Analysis of fire behaviour simulations over Spain with WRF-FIRE

Wildland fire spread and behaviour are complex phenomena owing to both the number of involved physico-chemical factors, and the non-linear relationship between variables. Spain is plagued by forest and brush fires every summer, when the extremely dry weather sets in along with high temperatures. The use of fire behaviour models requires the availability of high resolution environmental and fuel data; in the absence of real data, errors on the simulated fire spread can be compounded to affect the spatial and temporal accuracy of predicted data. The effect of input values on the accuracy of WRF-FIRE simulations was evaluated to assess the capabilities of the new system for wildland fire in accurately forecasting fire behaviour. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behaviour.

An Overview of Modelling Bulgarian Wildland Fire Behaviour by Application of a Mathematical Game Method and WRF-Fire Models

This paper presents the main achievements of the author’s PhD dissertation. The work is dedicated to mathematical and semi-empirical approaches applied to the case of Bulgarian wildland fires. After the introductory explanations, short information from every chapter is extracted to cover the main parts of the obtained results. The methods used are described in brief and main outcomes are listed. ACM Computing Classification System (1998): D.1.3, D.2.0, K.5.1.

Application of WRF-Chem to Forecasting PM10 Concentration Over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one-way nested domains using the GFS meteorological data and the TNO MACC II emissions. The 48 hour forecasts were run for each day of the winter and summer period of 2014 and there is only a small decrease in model performance for winter with respect to forecast lead time. The model in general captures the variability in observed PM10 concentrations for most of the stations. However, for some locations and specific episodes, the model performance is poor and the results cannot yet be used by official authorities. We argue that a higher resolution sector-based emission data will be helpful for this analysis in connection with a focus on planetary boundary layer processes in WRF-Chem and their impact on the initial distribution of emissions on both time and space.

Toward assessing the effects of aerosols on deep convection: a numerical study using the WRF-Chemistry model

As the formative agents of cloud droplets, aerosols play an undeniably important role in the development of clouds and precipitation. Few meteorological models have been developed or adapted to simulate aerosols and their contribution to cloud and precipitation processes. The Weather Research and Forecasting model (WRF) has recently been coupled with an atmospheric chemistry suite and is jointly referred to as WRF-Chem, allowing atmospheric chemistry and meteorology to influence each other’s evolution within a mesoscale modeling framework. Provided that the model physics are robust, this framework allows the feedbacks between aerosol chemistry, cloud physics, and dynamics to be investigated. This study focuses on the effects of aerosols on meteorology, specifically, the interaction of aerosol chemical species with microphysical processes represented within the framework of the WRF-Chem. Aerosols are represented by eight size bins using the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) sectional parameterization, which is linked to the Purdue Lin bulk microphysics scheme. The aim of this study is to examine the sensitivity of deep convective precipitation modeled by the 2D WRF-Chem to varying aerosol number concentration and aerosol type. A systematic study has been performed regarding the effects of aerosols on parameters such as total precipitation, updraft/downdraft speed, distribution of hydrometeor species, and organizational features, within idealized maritime and continental thermodynamic environments. Initial results were obtained using WRFv3.0.1, and a second series of tests were run using WRFv3.2 after several changes to the activation, autoconversion, and Lin et al. microphysics schemes added by the WRF community, as well as the implementation of prescribed vertical levels by the author. The results of WRFv3.2 runs contrasted starkly with WRFv3.0.1 runs. The WRFv3.0.1 runs produced a propagating system resembling a developing squall line, whereas the WRFv3.2 runs did not. The response of total precipitation, updraft/downdraft speeds, and system organization to increasing aerosol concentrations were opposite between runs with different versions of WRF. Results of the WRFv3.2 runs, however, were in better agreement in timing and magnitude of vertical velocity and hydrometeor content with a WRFv3.0.1 run using single-moment Lin et al. microphysics, than WRFv3.0.1 runs with chemistry. One result consistent throughout all simulations was an inhibition in warm-rain processes due to enhanced aerosol concentrations, which resulted in a delay of precipitation onset that ranged from 2-3 minutes in WRFv3.2 runs, and up to 15 minutes in WRFv.3.0.1 runs. This result was not observed in a previous study by Ntelekos et al. (2009) using the WRF-Chem, perhaps due to their use of coarser horizontal and vertical resolution within their experiment. The changes to microphysical processes such as activation and autoconversion from WRFv3.0.1 to WRFv3.2, along with changes in the packing of vertical levels, had more impact than the varying aerosol concentrations even though the range of aerosol tested was greater than that observed in field studies. In order to take full advantage of the input of aerosols now offered by the chemistry module in WRF, the author recommends that a fully double-moment microphysics scheme be linked, rather than the limited double-moment Lin et al. scheme that currently exists. With this modification, the WRF-Chem will be a powerful tool for studying aerosol-cloud interactions and allow comparison of results with other studies using more modern and complex microphysical parameterizations.

Análisis de rendimiento y profiling del modelo WRF en un clúster HPC

El modelo de investigación y pronóstico climático (WRF) es un sistema completamente funcional de modelado que permite realizar investigación atmosférica y predicción meteorológica. WRF fue desarrollado con énfasis en la eficiencia, portabilidad, facilidad de mantenimiento, escalabilidad y productividad, lo que ha permitido que sea implementado con éxito en una amplia variedad de equipos HPC. Por esta razón, el tamaño de los problemas a los que WRF da soporte ha incrementado, por lo que el entendimiento de la dependencia del WRF con los diversos elementos de clúster, como la CPU, interconexiones y librerías, son cruciales para permitir predicciones eficientes y de alta productividad. En este contexto, el presente manuscrito estudia la escalabilidad de WRF en un equipo HPC, tomando en consideración tres parámetros: número de CPUs y nodos, comunicaciones y librerías. Para esto, dos benchmarks son llevados a cabo sobre un clúster de alto rendimiento dotado de una red GigaEthernet, los cuales permiten establecer la relación entre escalabilidad y los tres parámetros estudiados, y particularmente demuestran la sensibilidad del WRF a la comunicación inter-nodo. Dicho factor es esencial para mantener la escalabilidad y el aumento de la productividad al añadir nodos en el clúster.

Numerical Modelling of the Observed Diurnal Cycle of Indian Monsoon Rainfall

We have analysed the diurnal cycle of rainfall over the Indian region (10S-35N, 60E-100E) using both satellite and in-situ data, and found many interesting features associated with this fundamental, yet under-explored, mode of variability. Since there is a distinct and strong diurnal mode of variability associated with the Indian summer monsoon rainfall, we evaluate the ability of the Weather Research and Forecasting Model (WRF) to simulate the observed diurnal rainfall characteristics. The model (at 54km grid-spacing) is integrated for the month of July, 2006, since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST), by using two different SST datasets, namely, Final Analyses (FNL) and Real-time Global (RTG). It was found that with RTG SST the rainfall simulation over central India (CI) was significantly better than that with FNL. On the other hand, over the Bay of Bengal (BoB), rainfall simulated with FNL was marginally better than with RTG. However, the overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the role of the convective parameterization scheme on the simulation of diurnal cycle of rainfall. We found that the Kain-Fritsch (KF) scheme performs significantly better than Betts-Miller-Janjić (BMJ) and Grell-Devenyi schemes. We also studied the impact of other physical parameterizations, namely, microphysics, boundary layer, land surface, and the radiation parameterization, on the simulation of diurnal cycle of rainfall, and identified the “best” model configuration. We used this configuration of the “best” model to perform a sensitivity study on the role of various convective components used in the KF scheme. In particular, we studied the role of convective downdrafts, convective timescale, and feedback fraction, on the simulated diurnal cycle of rainfall. The “best” model simulations, in general, show a good agreement with observations. Specifically, (i) Over CI, the simulated diurnal rainfall peak is at 1430 IST, in comparison to the observed 1430-1730 IST peak; (ii) Over Western Ghats and Burmese mountains, the model simulates a diurnal rainfall peak at 1430 IST, as opposed to the observed peak of 1430-1730 IST; (iii) Over Sumatra, both model and observations show a diurnal peak at 1730 IST; (iv) The observed southward propagating diurnal rainfall bands over BoB are weakly simulated by WRF. Besides the diurnal cycle of rainfall, the mean spatial pattern of total rainfall and its partitioning between the convective and stratiform components, are also well simulated. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over CI and BoB. While, the 54km and 18km simulations were conducted for the whole of July, 2006, the 6km simulation was carried out for the period 18 - 24 July, 2006. The results of our coarse- and fine-scale numerical simulations of the diurnal cycle of monsoon rainfall will be discussed.

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold's SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold's and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold's SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold's SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold's SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.

A divide and conquer strategy for scaling weather simulations with multiple regions of interest

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Investigations of aerosol black carbon from a semi-urban site in the Indo-Gangetic Plain region

Long-term (2009-2012) data from ground-based measurements of aerosol black carbon (BC) from a semi-urban site, Pantnagar (29.0 degrees N, 79.5 degrees E, 231 m amsl), in the Indo-Gangetic Plain (IGP) near the Himalayan foothills are analyzed to study the regional characterization. Large variations are seen in BC at both diurnal and seasonal scales, associated with the mesoscale and synoptic meteorological processes, and local/regional anthropogenic activities. BC diurnal variations show two peaks (morning and evening) arising from the combined effects of the atmospheric boundary layer (ABL) dynamics and local emissions. The diurnal amplitudes as well as the rates of diurnal evolution are the highest in winter season, followed by autumn, and the lowest in summer-monsoon. BC exhibits nearly an inverse relation with mixing layer depth in all seasons; being strongest in winter (R-2 = 0.89) and weakest (R-2 = 0.33) in monsoon (July-August). Unlike BC, co-located aerosol optical depths (AOD) and aerosol absorption are highest in spring over IGP, probably due to the presence of higher abundances of aerosols (including dust) above the ABL (in the free troposphere). AOD (500 nm) showed annual peak (>0.6) in May-June, dominated by coarse mode, while fine mode aerosols dominated in late autumn and early winter. Aerosols profiles from CALIPSO show highest values close to the surface in winter/autumn, similar to the feature seen in surface BC, whereas at altitudes > 2 km, the extinction is maximum in spring/summer. WRF-Chem model is used to simulate BC temporal variations and then compared with observed BC. The model captures most of the important features of the diurnal and seasonal variations but significantly underestimated the observed BC levels, suggesting improvements in diurnal and seasonal varying BC emissions apart from the boundary layer processes. (C) 2015 Elsevier Ltd. All rights reserved.

Inter-comparison and performance evaluation of chemistry transport models over Indian region

Aerosol loading over the South Asian region has the potential to affect the monsoon rainfall, Himalayan glaciers and regional air-quality, with implications for the billions in this region. While field campaigns and network observations provide primary data, they tend to be location/season specific. Numerical models are useful to regionalize such location-specific data. Studies have shown that numerical models underestimate the aerosol scenario over the Indian region, mainly due to shortcomings related to meteorology and the emission inventories used. In this context, we have evaluated the performance of two such chemistry-transport models: WRF-Chem and SPRINTARS over an India-centric domain. The models differ in many aspects including physical domain, horizontal resolution, meteorological forcing and so on etc. Despite these differences, both the models simulated similar spatial patterns of Black Carbon (BC) mass concentration, (with a spatial correlation of 0.9 with each other), and a reasonable estimates of its concentration, though both of them under-estimated vis-a-vis the observations. While the emissions are lower (higher) in SPRINTARS (WRF-Chem), overestimation of wind parameters in WRF-Chem caused the concentration to be similar in both models. Additionally, we quantified the under-estimations of anthropogenic BC emissions in the inventories used these two models and three other widely used emission inventories. Our analysis indicates that all these emission inventories underestimate the emissions of BC over India by a factor that ranges from 1.5 to 2.9. We have also studied the model simulations of aerosol optical depth over the Indian region. The models differ significantly in simulations of AOD, with WRF-Chem having a better agreement with satellite observations of AOD as far as the spatial pattern is concerned. It is important to note that in addition to BC, dust can also contribute significantly to AOD. The models differ in simulations of the spatial pattern of mineral dust over the Indian region. We find that both meteorological forcing and emission formulation contribute to these differences. Since AOD is column integrated parameter, description of vertical profiles in both models, especially since elevated aerosol layers are often observed over Indian region, could be also a contributing factor. Additionally, differences in the prescription of the optical properties of BC between the models appear to affect the AOD simulations. We also compared simulation of sea-salt concentration in the two models and found that WRF-Chem underestimated its concentration vis-a-vis SPRINTARS. The differences in near-surface oceanic wind speeds appear to be the main source of this difference. In-spite of these differences, we note that there are similarities in their simulation of spatial patterns of various aerosol species (with each other and with observations) and hence models could be valuable tools for aerosol-related studies over the Indian region. Better estimation of emission inventories could improve aerosol-related simulations. (C) 2015 Elsevier Ltd. All rights reserved.

Contribution of the North Atlantic subtropical high to regional climate model (RCM) skill in simulating southeastern United States summer precipitation

© 2014, Springer-Verlag Berlin Heidelberg.This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical–extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the modeled precipitation biases over the SE US. In conclusion, our study demonstrates that the NASH western ridge is an important factor responsible for the RCM skill in simulating SE US summer precipitation. Furthermore, the improvements in the PBL parameterizations for the Gulf of Mexico might help advance RCM skill in representing the NASH western ridge circulation and summer precipitation over the SE US.

Modelling the Minho river plume intrusion into the rias baixas

The Minho River, situated 30 km south of the Rias Baixas is the most important freshwater source flowing into the Western Galician Coast (NW of the Iberian Peninsula). This discharge is important to determine the hydrological patterns adjacent to its mouth, particularly close to the Galician coastal region. The buoyancy generated by the Minho plume can flood the Rias Baixas for long periods, reversing the normal estuarine density gradients. Thus, it becomes important to analyse its dynamics as well as the thermohaline patterns of the areas affected by the freshwater spreading. Thus, the main aim of this work was to study the propagation of the Minho estuarine plume to the Rias Baixas, establishing the conditions in which this plume affects the circulation and hydrographic features of these coastal systems, through the development and application of the numerical model MOHID. For this purpose, the hydrographic features of the Rias Baixas mouths were studied. It was observed that at the northern mouths, due to their shallowness, the heat fluxes between the atmosphere and ocean are the major forcing, influencing the water temperature, while at the southern mouths the influence of the upwelling events and the Minho River discharge were more frequent. The salinity increases from south to north, revealing that the observed low values may be caused by the Minho River freshwater discharge. An assessment of wind data along the Galician coast was carried out, in order to evaluate the applicability of the study to the dispersal of the Minho estuarine plume. Firstly, a comparative analysis between winds obtained from land meteorological stations and offshore QuikSCAT satellite were performed. This comparison revealed that satellite data constitute a good approach to study wind induced coastal phenomena. However, since the numerical model MOHID requires wind data with high spatial and temporal resolution close to the coast, results of the forecasted model WRF were added to the previous study. The analyses revealed that the WRF model data is a consistent tool to obtain representative wind data near the coast, showing good results when comparing with in situ wind observations from oceanographic buoys. To study the influence of the Minho buoyant discharge influence on the Rias Baixas, a set of three one-way nested models was developed and implemented, using the numerical model MOHID. The first model domain is a barotropic model and includes the whole Iberian Peninsula coast. The second and third domains are baroclinic models, where the second domain is a coarse representation of the Rias Baixas and adjacent coastal area, while the third includes the same area with a higher resolution. A bi-dimensional model was also implemented in the Minho estuary, in order to quantify the flow (and its properties) that the estuary injects into the ocean. The chosen period for the Minho estuarine plume propagation validation was the spring of 1998, since a high Minho River discharge was reported, as well as favourable wind patterns to advect the estuarine plume towards the Rias Baixas, and there was field data available to compare with the model predictions. The obtained results show that the adopted nesting methodology was successful implemented. Model predictions reproduce accurately the hydrodynamics and thermohaline patterns on the Minho estuary and Rias Baixas. The importance of the Minho river discharge and the wind forcing in the event of May 1998 was also studied. The model results showed that a continuous moderate Minho River discharge combined with southerly winds is enough to reverse the Rias Baixas circulation pattern, reducing the importance of the occurrence of specific events of high runoff values. The conditions in which the estuarine plume Minho affects circulation and hydrography of the Rias Baixas were evaluated. The numerical results revealed that the Minho estuarine plume responds rapidly to wind variations and is also influenced by the bathymetry and morphology of the coastline. Without wind forcing, the plume expands offshore, creating a bulge in front of the river mouth. When the wind blows southwards, the main feature is the offshore extension of the plume. Otherwise, northward wind spreads the river plume towards the Rias Baixas. The plume is confined close to the coast, reaching the Rias Baixas after 1.5 days. However, for Minho River discharges higher than 800 m3 s-1, the Minho estuarine plume reverses the circulation patterns in the Rias Baixas. It was also observed that the wind stress and Minho River discharge are the most important factors influencing the size and shape of the Minho estuarine plume. Under the same conditions, the water exchange between Rias Baixas was analysed following the trajectories particles released close to the Minho River mouth. Over 5 days, under Minho River discharges higher than 2100 m3 s-1 combined with southerly winds of 6 m s-1, an intense water exchange between Rias was observed. However, only 20% of the particles found in Ria de Pontevedra come directly from the Minho River. In summary, the model application developed in this study contributed to the characterization and understanding of the influence of the Minho River on the Rias Baixas circulation and hydrography, highlighting that this methodology can be replicated to other coastal systems.

Prevenção e detecção de incêndios

Os fogos florestais, embora possam ser encarados como um fenómeno natural, constituem igualmente uma ameaça com impactos negativos a vários níveis. A alteração dos regimes naturais do fogo por acção antrópica tem vindo a maximizar o potencial catastrófico do fenómeno em diferentes regiões do planeta, destacando-se, em particular, a Região Mediterrânica, onde o fogo constitui uma perturbação recorrente associada, por um lado, às características climáticas desta região e, por outro, às práticas tradicionais decorrentes da presença humana nessa área, numa extensão temporal de milhares de anos. Em Portugal, o problema dos fogos florestais assume uma expressividade de particular relevo, colocando-o entre os países do sul da Europa mais atingidos pelo fogo a cada Verão. Reconhecendo o papel das condições meteorológicas nas interacções envolvidas no processo de deflagração e propagação de incêndios, a identificação de condições meteorológicas propícias à ocorrência de incêndios, expressa sob a forma de índices de risco reveste-se de crucial importância para as operações de prevenção e combate aos incêndios, para além da mais-valia que constituem para os restantes sectores da sociedade. Adicionalmente, a detecção e monitorização de ocorrências de incêndios a partir de satélites tem vindo a assumir um papel preponderante, revelando-se fundamental enquanto fonte de alerta e pelas potencialidades que as bases de dados resultantes da observação contínua da Terra pelos satélites oferecem, no que às mais diversas áreas de investigação diz respeito. O presente trabalho explora, nas vertentes da prevenção de incêndios, a utilização de previsões de tempo de alta resolução espacial obtidas com o modelo WRF para a determinação das componentes do sistema FWI canadiano e sua disponibilização operacional. Os resultados apontam para um impacto positivo, em virtude do incremento da resolução espacial, da representação espacial do risco meteorológico de incêndio no território português. Paralelamente, apresentam-se os resultados do desenvolvimento de produtos de detecção de incêndios activos a partir da infra-estrutura de recepção de dados de satélite implementadas na Universidade de Aveiro, destacando a sua adequabilidade para a monitorização e identificação, em tempo quase-real, da ocorrência de fogos florestais em Portugal Continental.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.