Both renewable energy supply and electricity demand are strongly influenced by meteorological conditions and their evolution over time in terms of climate variability and climate change. However, ...knowledge of power output and demand forecasting beyond a few days remains poor. Current methodologies assume that long-term resource availability is constant, ignoring the fact that future wind resources could be significantly different from the past wind energy conditions. Such uncertainties create risks that affect investment in wind energy projects at the operational stage where energy yields affect cash flow and the balance of the grid. Here we assess whether sub-seasonal to seasonal climate predictions (S2S) can skilfully predict wind speed in Europe. To illustrate S2S potential applications, two periods with an unusual climate behaviour affecting the energy market will be presented. We find that wind speed forecasted using S2S exhibits predictability some weeks and months in advance in important regions for the energy sector such as the North Sea. If S2S are incorporated into planning activities for energy traders, energy producers, plant operators, plant investors, they could help improve management climate variability related risks.
An interesting topic in climate research is to determine the variability of teleconnection patterns under warming conditions. The North Atlantic Oscillation (NAO), the East Atlantic, the East ...Atlantic-West Russian and the Scandinavian (SCAND) patterns are the most important teleconnection patterns affecting Europe. Results associated with traditional methodologies for capturing these patterns, such as conventional and rotated empirical orthogonal function analysis, are difficult to intercompare when using different datasets. Therefore, we employed the method of partial least squares (PLS) regression to find a plausible representation of the teleconnections using the standard set of teleconnection patterns defined by National Oceanic and Atmospheric Administration’s Climate Prediction Center as a reference. The variability and trend of the teleconnection indices and patterns over the twentieth and twenty-first centuries were investigated for 20C3M and SRES A1B experiments from the third phase of the Coupled Model Intercomparison Project (CMIP) and compared with the twentieth-century reanalysis data. The results of this study show a positive trend for the NAO and a negative trend for the SCAND under a future climate scenario. With this study, we were able to extract consistent teleconnection patterns across different models, demonstrating the usefulness of the PLS regression in evaluating models and establishing the basis for future work using the fifth phase of CMIP data to assess atmospheric circulation trends and causes of regional climate change.
Under the pressing warming of climate, interpretable and useful-for-adaptation information has become a need in society and has promoted rapid methodological advances in climate science. One such ...advance is the development of the dynamical-storyline approach, with which the spread in multi-model scenario projections can be represented as a set of physically plausible scenarios (storylines) defined by (a) a global warming level and (b) changes in large-scale dynamical conditions that arise from climate forcing. Moreover, if changes in regional climate are assessed in such a way that they can clearly inform societal systems or management of natural ecosystems, they can potentially aid decision-making in a practical manner. Such is the aim of the climatic impact-driver (CID) framework, proposed in the Sixth Assessment Report (AR6) from the Intergovernmental Panel on Climate Change. Here, we combine the dynamical-storyline approach with the CID framework and apply them to climate services. We focus on CIDs associated with the viticulture sector and the region of the South American Andes, where currently both Argentina and Chile produce wine. We explain the benefits of this approach from a communication and adaptation perspective. In particular, we found that the CIDs related to seasonally aggregated temperatures are mainly dependent on the global warming level although in some regions, but they can also be sensitive to changes in dynamical conditions. Meanwhile, CIDs related to extreme temperature values and precipitation depend strongly on the dynamical response. We show how adaptation to climate-related compound risks can be informed by a storyline approach, given that they can address compound uncertainty in multiple locations, variables and seasons.
Climate services that can anticipate crop yields can potentially increase the resilience of food security in the face of climate change. These services are based on our understanding of how crop ...yield anomalies are related to climate anomalies, yet the share of global crop yield variability explained directly by climate factors is largely variable between regions. In Europe, France has been a major crop producer since the beginning of the 20th Century. Process based and statistical approaches to model crop yields driven by observed climate have proven highly challenging in France. This is especially due to a high regional diversity in climate but also due to environmental and agro-management factors. An additional level of uncertainty is introduced if these models are driven by seasonal-to-decadal surface climate predictions due to their low performances before the harvesting months of both wheat and maize in western Europe. On the other hand, large scale circulation patterns can possibly be better predicted than the regional surface climate, which offers the opportunity to rely on large scale circulation patterns as an alternative to local climate variables. This method assumes a certain degree of stationarity in the relationships between large scale patterns, surface climate variables, and crop yield anomalies. However, such an assumption was never tested, because of the lack of suitable long-term data. This study uses a unique dataset of subnational crop yields in France covering more than a century. By calibrating and comparing statistical models linking large scale circulation patterns and observed surface climate variables to crop yield anomalies, we can demonstrate that the relationship between large scale patterns and surface variables relevant for crop yields is not stationary. Therefore, large scale circulation pattern based crop yield forecasting methods can be adopted for seasonal predictions provided that regression parameters are constantly updated. However, the statistical crop yield models based on large-scale circulation patterns are not suitable for decadal predictions or climate change impact assessments at even longer time-scales.
This study describes the process of co-developing an operational climate forecast service for the viticulture sector. Weather and climate conditions affect grapevine development in cultivars: ...anticipating the atmospheric variables in the coming weeks and months is thus relevant for effectively managing vineyards, as impacts will be felt in wine production, biodiversity, and a wide range of related aspects. The operational service was co-developed with two types of users: impact modellers, who are the intermediary users incorporating climate forecast outputs in phenological and disease models, and end-users from the wine sector with vineyards in various European locations. For the operational service, sub-seasonal and seasonal climate forecasts were tailored considering their needs. The initial steps of the co-production process identified relevant decisions for which the service was essential and co-defined effective ways to deliver the climate information. Afterwards the climate forecasts outputs were integrated with impact model data. Substantial efforts were directed at the harmonisation of climate services information with the decision-making system of end-users. Because end-users need to navigate, comprehend, and select from various alternative options amidst uncertainty, significant emphasis has been placed on crafting the visual representation of the climate service, incorporating interactive elements, and cognitive considerations, thereby enhancing the overall user experience.
Weather and climate conditions affect the development of cultivars: phenological stages, disease risk, or wine quality. This study presents the co-production process for deploying a climate service for vineyard management. The service consists of the near-real-time operational provision of sub-seasonal and seasonal climate forecasts. This service aims to help vineyard managers make decisions by anticipating the climate conditions up to three months in advance for a set of essential climate variables. The service includes the requirements of a set of intermediary users, which are disease risk and phenology researchers who feed their impact models with the provided climate forecasts. To our knowledge, it is the first time that sub-seasonal and seasonal climate forecasts have been integrated into an operational service for vineyard management.
The service was developed during the VitiGEOSS project, the primary outcome of which is the VitiGEOSS platform: a single entry-point solution for wine producers aiming to boost vineyard sustainability. Three pilot plots are used for the service development: the Douro region in Portugal, the Catalonia region in Spain, and the Campania region in Italy. The co-production is seen as an iterative, interactive and collaborative process that brings together a plurality of knowledge sources to mutually define problems and develop usable products to address these problems. The process can be divided into three phases: initial co-exploration, co-design and co-development.
The co-exploration phase consisted of conducting a benchmark analysis, identifying available services to viticulture and highlighting the gap that the newly developed solution could fill in. In the co-design phase, more intense engagement methods were implemented to communicate the capabilities of climate forecasts and design the product’s visualisation. Finally, the co-evaluation consisted of an ad hoc and ongoing process during the recurring meetings and a final workshop conducted with direct and potential users to obtain feedback on using the platform and potential further developments.
As a result, the operational post-processing workflow of the sub-seasonal and seasonal state-of-the-art model outputs was adapted to include users’ requirements. The workflow includes the downscaling of model outputs to increase their spatial resolution, the storage of sub-seasonal climate forecasts at daily frequencies to feed phenological impact models, the provision of past climate simulations to train the impact models, the bias-adjust of climate forecasts to reduce systematic model errors, the assessment of the climate forecasts to aware users on their quality and the deployment of a server to allow access to impact modellers.
The variables provided are mean, minimum and maximum temperature, accumulated precipitation and solar radiation. The final co-designed product consists of a graphic of bars. The user can select the location and variable, and the forecasts for the next four weeks or the next three months are displayed for the sub-seasonal and seasonal climate forecasts, respectively. For each week or month, three bars show the tercile probabilities of above-normal, normal or below-normal conditions for the time of the year. The limits of the tercile categories are also displayed, which helps to understand the averaged values of the variable in the selected region and the time of the year calculated with information from the past. The probabilities of extremes, i.e. exceeding (non-exceeding) the percentile 90th (10th), are displayed as extra bars for each week and month in case the prediction is skilful and they are greater than 40%.
Last but not least, the results of the skill assessment are shown. This skill assessment consists of calculating a metric for each location, initialisation date and forecast time. When this metric, known as skill score, is positive (negative), the climate model forecast is better (worse) than the climatology (the climatology is a naive forecast which considers all categories equiprobable by definition). If the skill is negative, which means there is no proof of the added value of using the numerical model prediction, the bars are blurred, and the user can still be informed of the tercile category limits.
The service has been provided for almost two consecutive years. During this period, we have confirmed the value of some key recommendations from literature when co-producing a climate service. Especially relevant is the need to invest time and resources to conduct a good co-production process by repeating the iterative process. We also tested the idea of providing information in the format of seasonal climate forecast outlooks to end-users before the service was operational. In this way, the climate service process would be ‘slowed down’, by which the use of climate data is incorporated more slowly and allows for place-based knowledge from the resource managers to be included too.
One of the most challenging questions is the communication of the probabilistic forecasts product and their quality. The probabilistic nature of climate forecasts is sometimes understood by novice users as the incapacity to provide a deterministic forecast. Similarly, negative skill leads users to interpret the forecast fails. Overall, the perception of the service quality can be low. To avoid this perception, the co-producing process is essential to engage with users and redefine the service if possible.
In this work, we have tried different ways to overcome low-quality perception. The users requested access to the climate forecasts for their vineyard plots. For that reason, the downscaling technique was applied to increase the spatial resolution, and the bar plots were designed to show the forecast for a specific location. However, to improve the perception of the forecast quality, the forecast can be contextualised by providing the forecast in the format of a map of the surrounding areas.
Despite all these limitations, end-users reported on the extreme importance of climate information. Furthermore, end-users can benefit from getting the climate services integrated with the impact models to take maximum advantage of all services and make timely decisions, but also receiving this information in a clear, parsimonious and direct format that is intuitive and can be easily incorporated into the decision-making processes is key for the sustainability of their farm fields.
After almost two years of operational provision of the climate forecast service, some implications of our findings have been detected:●Combined downscaling and contextualisation. Downscaling techniques help to provide more accurate information at the parcel scale. Nevertheless, the spatial visualization over large regions may help to contextualize the climate forecasts, and that is also beneficial for end-user interpretation of the climate-related information.●Skill. Efforts to provide more skilful climate forecasts are required, as well as alternative information to be used in situations where skill is lacking (e.g.: past climate information). The skill assessment is crucial to inform users about forecast reliability and accuracy. It enhances user understanding and trust in the service by generating realistic expectations.●Operationalisation. Reducing the time for data processing or increasing the computational resources will allow the provision of climate forecasts that are closer to the date of production. Users will benefit from earlier access to the information than the current time-lapse.●Co-production. The co-production process ensures the service is designed based on user needs and feedback which is more likely to be adopted and effectively utilized by users. This process never ends, so, it needs to be applied if future developments or requests are included in the current service.●Support for Sustainability. End-users benefit from the integration of the climate forecast along with phenological and disease risk services. Further explorations to include more climate variables in the service and and in the impact models will be beneficial for end-users. For instance, the probabilities of extreme events help vineyard managers prepare for potential adverse conditions, while, safeguarding vineyards against weather impacts through proactive measures.●Capacity building. By training users about the nature of climate forecasts, they can enhance the preparedness and resili
X-band RF photoinjector design for the CompactLight project González-Iglesias, D.; Aksoy, A.; Esperante, D. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
10/2021, Letnik:
1014
Journal Article
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RF photoinjectors have been under development for several decades to provide the high-brightness electron beams required for X-ray Free Electron Lasers. This paper proposes a photoinjector design ...that meets the Horizon 2020 CompactLight design study requirements. It consists of a 5.6-cell, X-band (12 GHz) RF gun, an emittance-compensating solenoid and two X-band traveling-wave structures that accelerate the beam out of the space-charge-dominated regime. The RF gun is intended to operate with a cathode gradient of 200 MV/m, and the TW structures at a gradient of 65 MV/m. The shape of the gun cavity cells was optimized to reduce the peak electric surface field. An assessment of the gun RF breakdown likelihood is presented as is a multipacting analysis for the gun coaxial coupler. RF pulse heating on the gun inner surfaces is also evaluated and beam dynamics simulations of the 100MeV photoinjector are summarized.
On the Magnetic Field of a Finite Solenoid Martin-Luna, P.; Gimeno, B.; Gonzalez-Iglesias, D. ...
IEEE transactions on magnetics,
04/2023, Letnik:
59, Številka:
4
Journal Article
The magnetostatic field of a finite solenoid with infinitely thin walls carrying a dc current oriented in the azimuthal direction is calculated everywhere in space in terms of complete elliptic ...integrals by direct integration of the Biot-Savart law. The solution is particularized near the solenoid axis and in the midplane perpendicular to the axis obtaining expressions that agree with some typical approximations that are made in introductory courses of electromagnetism or in the technical literature. The range of validity of these approximations has been studied comparing them with the obtained general expression.
The objective of this work is the evaluation of the risk of suffering a multipactor discharge within an RF electron gun photoinjector. Photoinjectors are a type of source for intense electron beams, ...which are the main electron source for synchrotron light sources, such as free-electron lasers. The analyzed device consists of 1.6 cells and it has been designed to operate at the S -band. Besides, around the RF gun there is an emittance compensation solenoid, whose magnetic field prevents the growth of the electron beam emittance, and thus the degradation of the properties of the beam. The multipactor analysis is based on a set of numerical simulations by tracking the trajectories of the electron cloud in the cells of the device. To reach this aim, an in-house multipactor code was developed. Specifically, two different cases were explored: with the emittance compensation solenoid assumed to be off and with the emittance compensation solenoid in operation. For both the cases, multipactor simulations were carried out exploring different RF electric field amplitudes. Moreover, for a better understanding of the multipactor phenomenon, the resonant trajectories of the electrons and the growth rate of the electrons population are investigated.
The main aim of this work is to present a simple method, based on analytical expressions, for obtaining the temperature increase due to the Joule effect inside the metallic walls of an RF ...accelerating component. This technique relies on solving the 1-D heat-transfer equation for a thick wall, considering that the heat sources inside the wall are the ohmic losses produced by the RF electromagnetic fields penetrating the metal with finite electrical conductivity. Furthermore, it is discussed how the theoretical expressions of this method can be applied to obtain an approximation to the temperature increase in realistic 3-D RF accelerating structures, taking as an example the cavity of an RF electron photoinjector and a traveling wave linac cavity. These theoretical results have been benchmarked with numerical simulations carried out with commercial finite-element method (FEM) software, finding good agreement among them. Besides, the advantage of the analytical method with respect to the numerical simulations is evidenced. In particular, the model could be very useful during the design and optimization phase of RF accelerating structures, where many different combinations of parameters must be analyzed in order to obtain the proper working point of the device, allowing to save time and speed up the process. However, it must be mentioned that the method described in this article is intended to provide a quick approximation to the temperature increase in the device, which of course is not as accurate as the proper 3-D numerical simulations of the component.
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