Suchergebnisse

The goal of this analysis is the better understanding of how the large-scale atmospheric patterns affect the renewable resources over Europe and to investigate to what extent the dynamical predictions of the large-scale variability might be used to formulate empirical prediction of local climate conditions (relevant for the energy sector). The increasing integration of renewable energy into the power mix is making the electricity supply more vulnerable to climate variability, therefore increasing the need for skillful weather and climate predictions. Forecasting seasonal variations of energy relevant climate variables can help the transition to renewable energy and the entire energy industry to make better informed decision-making. At seasonal timescale climate variability can be described by recurring and persistent, large-scale patterns of atmospheric pressure and circulation anomalies that interest vast geographical areas. The main patterns of the North Atlantic region (Euro Atlantic Teleconnections, EATCs) drive variations in the surface climate over Europe. We analyze reanalysis dataset ERA5 and the multi-system seasonal forecast service provided by Copernicus Climate Change Service (C3S). We found that the observed EATC indices are strongly correlated with surface variables. However, the observed relationship between EATC patterns and surface impacts is not accurately reproduced by seasonal prediction systems. This opens the door to employ hybrid dynamical-statistical methods. The idea consists in combining the dynamical seasonal predictions of EATC indices with the observed relationship between EATCs and surface variables. We reconstructed the surface anomalies for multiple seasonal prediction systems and benchmarked these hybrid forecasts with the direct variable forecasts from the systems and also with the climatology. The analysis suggests that hybrid methodology can bring several improvements to the predictions of energy relevant Essential Climate Variables. ; This work was supported by the European Union's Horizon 2020 research and innovation programme [Grant Numbers. No 776787, H2020 S2S4E] and by the National Italian project PAR 2019–2021 1.8 'Energia dal Mare'. ; Peer Reviewed ; Postprint (published version)

Rainfall variability over the tropical Atlantic region is dominated by changes in the surface temperature of the surrounding oceans. In particular, the oceanic forcing over Northeast of South America is dominated by the Atlantic interhemispheric temperature gradient, which leads its predictability. Nevertheless, in recent decades, the SST influence on rainfall variability in some tropical Atlantic regions has been found to be non-stationary, with important changes of the Atlantic and Pacific influence on Sahelian rainfall which appear to be modulated at multidecadal timescales. In this work, we revisit the SST influence over Northeast of South America including the analysis of the stationarity of this relationship at interannual timescales. Principal Component Analysis has been applied to the interannual component of rainfall during the March-April-May season. Results show how the SST forcing on the first mode of rainfall variability, which is a dipole-like pattern generated by the changes in the seasonal migration of the Intertropical Convergence Zone, is different depending of the considered period. The response to the SST anomalies in the Pacific basin is opposite to the Atlantic one and affects different areas. The Atlantic Niño influences rainfall variability at the beginning of the XX century and after 1970, while the Pacific Niño plays a major role in the variability of the rainfall in the Northeast of South America from 1970 onwards. The combined effect of both basins after the 1970s amplifies the anomalous rainfall response. ; The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement n° 603521 (PREFACE project) and the Spanish project CGL2012-38923-C02-01. ; Peer reviewed

Rainfall variability over the tropical Atlantic region is dominated by changes in the surface temperature of the surrounding oceans. In particular, the oceanic forcing over Northeast of South America is dominated by the Atlantic interhemispheric temperature gradient, which leads its predictability. Nevertheless, in recent decades, the SST influence on rainfall variability in some tropical Atlantic regions has been found to be non-stationary, with important changes of the Atlantic and Pacific influence on Sahelian rainfall which appear to be modulated at multidecadal timescales. In this work, we revisit the SST influence over Northeast of South America including the analysis of the stationarity of this relationship at interannual timescales. Principal Component Analysis has been applied to the interannual component of rainfall during the March-April-May season. Results show how the SST forcing on the first mode of rainfall variability, which is a dipole-like pattern generated by the changes in the seasonal migration of the Intertropical Convergence Zone, is different depending of the considered period. The response to the SST anomalies in the Pacific basin is opposite to the Atlantic one and affects different areas. The Atlantic Niño influences rainfall variability at the beginning of the XX century and after 1970, while the Pacific Niño plays a major role in the variability of the rainfall in the Northeast of South America from 1970 onwards. The combined effect of both basins after the 1970s amplifies the anomalous rainfall response. ; The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement n° 603521 (PREFACE project) and the Spanish project CGL2012-38923-C02-01. ; Peer reviewed ; Peer Reviewed

Seasonal mean atmospheric circulation in Europe can vary substantially from year to year. This diversity of conditions impacts many socioeconomic sectors. Teleconnection indices can be used to characterize this seasonal variability, while seasonal forecasts of those indices offer the opportunity to take adaptation actions a few months in advance. For instance, the North Atlantic Oscillation has proven useful as a proxy for atmospheric effects in several sectors, and dynamical forecasts of its evolution in winter have been shown skillful. However the NAO only characterizes part of this seasonal circulation anomalies, and other teleconnections such as the East Atlantic, the East Atlantic Western Russia or the Scandinavian Pattern also play an important role in shaping atmospheric conditions in the continent throughout the year. This paper explores the quality of seasonal forecasts of these four teleconnection indices for the four seasons of the year, derived from five different seasonal prediction systems. We find that several teleconnection indices can be skillfully predicted in advance in winter, spring and summer. We also show that there is no single prediction system that performs better than the others for all seasons and teleconnections, and that a multi-system approach produces results that are as good as the best of the systems. ; The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement n° 776787 (S2S4E). ; Peer Reviewed ; Postprint (published version)

Subseasonal predictions bridge the gap between medium-range weather forecasts and seasonal climate predictions. This time scale is crucial for operations and planning in many sectors such as energy and agriculture. For users to trust these predictions and efficiently make use of them in decision-making, the quality of predicted near-surface parameters needs to be systematically assessed. However, the method to follow in a probabilistic evaluation of subseasonal predictions is not trivial. This study aims to offer an illustration of the impact that the verification setup might have on the calculation of the skill scores, thus providing some guidelines for subseasonal forecast evaluation. For this, several forecast verification setups to calculate the fair ranked probability skill score for tercile categories have been designed. These setups use different number of samples to compute the fair RPSS as well as different ways to define the climatology, characterized by different time periods to average (week or month). These setups have been tested by evaluating 2-m temperature in ECMWF-Ext-ENS 20-yr hindcasts for all of the initializations in 2016 against the ERA-Interim reanalysis. Then, the implications on skill score values of each of the setups are analyzed. Results show that to obtain a robust skill score several start dates need to be employed. It is also shown that a constant monthly climatology over each calendar month may introduce spurious skill score associated with the seasonal cycle. A weekly climatology bears similar results to a monthly running-window climatology; however, the latter provides a better reference climatology when bias adjustment is applied. ; The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grants 7767874 (S2S4E) and 641811 (IMPREX). We acknowledge the ECMWF for producing the ERA-Interim reanalysis and ECMWF-Ext-ENS predictions and the WWRP/WCRP S2S Project for making ECMWF-Ext-ENS predictions available through its database (http://s2sprediction.net/). We acknowledge the use of the SpecsVerification (https://CRAN.R-project.org/package=SpecsVerification), s2dverification https://CRAN.R-project.org/package=s2dverification), and startR (https://CRAN.R-project.org/package=startR) R software packages. The authors thank Pierre-Antoine Bretonnière, Margarida Samsó, and Julia Giner for data downloading and processing and Nicolau Manubens, An Chi-Ho, Núria Pérez-Zanón, Javier Vegas, and Lluís Palma for technical support. ; Peer Reviewed ; Postprint (published version)

Decadal climate predictions are being increasingly used by stakeholders interested in the evolution of climate over the coming decade. However, investigating the added value of those initialized decadal predictions over other sources of information typically used by stakeholders generally relies on forecast accuracy, while probabilistic aspects, although crucial to users, are often overlooked. In this study, the quality of the near-surface air temperature from initialized predictions has been assessed in terms of reliability, an essential characteristic of climate simulation ensembles, and compared to the reliability of noninitialized simulations performed with the same model ensembles. Here, reliability is defined as the capability to obtain a true estimate of the forecast uncertainty from the ensemble spread. We show the limited added value of initialization in terms of reliability, the initialized predictions being significantly more reliable than their noninitialized counterparts only for specific regions and the first forecast year. By analyzing reliability for different forecast system ensembles, we further highlight the fact that the combination of models seems to play a more important role than the ensemble size of each individual forecast system. This is due to sampling different model errors related to model physics, numerics, and initialization approaches involved in the multimodel, allowing for a certain level of error compensation. Finally, this study demonstrates that all forecast system ensembles are affected by systematic biases and dispersion errors that affect the reliability. This set of errors makes bias correction and calibration necessary to obtain reliable estimates of forecast probabilities that can be useful to stakeholders. ; The EUCP project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement 776613. The research leading to these results has also received funding from the Spanish Ministerio de Ciencia, Innovación y Universidades as part of the CLINSA project with funding reference CGL2017-85791-R. MGD is also supported by the Spanish Ministry of Science, Innovation and Universities Grant RYC-2017-22964. BSM acknowledges financial support from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement 713673 and from a fellowship of "la Caixa" Foundation (ID 100010434). The fellowship code is LCF/BQ/IN17/11620038. SW has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433. We acknowledge the use of the s2dverification (Manubens et al. 2018), startR (BSC/CNS and Manubens 2020), SpecsVerification (Siegert 2017), CSTools (Perez-Zanon et al. 2019), ClimProjDiags (BSC/CNS et al. 2020), and boot (Davison and Hinkley 1997; Canty and Ripley 2020) R (R Core Team 2013) software packages. We also thank Nicolau Manubens, An-Chi Ho, Pablo Ortega, Rashed Mahmood, Yohan Ruprich-Robert, and Roberto Bilbao from the BSC for their technical and scientific support. We further express our gratitude to Charles Pelletier from ELI for his careful reading of the manuscript. Finally, we would like to thank Antje Weisheimer (University of Oxford) and two anonymous reviewers for constructive comments that helped us greatly improve this article. ; Peer Reviewed ; Postprint (published version)

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers. ; The authors wish to acknowledge all of those who contributed indirectly to the development of the EUPORIAS prototypes, through scientific discussion, review, data provision, stakeholder engagement and facilitation: for SPRINT, Adam Scaife, Anca Brookshaw, Alberto Arribas, Emily Wallace, Jeff Knight, Margaret Gordon, Kate Brown, Brent Walker, Mathew Richardson, Jodie Wild, and the DfT-led stakeholder group; for RESILIENCE, Melanie Davis for conceiving the prototype and for her vision on Climate Services. In the LMTool, Clinton Devon Estates, the National Farmers Union, and all the farmers involved in the development of the tool. The UK Government Department for Transport is acknowledged for providing financial support, in parallel to that received from EUPORIAS, for the SPRINT prototype. The visualisation, project UKKO, within RESILIENCE prototype was done by Moritz Stefaner. EUPORIAS was funded by the European Commission through the 7th Framework Programme for Research, grant agreement 308291. ; Peer Reviewed ; Postprint (published version)

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers. ; The authors wish to acknowledge all of those who contributed indirectly to the development of the EUPORIAS prototypes, through scientific discussion, review, data provision, stakeholder engagement and facilitation: for SPRINT, Adam Scaife, Anca Brookshaw, Alberto Arribas, Emily Wallace, Jeff Knight, Margaret Gordon, Kate Brown, Brent Walker, Mathew Richardson, Jodie Wild, and the DfT-led stakeholder group; for RESILIENCE, Melanie Davis for conceiving the prototype and for her vision on Climate Services. In the LMTool, Clinton Devon Estates, the National Farmers Union, and all the farmers involved in the development of the tool. The UK Government Department for Transport is acknowledged for providing financial support, in parallel to that received from EUPORIAS, for the SPRINT prototype. The visualisation, project UKKO, within RESILIENCE prototype was done by Moritz Stefaner. EUPORIAS was funded by the European Commission through the 7th Framework Programme for Research, grant agreement 308291. ; Peer Reviewed ; Postprint (published version)

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers. ; The authors wish to acknowledge all of those who contributed indirectly to the development of the EUPORIAS prototypes, through scientific discussion, review, data provision, stakeholder engagement and facilitation: for SPRINT, Adam Scaife, Anca Brookshaw, Alberto Arribas, Emily Wallace, Jeff Knight, Margaret Gordon, Kate Brown, Brent Walker, Mathew Richardson, Jodie Wild, and the DfT-led stakeholder group; for RESILIENCE, Melanie Davis for conceiving the prototype and for her vision on Climate Services. In the LMTool, Clinton Devon Estates, the National Farmers Union, and all the farmers involved in the development of the tool. The UK Government Department for Transport is acknowledged for providing financial support, in parallel to that received from EUPORIAS, for the SPRINT prototype. The visualisation, project UKKO, within RESILIENCE prototype was done by Moritz Stefaner. EUPORIAS was funded by the European Commission through the 7th Framework Programme for Research, grant agreement 308291. ; Peer Reviewed ; Postprint (published version)

The international effort toward climate services, epitomised by the development of the Global Framework for Climate Services and, more recently the launch of Copernicus Climate Change Service has renewed interest in the users and the role they can play in shaping the services they will eventually use. Here we critically analyse the results of the five climate service prototypes that were developed as part of the EU funded project EUPORIAS. Starting from the experience acquired in each of the projects we attempt to distil a few key lessons which, we believe, will be relevant to the wider community of climate service developers. ; The authors wish to acknowledge all of those who contributed indirectly to the development of the EUPORIAS prototypes, through scientific discussion, review, data provision, stakeholder engagement and facilitation: for SPRINT, Adam Scaife, Anca Brookshaw, Alberto Arribas, Emily Wallace, Jeff Knight, Margaret Gordon, Kate Brown, Brent Walker, Mathew Richardson, Jodie Wild, and the DfT-led stakeholder group; for RESILIENCE, Melanie Davis for conceiving the prototype and for her vision on Climate Services. In the LMTool, Clinton Devon Estates, the National Farmers Union, and all the farmers involved in the development of the tool. The UK Government Department for Transport is acknowledged for providing financial support, in parallel to that received from EUPORIAS, for the SPRINT prototype. The visualisation, project UKKO, within RESILIENCE prototype was done by Moritz Stefaner. EUPORIAS was funded by the European Commission through the 7th Framework Programme for Research, grant agreement 308291. ; Peer Reviewed ; Postprint (published version)