Early instrumental meteorological observations are essential for identifying and characterizing extreme climate events prior to the modern observational era, particularly in regions where historical data are scarce. This study documents a remarkable late-spring heatwave using newly recovered daily temperature observations from Ferrol (northwestern Spain) for the period 1792–1795, retrieved from the Historical Archive of the Royal Institute and Observatory of the Spanish Navy. Despite the temporal limitations of this early dataset, its daily resolution enables a detailed analysis of short-term climatic variability and extreme temperature events. The analysis reveals an extraordinary warm episode in late May 1795, characterized by sustained positive temperature anomalies that stand out clearly against the surrounding days. Comparison with the modern climate indicates that the event was exceptional even by present-day standards, with mean temperatures approximately 2 °C above the current 95th percentile. To assess the spatial extent of the heatwave, we compared the Ferrol data with contemporaneous instrumental records from Madrid, Barcelona, and Cádiz. All three locations exhibit synchronous, pronounced positive anomalies, demonstrating that the 1795 event was a large-scale phenomenon affecting most of the Iberian Peninsula. This study highlights the critical value of historical data rescue for contextualizing modern climate extremes and extending our understanding of regional climate variability.

General Circulation Models provide comprehensive climate projections but are limited by their coarse spatial resolution. Regional Climate Models are therefore used to obtain higher-resolution simulations for assessing regional climate change impacts through dynamical downscaling. This is typically performed using continuous simulations over a selected period. Alternatively, short, frequently reinitialized simulations can be applied to reduce error accumulation and computational cost via parallelization, although they may limit the development of some atmospheric processes. In this study, the WRF model was applied using both continuous and daily reinitialized downscaling approaches. Simulations were driven by ERA5 and CMIP6 data at spatial resolutions of 1 degrees and 1.25 degrees, respectively, over a domain spanning 115 degrees W-40 degrees E and 20 degrees N-60 degrees N, and downscaled to 20 km. Model outputs were evaluated against ERA5 data at 0.25 degrees resolution. The analysis considered wind speed, air temperature, humidity, precipitation, surface pressure, and solar radiation. Both downscaling techniques showed good to excellent agreement with the reference data, though neither reliably reproduced wind speed or surface pressure in mountainous regions. In ERA5-driven simulations, the reinitialized approach performed better for air temperature and humidity in coastal areas, while the continuous method slightly improved solar radiation estimates. For CMIP6-driven simulations, results were largely similar, except for marginally better solar radiation performance over land with the continuous approach. The reinitialized method required approximately 30 times less computational time while maintaining comparable accuracy, strongly supporting its recommendation as the preferred approach when both performance and efficiency are considered. Practical Implications: High-resolution climate information is a key component of climate services that support policy making, risk management, and sectoral planning. Regional climate simulations are widely used by public agencies and practitioners to assess climate variability, extremes, and future change at spatial scales relevant for decision making. However, the computational cost associated with producing such datasets often constrains their operational use, limiting spatial coverage, ensemble size, update frequency, or the range of variables that can be delivered to users. This study provides practical guidance on how these limitations can be reduced by comparing two dynamical downscaling strategies commonly used in climate services: continuous and daily reinitialized simulations. The results show that daily reinitialized dynamical downscaling can generate climate information with accuracy comparable to that of continuous simulations, while reducing computational time by approximately a factor of 30. This efficiency gain has direct implications for climate service providers, including national meteorological services, climate data centers, and publicly funded research infrastructures. By adopting a reinitialized approach, these institutions can substantially expand their modeling capabilities without increasing computational resources, enabling larger ensembles, higher spatial resolution, broader domains, or more frequent updates of climate products. For most atmospheric variables relevant to climate services-such as air temperature, humidity, precipitation, solar radiation, and wind speed-both downscaling approaches reproduce large-scale climatological patterns and variability well. Importantly for practitioners, the reinitialized simulations do not introduce systematic discontinuities in time series when an adequate spin-up period is used. This ensures that the resulting datasets are suitable for applications requiring temporal consistency, including the calculation of climate indicators, assessment of trends, and analysis of extreme or compound events. The study also highlights limitations that are relevant for practical use. Both downscaling strategies show reduced reliability for near-surface wind speed and surface pressure in mountainous regions. Users applying downscaled climate data in complex terrain, for example in infrastructure design, hazard assessment, or renewable energy planning, should therefore interpret these variables with caution and consider complementary methods such as bias adjustment, ensemble interpretation, or the use of additional data sources. Overall, this study supports the use of daily reinitialized dynamical downscaling as a practical and efficient approach for many climate service applications. By maintaining comparable accuracy while dramatically reducing computational cost, this method can enhance the scalability, accessibility, and sustainability of climate services, ultimately improving the delivery of actionable climate information to policy makers and practitioners.

Accurate topographic representation is critical for reliable hydraulic modelling of flood events. Considering that several worldwide areas lacks of high resolution topographic models, this study assesses the impact of global digital elevation model (DEM) accuracy on simulated flood extent and water depth using Iber+, a validated twodimensional hydraulic model. Five freely available global DEMs-ASTER, AW3D30, EU_DEM, COP30, and SRTM-were evaluated across three flood-prone areas in Spain (Villan & uacute;a, Lugo, and Badajoz) that exhibit contrasting hydrological and topographic conditions. A high-resolution LiDAR-based DEM (5 m) provided by the Spanish National Geographic Institute served as a reference. Simulations were performed for 10-, 100-, and 500year return periods, enabling a comparative analysis under diverse flood scenarios. Results show that AW3D30, EU_DEM, and SRTM provide the most accurate flood extents in Villan & uacute;a and Lugo, while EU_DEM and COP30 perform best in Badajoz. ASTER consistently yields the lowest accuracy in both flood extent and water depth prediction. For water depth estimation, COP30, EU_DEM, and AW3D30 achieve the lowest mean relative differences, with only a slight increase for extreme events. Overall, model accuracy tends to improve with longer return periods. The findings highlight that no single global DEM consistently outperforms others, emphasizing the need for context-specific evaluations. Nevertheless, when considering overall performance - that is, the ability to reproduce both flood extent and associated water depths - AW3D30, COP30, and EU_DEM emerge as the most reliable options for flood modelling using Iber+, supporting more accurate and cost-effective flood hazard assessments in data-scarce regions.

Climate change is increasingly affecting the aquaculture sector, particularly in estuarine systems that support high-value production. In the Galician Rías Baixas, where shellfish farming is a cornerstone of the coastal economy, rising sea temperatures, sea-level rise, and changing precipitation patterns pose significant risks to mussel aquaculture. This study presents a spatially explicit Aquaculture Suitability Similarity Index (ASI) designed to identify alternative cultivation areas that replicate the environmental and logistical characteristics of historically successful mussel farms. The ASI integrates a set of environmental variables (water temperature, salinity, biogeochemical quality, current velocity, and wave height) and technical constraints (depth and distance to port), with factor weights derived via expert elicitation using the Delphi method. Results show that most waters are highly similar to current farming areas, suggesting strong potential for spatial expansion or relocation. In contrast, areas near the mouths of the rías and the adjacent continental shelf show lower suitability due to greater oceanic exposure and associated logistical challenges. The ASI provides a robust, transferable tool to inform aquaculture spatial planning and climate adaptation strategies. Its methodological framework can be adapted to other regions and species, supporting evidence-based decision-making for sustainable aquaculture development.

Spain has taken a significant stride towards its goal of installing 1 to 3 GW of floating offshore wind capacity by 2030. This was achieved through the implementation of a Maritime Spatial Planning (MSP) covering 19 designated areas, where it is expected the installation of offshore wind farms in the upcoming years. Therefore, it is of interest analysing the impact of climate change on offshore wind resource in these areas. To achieve a sufficiently high spatial resolution for this study, a dynamic downscaling of a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project (CMIP6) was conducted using the Weather Research and Forecasting (WRF) model in the Spanish territorial waters, encompassing the Iberian Peninsula, Balearic Islands, and Canary Islands. Thus, wind data were obtained from the latest climate projections, with a 10-km spatial resolution and a 6-hour temporal resolution. The results were compared, for a historical period from 1985 to 2014, with data from the ERA5 reanalysis database and with observational data from buoys. The results of this validation process showed a great accuracy in the dynamical downscaling performed, generally better than when using data from the Coordinated Regional Climate Downscaling Experiment (CORDEX), which performed dynamical downscaling on data from several CMIP5 climate models. Future projections, from 2015 to 2100, were assessed under the Shared Socioeconomic Pathways (SSP) 2-4.5 and 5-8.5 scenarios. The findings of this study indicate a projected growth in Spain's offshore wind energy potential, especially in the Atlantic Ocean and around the Canary Islands. Using wind speed data from simulations carried out with the WRF atmospheric model, the offshore wind energy resource was classified in the 19 areas involved in de Spanish MSP. This classification considered the wind power density but also factors such as resource stability, environmental risks, and installation costs. The results reveal significant diversity in wind resource classification within potential offshore wind farm areas, ranging from "fair" (3/7) to "outstanding" (6/7). The most promising areas for offshore wind farm development in the future are situated in the northwest of the Iberian Peninsula and the Canary Islands. The identification of the most cost-effective solutions in each area involves determining the optimal combination of rated power and the number of turbines and comparing them across different locations to pinpoint the most economical sites for offshore wind energy exploitation. This economic analysis was done for a 25-year near-future period under the SSP 2-4.5 scenario, aligning with the expected operational lifespan of wind farms. This study includes the calculation of the Levelized Cost of Energy (LCOE) index, which gives an indication of the minimal price at which the electricity should be sold in order for the project to be profitable. The results highlight that the LCOE is lower for farms with a higher number of wind turbines featuring increased rated power. While the Canary Islands exhibit the most economically advantageous prices overall, other regions such as Galicia and Cataluña also boast promising areas.

Spain took a significant step towards achieving its goal of installing 1 to 3 GW of floating offshore wind capacity by 2030, by implementing Maritime Spatial Planning encompassing 19 designated areas. Therefore, it is essential to calculate the Levelized Cost of Energy for strategically designed floating wind farms, taking into account the number and capacity of wind turbines. To find the most cost-effective offshore wind energy sites, the optimal combination of rated power and number of turbines was determined and compared across different locations. This analysis used downscaled wind data from the 6th phase of the Coupled Model Intercomparison Project multi-model ensemble, covering the 2025-2049 period under the Shared Socioeconomic Pathway 2-4.5 climate scenario, matching the expected lifespan of wind farms. The results show that the Levelized Cost of Energy is lower for farms with a higher number of wind turbines with increased rated power. The areas located in the Canary Islands exhibit the most economically advantageous prices overall, ranging from 100 to 135 /MWh. Regions such as Galicia and Cataluna also present a high diversity in prices (105-160 /MWh), while Andalucia shows moderate values (135-140 /MWh).

The heightened occurrence of marine heatwaves (MHWs) attributed to climate change has garnered significant attention, primarily due to its profound impacts on marine ecosystems. Eastern Boundary Upwelling Systems, recognized as high-productivity oceanic areas, have emerged as crucial thermal refuges mitigating the effects of global warming, thereby safeguarding marine fauna and flora. Acknowledging the synergies between MHWs and upwelling becomes pivotal in this context. The main objective of this study is to assess the unprecedented extreme SSTs observed in the North Atlantic Ocean throughout 2023 which represent a departure from the norms observed in the past 40 years of satellite data, resulting in quasi-permanent MHW conditions. Additionally, the investigation aims to delineate the influence of upwelling on the disparities between oceanic and coastal SST throughout the Canary Upwelling System. For this purpose, SST and wind data from OISST ¼ and ERA5 databases, respectively, have been used to calculate SST extremes and differences between coast and ocean as well as Upwelling Index (UI) values from 1982 to 2023. Despite the overall increase in oceanic and nearshore SST during 2023, substantial differences between coastal and oceanic temperatures were noted compared to the 1982-2023 period average. Moreover, distinct upwelling regimes along the Canary Upwelling System exhibited discernible variations in the impact of upwelling on coastal SST. Nonetheless, the influence of upwelling mitigated warming nearshore more effectively than offshore, underscoring its capacity to modulate climate change impacts, even under the extreme SST conditions arising from the unprecedented 2023.

The economic profitability of future wave energy production along the Galician coast is assessed by analyzing the Levelized Cost of Energy (LCoE) under different Capital Expenditure (CapEx) scenarios and two discounts rates (5% and 10%). Wave resources for the near future under the RCP8.5 scenario are downscaled using SWAN, providing up to 75 m spatial resolution in coastal areas. The study’s goal is to enhance the cost-effectiveness by selecting the most suitable wave energy converter (WEC) for each location. Fourteen WECs operating at different depths are considered. This analysis reveals that the Atargis device boasts the lowest LCoE for 64.2% of the coastal area, mainly in deep waters, with an LCoE of 77 €/MWh. In addition, the Oyster and Wave Dragon devices exhibit the lowest LCoE for 12.4% and 15.0% of the coastal area, respectively, excelling in shallow waters and near the coast, with values of 50 €/MWh and 97 €/MWh. These findings demonstrate the profitability of wave energy production along the Galician coast, even when considering a more conservative CapEx of 3 M€/MW, resulting in a cost of 140 €/MWh. This conclusion takes into account the evolving electricity prices in Spain, which reached 0.2068 €/kWh in the second half of 2023.

The increment of the share of renewable energies in the global mix implies that all renewable energies must be exploited. In this sense, it is necessary to make significant research and investment effort in the particular case of wave energy to reach the degree of maturity of other marine energies in the near future. Apart from the inherent factors that hinder the development of wave energy, such as the non-existence of a market-leading type of capturing device, uncertainties about the available future resource also hamper its growth. In this article, a review of the procedures followed in the literature to deal with the future wave energy resources and their subsequent exploitation is described. These procedures include the evaluation of the best future atmospheric models to drive wave models, the different downscaling techniques to evaluate the resource in large regions with high spatial resolution, and the analysis of the variability of the future energy resource and its future exploitability in a certain region taking into account different types of devices. Additionally, the current state of the art of previous studies dealing with future wave energy resources for different locations worldwide is described. Despite the difficulties involved in studying future wave energy resources, the high technological readiness level of the offshore wind industry, the creation of power generation farms with combined technologies, and the growth of marine aquaculture in the coming years could generate synergies that provide the definitive impulse to achieve the necessary technological development.

Abstract. The analysis of climate behavior over centuries reveals how environmental forces shaped society and helps contextualize modern climate trends and future projections. The torrential rains in several regions of the Eastern Atlantic during 1768–1769 triggered the last and most severe agricultural crisis in Galicia and Northern Portugal, resulting in unprecedented mortality. The atmospheric conditions of this historical episode were analyzed using the EKF400v2 paleo-reanalysis dataset, which spans from the 17th century to the early 21st century. From June 1768 to May 1769, the rainfall anomaly in Galicia and Northern Portugal was positive in 11 out of 12 months. Although the rainfall in Northern Portugal appeared less intense than in Galicia, June 1768 had the highest positive rain anomaly of the century, and September 1768 had the second-highest. This excess precipitation agrees with the occurrence of pro-Serenitate rogations and written testimonies indicating an unusually high number of rainy days between June 1768 and May 1769. The atmospheric synoptic patterns for the rainiest months show negative anomalies in both sea level pressure and 500 hPa geopotential height in the northeast Atlantic. These patterns are associated with troughs in the northeastern Atlantic that induce the formation of surface low-pressure systems and hinder the eastward progression of anticyclones into the region, resulting in more frequent episodes of rain and cold than usual.

Estuaries are dynamic and resource-rich ecosystems renowned for their high productivity and ecological significance. The Rías Baixas, located in the northwest of the Iberian Peninsula, consist of four highly productive estuaries that support the region’s economy through key fisheries and aquaculture activities. Numerical modeling of biogeochemical processes in the rias is essential to address environmental and anthropogenic pressures, particularly in areas facing intense human development. This study presents a high-resolution water quality model developed using Delft3D 4 software, integrating the hydrodynamic (Delft3D-FLOW) and water quality (Delft3D-WAQ) modules. Calibration and validation demonstrate the robust performance and reliability of the model in simulating critical biogeochemical processes, such as nutrient cycling and phytoplankton dynamics. The model effectively captures seasonal and spatial variations in water quality parameters, including water temperature, salinity, inorganic nutrients, dissolved oxygen, and chlorophyll-a. Of the variables studied, the model performed best for dissolved oxygen, followed by nitrates, phosphates, ammonium, silicate, and chlorophyll-a. While some discrepancies were observed in the inner zones and deeper layers of the rias, the overall performance metrics aligned closely with the observed data, enhancing confidence in the model’s utility for future research and resource management. These results highlight the model’s value as a tool for research and managing water and marine resources in the Rías Baixas.

With the growing world energy needs, offshore wind farms tend to increase in terms of installed capacity, rated power, and the number of wind turbines. This trajectory leads to higher electricity production losses due to the wake effect between the wind turbines, resulting in an elevated Levelized Cost of Energy. Therefore, it is crucial to estimate this cost for various wind farm designs, involving the application of different distances between the wind turbines, aiming to identify the most cost-effective solutions. In this study these estimates were carried out within a legally designated 1800 km2 area earmarked for offshore wind energy exploitation by the Spanish government, situated at the northwest corner of the Iberian Peninsula, considering 15 MW wind turbines. This region is one of the most promising areas of the Iberian Peninsula and Europe since its wind resource potential for the upcoming years has been classified as outstanding. The wind data employed in this analysis emanates from a dynamical downscaling process performed using the Weather Research and Forecasting model, derived from a multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project. The data encompasses the timeframe spanning 2025 to 2049, under the Shared Socioeconomic Pathways 2-4.5, adjusted to coincide with the projected operational lifetime of wind farms. The results show that, without any kind of restrictions in terms of installed power and number of wind turbines, the most economically advantageous Levelized Cost of Energy is achieved at intermediate distances between the wind turbines. Conversely, when specifying a predetermined number of wind turbines, optimal results are attained with the application of the highest distance between turbines.

Coastal upwelling is of particular importance in the western Iberian Peninsula, considering its socioeconomic impact on the region. Therefore, it is of crucial interest to evaluate how climate change, by modifying wind patterns, might influence its intensity and seasonality. Given the limited spatial extension of the area, it is essential to use high-resolution data. Thus, the weather research and forecasting model was used to dynamically downscale data from a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project, representing the latest climate projections. Two shared socioeconomic pathways, 2–4.5 and 5–8.5 scenarios, were considered. The results show that climate change will not modify the upwelling seasonality in the area, where the months from April to September represent the period of highest intensity. Conversely, this seasonality might be exacerbated throughout the 21st century, as upwelling is expected to strengthen during these months and decrease during others. Additionally, coastal upwelling shows the highest increase at the northerner locations of the western Iberian Peninsula, resulting in a homogenization of its intensity along this coast. These changes may result from the anticipated intensification and northward shift of the Azores High.

Marine renewable energies can play a key role by reducing the dependency on fossil fuels and, therefore, mitigating climate change. Among them, it is expected that wave energy will experience rapid growth in the upcoming decades. Thus, it is important to know how wave climate will change and how suitable the wave energy converters (WECs) will be to the new wave conditions. This paper aims to evaluate the capability of four different WECs-a WaveRoller type device (WRTD), Atargis, AquaBuoy and RM5-to extract wave energy on the Northwest coast of Spain (NWCS). The analysis was performed using the high-resolution wave data obtained from the Simulating Waves Nearshore (SWAN) model over the near future winters (2026-2045). The energy output (PE), the power load factor (& epsilon;), the normalized capture width (NCw) and the operational time (OT) were analyzed. According to these parameters, among the devices that work for intermediate-deep waters, Atargis would be the best option (PE=1400 & PLUSMN; 56 kW, & epsilon; =55.4 & PLUSMN; 2.2%, NCw=35.5 & PLUSMN; 4.1% and OT =84.5 & PLUSMN; 3.3%). The WRTD would also be a good option for shallow nearshore areas with PE=427 & PLUSMN; 248 kW, & epsilon; =12.8 & PLUSMN; 7.4%, NCw = 48.9 & PLUSMN; 9.6% and OT = 88.7 & PLUSMN; 18.9%. A combination of Atargis and WRTDs is proposed to make up the future wave energy farms on the NWCS.

The Spanish government has established a Maritime Spatial Planning including areas for wind farms, with the aim of contributing up to 40% of European floating offshore wind power by 2030. Thus, it is crucial to assess the current and future offshore wind energy resource in these areas, and classify the near future resource by considering wind power density and other relevant factors like resource stability, environmental risks, and installation costs. To attain the necessary high spatial resolution, a dynamic downscaling of a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project was conducted using the Weather Research and Forecasting model in Spanish territorial waters, including the Iberian Peninsula, Balearic Islands, and Canary Islands. Future projections were considered under the Shared Socioeconomic Pathways 2–4.5 and 5–8.5 scenarios. According to the results, Spain's offshore wind energy potential is projected to grow in the upcoming years, particularly in the Atlantic Ocean and surrounding the Canary Islands. Wind resource classification in the potential offshore wind farm areas reveals noteworthy diversity, with ratings ranging from “fair” (3/7) to “outstanding” (6/7). The most promising areas for offshore wind farm development in the near future are located in the northwest of the Iberian Peninsula and the Canary Islands.

The Atacama desert is a region with exceptional conditions for solar power production. However, despite its relevance, the impact of climate change on this resource in this region has barely been studied. Here, we use regional climate models to explore how climate change will affect the photovoltaic solar power resource per square meter (PVres) in Atacama. Models project average reductions in PVres of 1.5% and 1.7% under an RCP8.5 scenario, respectively, for 2021-2040 and 2041-2060. Under RCP2.6 and the same periods, reductions range between 1.2% and 0.5%. Also, we study the contribution to future changes in PVres of the downwelling shortwave radiation, air temperature and wind velocity. We find that the contribution from changes in wind velocity is negligible. Future changes of downwelling shortwave radiation, under the RCP8.5 scenario, cause up to 87% of the decrease of PVres for 2021-2040 and 84% for 2041-2060. Rising temperatures due to climate change are responsible for drops in PVres ranging between 13%-19% under RCP2.6 and 14%-16% under RCP8.5. We conclude that climate change has the potential to impact the PVres in the Atacama region while retaining exceptional conditions for solar power production.

There are currently several types of devices capable of harnessing wave energy, exploiting a broad variety of physical transformation processes. These devices – known as Wave Energy Converters (WECs) – are developed to maximize their power output. However, there are still uncertainties about their response and survivability to loads induced by adverse environmental conditions, with a consequent increase of the Levelized Cost of Energy (LCOE), which prevents in fact their commercial diffusion. As evidenced by a large body of research, marine renewable energy devices need to have more robust design practices. To address this issue, we propose the CFD-based DualSPHysics toolbox as a support in the design stages. DualSPHysics is high-fidelity software inherently suited to numerically address most challenges posed by multiphysics simulations, which are required to reliably predict WEC response in situations well beyond operational conditions. It should be noted that WECs, generally, may be connected to the seabed and comprise mechanical systems named Power Take-Offs (PTO) used to convert the energy from waves into electricity or other usable energies. To reproduce these features, DualSPHysics benefits from coupling with the multiphysics library Project Chrono and the dynamic mooring model Moordyn+. In this work, the augmented DualSPHysics framework is utilised to simulate a range of very different types of WECs with a variety of elements, such as catenary connections, taut mooring lines, or linear and nonlinear PTO actuators. Version 5.2 of the open-source licensed code was recently released, making the numerical framework publicly available as one unit. This work aims to provide a numerical review of past applications, and to demonstrate how the same open-source code is able to simulate very different technologies. Specifically, this paper proposes routine modeling and validation procedures using the SPH-based solver DualSPHysics applied to five different WEC types: i) a moored point absorber (PA); ii) an oscillating wave surge converter (OWSC); iii) a floating OWSC (so called FOSWEC); iv) a wave energy hyperbaric converter (WEHC); and v) a multi-body attenuator (so called Multi-float M4). For each device listed above, we provide validation proof against physical model data for various components of the floater(s) and PTO related quantities, performed under specific sea conditions that aim to challenge their survivability. Within the scope of this research, we present the WEC response with respect to the degrees of freedom that really matter for each of the floatings due to hydrodynamic interactions (i.e., heave, surge, and pitch), along with quantities more intimately connected to the anchoring systems (e.g., line tension) or the mechanical apparatus (e.g., end-stopper force). The quality of the results, the discussion built upon them and the demonstrated solver exploitability to a wide range of WECs show that one software model can run all cases using the exact same methodology, which is of great value for the marine energy R&D community. Finally, we discuss future research objectives, which include the implementation of automation to apply open control systems and possible applications to subsets of WEC farm arrays and other floating energy harnessing devices.

Shellfisheries of the intertidal and shallow subtidal infaunal bivalves Ruditapes decussatus, Ruditapes philippinarum, Venerupis corrugata and Cerastoderma edule are of great socio-economic importance (in terms of landings) in Europe, specifically in the Galician Rías Baixas (NW Spain). However, ocean warming may threaten these fisheries by modifying the geographic distribution of the species and thus affecting productive areas. The present study analysed the impact of rising ocean temperature on the geographical distribution of the thermal comfort areas of these bivalves throughout the 21st century. The Delft3D model was used to downscale climate data from CORDEX and CMIP5 and was run for July and August in three future periods (2025-2049, 2050-2074 and 2075-2099) under the RCP8.5 scenario. The areas with optimal temperature conditions for shellfish harvesting located in the middle and outer parts of the rias may increase in the near future for R. decussatus, V. corrugata and C. edule and decrease in the far future for R. philippinarum. Moreover, shellfish beds located in the shallower areas of the inner parts of the Rías Baixas could be affected by increased water temperature, reducing the productive areas of the four species by the end of the century. The projected changes in thermal condition will probably lead to changes in shellfish harvesting modality (on foot or aboard vessels) with further socio-economic consequences.

Abstract. River floods, which are one of the most dangerous natural hazards worldwide, have increased in intensity and frequency in recent decades as a result of climate change, and the future scenario is expected to be even worse. Therefore, their knowledge, predictability, and mitigation represent a key challenge for the scientific community in the coming decades, especially in those local areas that are most vulnerable to these extreme events. In this sense, a multiscale analysis is essential to obtain detailed maps of the future evolution of floods. In the multiscale analysis, the historical and future precipitation data from the CORDEX (Coordinated Regional Downscaling Experiment) project are used as input in a hydrological model (HEC-HMS) which, in turn, feeds a 2D hydraulic model (Iber+). This integration allows knowing the projected future changes in the flow pattern of the river, as well as analyzing the impact of floods in vulnerable areas through the flood hazard maps obtained with hydraulic simulations. The multiscale analysis is applied to the case of the Miño-Sil basin (NW Spain), specifically to the city of Ourense. The results show a delay in the flood season and an increase in the frequency and intensity of extreme river flows in the Miño-Sil basin, which will cause more situations of flooding in many areas frequented by pedestrians and in important infrastructure of the city of Ourense. In addition, an increase in water depths associated with future floods was also detected, confirming the trend for future floods to be not only more frequent but also more intense. Detailed maps of the future evolution of floods also provide key information to decision-makers to take effective measures in advance in those areas most vulnerable to flooding in the coming decades. Although the methodology presented is applied to a particular area, its strength lies in the fact that its implementation in other basins and cities is simple, also taking into account that all the models used are freely accessible.

The expansion of marine renewable power is a major alternative for the reduction of greenhouse gases emissions. In Europe, however, the high penetration of offshore wind brings intermittency and power variability into the existing power grid. Offshore solar photovoltaic power is another technological alternative under consideration in the plans for decarbonization. However, future variations in wind, air temperature or solar radiation due to climate change will have a great impact on both renewable energy resources. In this context, this study focusses on the offshore energy assessment off the coast of Western Iberia, a European region encompassing Portugal and the Northwestern part of Spain. Making use of a vast source of data from 35 simulations of a research project called CORDEX, this study investigates the complementarity of offshore wind and solar energy sources with the aim of improving the energy supply stability of this region up to 2040. The most pessimistic greenhouse gases emission scenario (RCP8.5) is considered. The 35 simulations are validated by comparing wind speed at 10m, air temperature at 2m and solar radiation values with data from the ERA5 reanalysis database. Although the offshore wind energy resource has proven to be higher than solar photovoltaic resource at annual scale, both renewable resources showed significant spatiotemporal energy variability throughout the western Iberian Peninsula. When both renewable resources are combined, the stability of the energy resource increased considerably throughout the year. The proposed wind and solar combination scheme is assessed by a performance classification method called Delphi, considering stability, resource, risk, and economic factors. The total index classification increases when resource stability is improved by considering hybrid offshore wind-photovoltaic solar energy production, especially along the nearshore waters.