem zukünftigen Klima wahrscheinlich ist. Nichtsdestoweniger sind aufgrund der gefundenen Unsicherheiten weitere Untersuchungen mit Multi-Modell Ensembles nötig und sinnvoll

Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

Decadal predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy and society. The present study examines the decadal predictability of regional wind speed and wind energy potentials in three generations of the MiKlip (‘Mittelfristige Klimaprognosen’) decadal prediction system. The system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM), and the three generations differ primarily in the ocean initialisation. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess the forecast skill for 10 m wind speeds and wind energy output (Eout) over Central Europe with lead times from one year to one decade. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD-simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. This forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skills of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer and persist longest in autumn. A large-scale westerly weather type with strong pressure gradients over Central Europe is identified as potential source of the skill for wind energy potentials, showing a similar forecast skill and a high correlation with Eout anomalies. These results are promising towards the establishment of a decadal prediction system for wind energy applications over Central Europe

Non‐linear plant‐plant interactions modulate impact of extreme drought and recovery on a Mediterranean ecosystem

Interaction effects of different stressors, such as extreme drought and plant invasion, can have detrimental effects on ecosystem functioning and recovery after drought. With ongoing climate change and increasing plant invasion, there is an urgent need to predict the short- and long-term interaction impacts of these stressors on ecosystems. We established a combined precipitation exclusion and shrub invasion (Cistus ladanifer) experiment in a Mediterranean cork oak (Quercus suber) ecosystem with four treatments: (1) Q. suber control; (2) Q. suber with rain exclusion; (3) Q. suber invaded by shrubs; and (4) Q. suber with rain exclusion In an average precipitation year, the interaction effects of both stressors were neutral. However, the combination of imposed drought and shrub invasion led to amplifying interaction effects during an extreme drought by strongly reducing tree transpiration. Contrarily, the imposed drought reduced the competitiveness of the shrubs in the following recovery period, which buffered the negative effects of shrub invasion on Q. suber. Our results demonstrate the highly dynamic and nonlinear effects of interacting stressors on ecosystems and urges for further investigations on biotic interactions in a context of climate change pressures

Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe

In recent years, several decadal prediction systems have been developed to provide multi-year predictions of the climate for the next 5–10 years. On the global scale, high decadal predictability has been identified for the North Atlantic sector, often extending over Europe. The first full regional hindcast ensemble, derived from dynamical downscaling, was produced within the German MiKlip project (‘decadal predictions’). The ensemble features annual starting dates from 1960 to 2017, with 10 decadal hindcasts per starting year. The global component of the prediction system uses the MPI-ESM-LR and the downscaling is performed with the regional climate model COSMO-CLM (CCLM). The present study focusses on a range of aspects dealing with the skill and added value of regional decadal temperature predictions over Europe. The results substantiate the added value of the regional hindcasts compared to the forcing global model as well as to un-initialized simulations. The results show that the hindcasts are skilful both for annual and seasonal means, and that the scores are comparable for different observational reference data sets. The predictive skill increases from earlier to more recent start-years. A recalibration of the simulation data generally improves the skill further, which can also be transferred to more user-relevant variables and extreme values like daily maximum temperatures and heating degree-days. These results provide evidence of the potential for the regional climate predictions to provide valuable climate information on the Abstract Formulae display:MathJax Logo? In recent years, several decadal prediction systems have been developed to provide multi-year predictions of the climate for the next 5–10 years. On the global scale, high decadal predictability has been identified for the North Atlantic sector, often extending over Europe. The first full regional hindcast ensemble, derived from dynamical downscaling, was produced within the German MiKlip project (‘decadal predictions’). The ensemble features annual starting dates from 1960 to 2017, with 10 decadal hindcasts per starting year. The global component of the prediction system uses the MPI-ESM-LR and the downscaling is performed with the regional climate model COSMO-CLM (CCLM). The present study focusses on a range of aspects dealing with the skill and added value of regional decadal temperature predictions over Europe. The results substantiate the added value of the regional hindcasts compared to the forcing global model as well as to un-initialized simulations. The results show that the hindcasts are skilful both for annual and seasonal means, and that the scores are comparable for different observational reference data sets. The predictive skill increases from earlier to more recent start-years. A recalibration of the simulation data generally improves the skill further, which can also be transferred to more user-relevant variables and extreme values like daily maximum temperatures and heating degree-days. These results provide evidence of the potential for the regional climate predictions to provide valuable climate information on the decadal time-scale to users

Impact of climate change on backup energy and storage needs in wind-dominated power systems in Europe

The high temporal variability of wind power generation represents a major challenge for the realization of a sustainable energy supply. Large backup and storage facilities are necessary to secure the supply in periods of low renewable generation, especially in countries with a high share of renewables. We show that strong climate change is likely to impede the system integration of intermittent wind energy. To this end, we analyze the temporal characteristics of wind power generation based on high-resolution climate projections for Europe and uncover a robust increase of backup energy and storage needs in most of Central, Northern and North-Western Europe. This effect can be traced back to an increase of the likelihood for long periods of low wind generation and an increase in the seasonal wind variability

The regional MiKlip decadal prediction system for Europe: Hindcast skill for extremes and user‐oriented variables

Regional climate predictions for the next decade are gaining importance, as this period falls within the planning horizon of politics, economy, and society. The potential predictability of climate indices or extremes at the regional scale is of particular interest. The German MiKlip project (“mid‐term climate forecast”) developed the first regional decadal prediction system for Europe at 0.44° resolution, based on the regional model COSMO‐CLM using global MPI‐ESM simulations as boundary conditions. We analyse the skill of this regional system focussing on extremes and user‐oriented variables. The considered quantities are related to temperature extremes, heavy precipitation, wind impacts, and the agronomy sector. Variables related to temperature (e.g., frost days, heat wave days) show high predictive skill (anomaly correlation up to 0.9) with very little dependence on lead‐time, and the skill patterns are spatially robust. The skill patterns for precipitation‐related variables (e.g., heavy precipitation days) and wind‐based indices (like storm days) are less skilful and more heterogeneous, particularly for the latter. Quantities related to the agronomy sector (e.g., growing degree days) show high predictive skill, comparable to temperature. Overall, we provide evidence that decadal predictive skill can be generally found at the regional scale also for extremes and user‐oriented variables, demonstrating how the utility of decadal predictions can be substantially enhanced. This is a very promising first step towards impact‐related modelling at the regional scale and the development of individual user‐oriented products for stakeholders.The skill of the regional MiKlip decadal prediction system is analysed focussing on extremes and user‐oriented variables. Variables related to temperature extremes and the agronomy sector show high predictive skill with very little dependence on lead‐time. Skill patterns for precipitation‐related variables and wind‐based indices are less skilful and more heterogeneous, especially for the latter.The study was mainly funded by the Bundesministerium für Bildung und Forschung (BMBF) under project FONA MiKlip‐II http://dx.doi.org/10.13039/501100002347AXA Research Fund http://dx.doi.org/10.13039/50110000196