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The Arabian Peninsula is an area of diverse climatic conditions due to its location and geomorphological characteristics. It is affected by the Indian monsoon in the South and the Mediterranean synoptic scale systems in the North. It has mostly a desert-type climate with extreme heat during the daytime and very low annual rainfall. Extreme precipitation events related to convective activities are not that rare though. Such events often lead to flooding and may pose threat to human life and activities. At the same time, their local nature makes the recording and forecasting very difficult but essential. Towards a better understanding of the spatiotemporal features, the links and the feedback mechanisms associated with precipitation, a thirty year regional climatic analysis has been prepared with the aid of the state-of-the-art modeling system RAMS/ICLAMS. Its two-way interactive nesting capabilities, explicit cloud microphysical schemes with seven categories of hydrometeors and the ability to handle dust aerosols as predictive quantities make it suitable in an area where dust is a dominant factor. Special focus is given to densely populated regions and in several cities in order to cover the climatic features of the Peninsula to a satisfactory extent. An extended evaluation based on in-situ measurements and satellite records is performed. A monthly climatic analysis is performed alongside with a trend analysis to better assess the rainfall patterns throughout the thirty year period. The extremes are studied under the principles of the extreme value theory focusing not only on the duration but also on the intensity of the events. To enrich the analysis of the precipitation climate an examination of droughts is also performed. Apart from the strict scientific interest, the outcome has an added value in civil protection and several industries such as constructions and reinsurance.

Of the boundary conditions that affect the simulation of convective precipitation, soil moisture is one of the most important. In this study, we explore the impact of the soil moisture on convective precipitation, and factors affecting it, through an extensive numerical experiment based on four convective precipitation events that caused moderate to severe flooding in the Gard region of southern France. High-spatial-resolution (1 km) weather simulations were performed using the integrated atmospheric model Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System (RAMS/ICLAMS). The experimental framework included comparative analysis of five simulation scenarios for each event, in which we varied the magnitude and spatial distribution of the initial volumetric water content using realistic soil moisture fields with different spatial resolution. We used precipitation and surface soil moisture from radar and satellite sensors as references for the comparison of the sensitivity tests. Our results elucidate the complexity of the relationship between soil moisture and convective precipitation, showing that the control of soil water content on partitioning land surface heat fluxes has significant impacts on convective precipitation. Additionally, it is shown how different soil moisture conditions affect the modeled microphysical structure of the clouds, which translates into further changes in the magnitude and distribution of precipitation.

The Cyprus coastal ocean forecasting system, known as CYCOFOS has been providing operational hydrodynamical and sea state forecasts in the Eastern Mediterranean since early 2002. Recently, it has been improved with the implementation of new hydrodynamic and new wave modeling systems with the objective of targeting higher resolution domains, at coastal, sub-regional and regional scales in the Mediterranean and the Black Sea. For the new CYCOFOS hydrodynamic modeling system a novel parallel version of the well established POM has been implemented. The new CYCOFOS hydrodynamical models covers the entire Eastern Mediterranean with a resolution of 2 km and the Levantine Basin with a resolution of ~600 m, both nested in the Copernicus Marine Environmental Monitoring Service of the Mediterranean Forecasting Center-CMEMS Med MFC. For sea waves forecasting, CYCOFOS has implemented the new ECMWF wave model WAM CY46R1 in the Mediterranean and the Black seas at a higher resolution of 5 km. The CYCOFOS hydrodynamical models received an extended cal/val against the parent model, Argo profiles and satellite SST time series, while in-situ wave data gathered by the HERMES buoy monitoring network in the Eastern Mediterranean and the Black Sea were used for statistical validation of the new CYCOFOS wave forecasts. The new CYCOFOS validated modeling systems, provide higher resolution quality controlled forecasting data suiting the needs for : a) down-streaming applications supporting risk assessment for offshore platforms in the Levantine Basin and studies concerning the coastal erosion in the Eastern Mediterranean (Albania, Cyprus, Greece) and the Black Sea (Bulgaria) in the framework of the HERMES project, and b) further hierarchical downscaling applications for the development of the COASTAL CRETE operation forecasting system at a higher resolution in the Eastern Mediterranean (Crete, Greece).

The effects of natural aerosols on microphysical processes in clouds are quite important for their development and evolution and still pose some unresolved questions on the impact they have in the atmosphere and climate. The processes where they interfere, can lead to an uncertainty in the intensity of precipitation and the hydrometeor species as well as the temporal and spatial extent of the affected areas. Apart from the scientific interest of such studies, the outcome highly affects applications and early warning systems associated to water management, food security and agriculture.For the needs of the study, the state of the art atmospheric modeling system RAMS-ICLAMS was used to investigate the effects of desert dust concentrations on microphysical processes in clouds. The model is able to run in very high resolutions in order to resolve cloud processes explicitly. Extreme case studies were selected, simulated and the model performance was evaluated showing satisfactory results. Sensitivity tests were performed in order to quantify the direct, indirect and semi-direct impact of CCN and IN concentrations. These tests showed notable effects on the cloud microphysical processes, as well as on hydrometeors. This further enhances the need for a more accurate description of aerosol feedbacks in regional and climate atmospheric models.

Wind energy investments have met a quick growth during the last decades due to the stricter climate policies, the need for energy independence and the higher profits coming from the smaller costs of such applications. Moreover the evolution of technology leads to the characterization of more areas as suitable for energy applications. Offshore wind farms are a nice example of how to build bigger, more efficient and resistant in extreme conditions wind power plants.The present work is focused on the determination of the suitability of an offshore marine area for the development of wind farm structures. More specifically the region of interest is the marine area on the south of France including the Gulf of Leon. For the needs of the study a 10-year database, produced employing state of the art atmospheric and wave models, is utilized. The wind and wave parameters used, have a spatial resolution of 6 km and a frequency of one hour.Wind speed and power probability distribution characteristics are discussed in different heights throughout the domain. Particular locations are selected for a more comprehensive analysis. At the same time extreme wind and wave conditions and their 50-years return period are analyzed and used to define the safety level of the wind farms structural characteristics. The outcome could lead to a review of the area suitability for wind farm development, providing a new tool for technical/research teams and decision makers.

One of the largest last decade discoveries of hydrocarbons in the Eastern Mediterranean Sea is the Leviathan field, which constitutes a large-scale energy program of the State of Israel. Gas and condensate from the Leviathan well are transferred via pipeline to an offshore platform located ~10 km from the Israeli shoreline, and from there via a pipeline to the coastal Leviathan energy installation. The local communities are concerned from the pollution implications that might occur in case of spillage and/or any malfunction in regular operation.The present work includes review of previous environmental studies regarding the Leviathan energy project 2007-2011, new extended simulations 2015-2018 for condensate, diesel and grey water leaks and resultant evaporation simulations caused by possible condensate spillage from the offshore platform and the pipe rupture.In the framework of the current study concerning the Leviathan offshore platform, a robust statistics is obtained by 5844 spill simulation runs for condensate and diesel against12 runs as mentioned in the previous studies, while for the pipe rupture a robust statistics was made with 104 runs for condensate and diesel compared to12 runs as performed previously.The previous spillage scenarios from the offshore platform had underestimated by almost order of magnitude the content per design itself (1000bbls vs. ~6000bbls) and documentation of permits. Similarly, the pipe rupture spillage scenarios underestimated by almost half order of magnitude (1200bbls vs. ~3000bbls). Therefore, the current simulations predicted larger spillage quantities, compared to the aforementioned previous simulations.The main conclusions driven from the 10km counter simulations for the offshore platform spillage show the following: First oil arrival at the Israeli coast from the offshore platform is predicted to be within 8 hours after start of spillage event in winter, and within 11 hours in summer.The first impacted area is predicted to be the coastline between Zichron-Ya'akov/Dor and Atlit. In winter on average, it is predicted that 17% of the spillage is beached, while in summer, twice as higher, i.e. up to 35%. Deposition of spilled condensate in the Hadera desalination plant is estimated to be the highest among the 5 desalination plants examined.Similarly, the main conclusions driven from the 1km pipe rupture spillage counter show that the first impact on the Israel is predicted to be within 5-6 hours after start of spillage in winter, and within 3-4 hours in summer, with the worst case scenario occurring within half an hour after start of the spillage. The coastline of Zichron-Ya'akov is found to be an epicenter of the highest condensate deposition up to 15 tons/km, regardless the season. Due to the proximity of the pipe rupture to the shore, it is predicted that 38-40% of the condensate washed up the shore nearby, without any significant seasonal or monthly variability. The condensate spillage from the pipe rupture located 1 km from the shoreline will affect mostly the Atlit, Ma'agan-Michael and Caesarea National parks’ and the Hadera desalination plant coastlines.

The air-water exchange processes are considered as complicated but very important for the boundary layer structure. The complex physical procedures related to momentum, moisture and thermal exchanges, render their numerical description into a quite challenging task. Ocean surface roughness and spray droplets have an impact on the lower atmospheric layers with profound effects. These involve alterations in the atmospheric stability profiles and microphysical processes such as the formation of sea salt particles. Water vapor produced by sea spray can alter humidity and temperature profiles close to the ocean surface, leading to modified stability conditions. This cascade of effects can be further extended to wind profiles. Sea salt particles derived from water droplet evaporation are a major source of CCN and GCCN that may lead in low cloud formation over the sea and/or the coastal boundary layer. To describe these processes numerically, an atmospheric-wave-spray coupled system is introduced. The RAMS/ICLAMS atmospheric and the WAM wave spectral model are interfaced, including schemes for ocean drag, water droplet thermodynamics and salt particles considered as predictive quantity. Model simulations performed in the Atlantic shoreline showed that droplet evaporation near the surface modifies the atmospheric stability and affects sea salt dispersion.

The Arabian Peninsula is a region characterized by diverse climatic conditions due to its location and geomorphological characteristics. Its precipitation patterns are characterized by very low annual amounts with great seasonal and spatial variability. Moreover, extreme events often lead to flooding and pose threat to human life and activities. Towards a better understanding of the spatiotemporal features of precipitation in the region, a thirty-year (1986-2015) climatic analysis has been prepared with the aid of the state-of-the-art numerical modeling system RAMS/ICLAMS. Its two-way interactive nesting capabilities, explicit cloud microphysical schemes with seven categories of hydrometeors and the ability to handle dust aerosols as predictive quantities are significant advantages over an area where dust is a dominant factor. An extended evaluation based on in situ measurements and satellite records revealed a good model behavior. The analysis was performed in three main components, the mean climatic characteristics, the rainfall trends and the extreme cases. The extremes are analyzed under the principles of the extreme value theory, focusing not only on the duration but also on the intensity of the events. The annual and monthly rainfall patterns are investigated and discussed. The spatial distribution of the precipitation trends revealed insignificant percentage differences in the examined period. Furthermore, it was demonstrated that the eastern part and the top half of the western Arabian Peninsula presented the lowest risk associated with extreme events. Apart from the pure scientific interest, the present study provides useful information for different sectors of society and economy, such as civil protection, constructions and reinsurance.

The effect of extreme wind speeds in applications for design is of great interest in a variety of fields such as meteorology and coastal engineering. In these fields a common problem is the scarcity of long datasets. To overcome this limitation, a common approach is to utilize the entire available dataset using the Peak-Over-Threshold (POT) approach. In small samples there may be a limited number of extremes and so re-sampling is often beneficial. However, the re-samples are often affected by dependency and the independence limitations are usually disregarded. To alleviate this effect, the DeCA Uncorrelated (DeCAUn) model is proposed taking into account the correlation effect when re-sampling. This model provides an improvement to the current physical De-Clustering Algorithm (DeCA), by re-sampling the samples of DeCA irregularly in time. The methodology proposed in this assessment is illustrated using wind speed data from a high resolution database over the North Sea, the Atlantic Ocean and the Mediterranean Sea. From this evaluation, the DeCAUn model is proposed as an alternative re-sampling strategy for observations irregularly spaced in time.

The continuous rise of off-shore activities such as the development of wind farms requires a reliable operational support in order to minimize cost drawbacks and secure operations during the different stages of associated projects. One of the most important parameters for this kind of analysis is wind gustiness. The objective of the study is the development of a methodology for the surface wind gust estimation based on Numerical Weather Prediction Models and statistical post processing. The obtained method has been tested over the offshore west coastline of the United States and evaluated utilizing observational data from the NOAA’s buoy network.

The contribution of natural sources to ambient air particulate matter (PM) concentrations is often not considered; however, it may be significant for certain areas and during specific periods of the year. In the framework of the AIRUSE-LIFE+ project, state-of-the-art methods have been employed for assessing the contribution of major natural sources (African dust, sea salt and forest fires) to PM concentrations, in southern European urban areas. 24 h measurements of PM10 and PM2. 5 mass and chemical composition were performed over the course of a year in five cities: Porto, Barcelona, Milan, Florence and Athens. Net African dust and sea-salt concentrations were calculated based on the methodologies proposed by the EC (SEC 2011/208). The contribution of uncontrolled forest fires was calculated through receptor modelling. Sensitivity analysis with respect to the calculation of African dust was also performed, in order to identify major parameters affecting the estimated net dust concentrations. African dust contribution to PM concentrations was more pronounced in the eastern Mediterranean, with the mean annual relative contribution to PM10 decreasing from 21 % in Athens, to 5 % in Florence, and around 2 % in Milan, Barcelona and Porto. The respective contribution to PM2. 5 was calculated equal to 14 % in Athens and from 1.3 to 2.4 % in all other cities. High seasonal variability of contributions was observed, with dust transport events occurring at different periods in the western and eastern Mediterranean basin. Sea salt was mostly related to the coarse mode and also exhibited significant seasonal variability. Sea-salt concentrations were highest in Porto, with average relative contributions equal to 12.3 % for PM10. Contributions from uncontrolled forest fires were quantified only for Porto and were low on an annual basis (1.4 and 1.9 % to PM10 and PM2. 5, respectively); nevertheless, contributions were greatly increased during events, reaching 20 and 22 % of 24 h PM10 and PM2. 5 concentrations, respectively.

The main concern when utilizing renewable energy resources is their intermittency and variability. One way to deal with this shortcoming is to harvest energy from complementary sources. In this study, wind and wave energy were selected as such and further analyzed in terms of availability, variability, coherence, correlation and potential impact from extreme values. This resource characterization was performed in different timescales, during a 10-year period, using high resolution numerical modeling systems. Based on the results of this analysis, the most suitable areas for combined exploitation were identified and the possible merits from this synergy were pin-pointed and discussed. It was indicated that the most suitable areas for combined use are the western offshore areas of Europe. The wind and wave fields in these open sea areas reveal the lowest correlation in the examined field in contrast to those located in semi-enclosed and enclosed basins that exhibit the highest ones. The joint exploitation in the former regions gives a less variable power output with considerable fewer hours of zero production. Moreover, the suitable energy conversion system for a specific area is strongly dependent on the local characteristics of the available resource.

Over the last decades, wind energy industry has been growing with an increasing rate. This is highly relevant to the need of new wind farm site selection with certain standards such as high wind potential and accessibility. Even in windy areas, low wind speed persistence can be characterized as an extreme (non-frequent) atmospheric condition for the electricity network as it can lead to low or no energy production. The current work is focused on the estimation of the duration and the frequency of occurrence of low wind speed events using the principles of extreme value theory. The two methods used are the ‘intensity given duration’ and the ‘duration given intensity’ that lead to the same point from different perspectives. The data used is derived from a 10 year, hindcast, high-resolution database developed by the Atmospheric Modeling and Weather Forecasting Group of the University of Athens. The great potential and multinational interest concerning energy applications in the North Sea has led to its selection as a study area. The outcome of the study includes the development of intensity–duration–frequency curves as well as a comparison between the two methodologies adopted. Based on these, the largest period of no energy production for a preselected probability of occurrence is estimated for the area of interest. The results of this work could be potentially supportive for studying the regional climatology. Such information can be included in risk assessment techniques and can be applied among others for energy activities. Copyright © 2017 John Wiley & Sons, Ltd.

Este artículo contiene 30 páginas, 14 figuras., The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstreamservices in response to the needs of the heavily populatedMediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level ofMediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN’s Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system.

Deterministic wind power forecasts enclose an inherent uncertainty due to several sources of error. In order to counterbalance this deficiency, an analysis of the error characteristics and construction of probabilistic forecasts with associated confidence levels is necessary for the quantification of the corresponding uncertainty. This work proposes a probabilistic forecasting method using an atmospheric model, optimization techniques for addressing the temporal error dependencies and Kalman filtering for eliminating systematic errors and enhancing the symmetry-normality of the shaped error distributions. The method is applied in case studies, using real time data from four wind farms in Greece. The performance is compared against a reference method as well as other common methods showing an improvement in the predictive reliability.

Nowadays, renewable energy resources are one of the top priority issues for the environmental and political community. In particular, wind and wave energy are two of the most promising solutions, with great potential from research and technological point of view. In this work, an integrated high resolution platform, consisting of state-of-the-art wind-wave numerical models, has been utilized and produced a 10-year database containing all the relevant environmental parameters for a detailed resource assessment over the Greek seas. The results of the atmospheric and sea wave numerical models concerning the environmental parameters that directly affect the wave energy potential were evaluated. High resolution maps for the coastal and offshore areas of Greece present sea wave and wind climatological characteristics, as well as the relevant distribution of the wave energy potential. A number of statistical indices have been employed for analyzing the output of the models, including the potential impact of extreme values and the corresponding distribution of the above parameters, which optimally describe the spatial and temporal analysis of the wave power potential over the area of interest. It is shown that the regions with increased wave energy potential are mainly the western and southern seas of Greece, which are usually exposed to swell from central and south Mediterranean Sea.

The rising demand of energy consumption in isolated locations such as in islands leads in the expansion of on and off-shore wind farms. The optimization of the structural design of wind turbines for such applications requires a risk analysis that is made by using the definition of return periods of extreme events with respect to the lifespan of wind turbines. This work is focusing on the estimation and the analysis of extreme wind speeds by means of the corresponding return periods based on two methods: the Peaks Over Threshold and the Annual Maxima. In addition, different methodologies and tools are tested in order to achieve more accurate results. The data used for the application are both: observations (measurements from Met Stations located on Greek islands) and modeling (a 10-year model hindcast database). The sensitivity test results were used to adjust the methodologies and make 50-year extreme wind speed maps for Northeast Mediterranean (focusing on the sea and the islands). The outcome should be used as a guide for on and off-shore wind energy applications and other construction activities.

The interaction mechanisms between the lower part of the atmosphere and the ocean surface comprise of a complicated issue with many parameters to be studied. Heat, moisture and momentum exchanges in the air-sea system exert a significant role on both lower atmosphere and sea state conditions. Working towards the understanding of how wave characteristics link the atmosphere with the ocean, an atmospheric model is fully coupled with a wave spectral model. The RAMS/ICLAMS atmospheric model is integrated with the WAM wave spectral model under the OASIS-MCT coupler. The combined modeling system utilizes schemes for ocean surface roughness and sea spray droplet thermodynamics. A series of sensitivity tests related to midlatitude cyclones is performed to examine the associated effects of sea state and sea spray impact on wave conditions and lower atmosphere. Under increased wind conditions, sea drag is enhanced as illustrated in the case of the two-way coupling simulations. In addition, increased values of roughness length were traced in near-shore areas in the case of expressions that employ wave parameters such as the wave age. The magnitude and the role of energy yield from sea water droplets depend on the prevailing weather conditions. Sea spray fluxes are amplified in areas with intensified surface winds that also results in an increase of the total heat fluxes. This induces a moistening of the near surface air, an effect in stability profile and an increase of wind speed. The most noticeable impact on marine layer structure emerged close to the first hundred meters. The study revealed an enrichment of the description of the air-sea system through the transition of information between the different models.

Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. The use of numerical wind and wave models gives a credible and convenient way of monitoring the general atmospheric and sea state conditions, especially in the absence of sufficient observational networks. However, when focusing on the study of non-frequent cases, in particular over coastal areas, increased uncertainty in the model outputs and accordingly in the reliability of the estimation of extreme waves becomes an important issue. The current study introduces a methodology to validate and post-process outputs from a high resolution numerical wave modeling system for extreme wave estimation based on the significant wave height. This approach is demonstrated through the data analysis at a relatively deep water site, FINO 1, as well as a relatively shallow water area, coastal site Horns Rev, which is located in the North Sea, west of Denmark. The post-processing targets at correcting the modeled time series of the significant wave height, in order to match the statistics of the corresponding measurements, including not only the conventional parameters such as the mean and standard deviation, but also a new parameter, the second-order spectral moment. This second-order spectral moment is essential for extreme value estimation but has so far been neglected in relevant studies. The improved model results are utilized for the estimation of the 50-year values of significant wave height as a characteristic index of extreme wave conditions. The results from the proposed methodology seem to be in a good agreement with the measurements at both the relatively deep, open water and the shallow, coastal water sites, providing a potentially useful tool for offshore renewable energy applications.

The September 2013 flash flood–triggering rainfall event in Colorado highlighted the strong underestimation of remote sensing techniques over mountainous terrain. In this work, the use of high-resolution rainfall forecasts for adjusting weather radar– [Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation (Q3)] and satellite-based [CPC morphing technique (CMORPH) and TRMM 3B42RT] rainfall estimates is examined. Evaluation of the adjustment procedures is based on the NCEP Stage IV product. Results show that 1-km-grid-resolution rainfall forecasts provided by a numerical weather prediction model [Regional Atmospheric Modeling System and Integrated Community Limited Area Modeling System (RAMS-ICLAMS)] adequately captured total rainfall amounts during the event and could therefore be used to adjust biases in radar and satellite rainfall estimates. Two commonly used adjustment procedures according to 1) mean field bias and 2) probability density function matching are examined. Findings indicate that both procedures are successful in improving the original radar and satellite rainfall estimates, with the first method consistently providing the highest bias reduction while the second exhibits higher improvement in RMSE and correlation.

The use of atmospheric models for wind resource assessment in complex terrain is limited by their coarse resolution. Using non-hydrostatic mesoscale models such as RAMS, fine resolution grids and a proper turbulent closure scheme such as the k – e , it is theoretically possible to describe orographic shear-induced turbulence at microscale level with certain accuracy. In such cases, microscale CFD models modified to represent the interaction of the atmospheric boundary layer with the local orography are proven to show accurate results in idealized cases such as neutral stratification. On the other hand, their limitation in representing real atmospheric interaction between large scale structures and thermal stratification with the flow pattern can introduce significant errors in evaluating wind energy potential. In this work, proper modifications of the RAMS model were performed to simulate 2D wind flow over an isolated hill at high resolution configuration. The results have been compared with the CFD model CRES-Flow-NS and with wind tunnel experimental data. It is found that RAMS is able to reproduce basic flow features with comparable accuracy as the CFD model. This work is part of a major effort to make RAMS a reliable tool for atmospheric flow simulations of various complexity.

Volcanic ash eruptions and mineral dust injection into the atmosphere are of particular importance to the aviation industry. Ash and dust affect almost any aspect of air operations, from airport facilities to cruise flight. This paper is focused on the advantage of using dust forecasting tools and the potential benefit for Air Traffic Management (ATM), flight safety and aircraft performance. It is suggested that state of the art Chemical Weather Prediction (CWP) model coupled with accurate dust cycle module could be a useful operational tool for more efficient Air Traffic Management and aircraft exploitation.

Highly hygroscopic aerosols, such as sodium chloride or sulphates are often present in the atmosphere. They can be produced through several natural or anthropogenic processes (ocean spray, fires, volcanoes, anthropogenic emissions). Their hygroscopicity depends on their chemical properties and thus some of them can serve as cloud condensation nuclei (CCN) easier than others having different impacts on the cloud formation. While the interactions of hygroscopic aerosols with water in the atmosphere is more clearly understood, the impact of aerosols in the resulting precipitation remains inconclusive (Rosenfeld et al. 2008). The thermodynamic state, the background aerosol composition of the atmosphere and the topographical variation of the region can modify these impacts. In this study we use a fully coupled modeling system (atmospheric and chemical—RAMS/ICLAMS) in order to study the impact of highly hygroscopic particles in a cloud system, representing the average thermodynamic conditions of winter convective clouds in the eastern Mediterranean. Of particular interest is the analysis of the level of background pollution in such sensitivity studies. For this reason we applied the material dispersion processes to two characteristic air masses with different pollution levels: clean air masses and highly polluted. This study focuses on the contribution of the material dispersion on the size and number of cloud droplets as well as the liquid and ice mass of the respective cloud system. The dispersion of NaCl (Material 1) resulted in decrease of the amount of ground precipitation, while the background pollution affected the distribution of liquid and ice masses as well as the size of the hydrometeors. In respect to the time of cloud development the effect of the material dispersion was more evident in the mature phase of the cloud system.

The dust cycle plays an important role in the atmospheric processes. The levels of dust concentration in the Arabian cities are quite high, a fact that affects air quality. A better understanding of this phenomenon may lead in reduced impacts. Towards this direction, an integrated modeling approach has been selected and applied in SW Saudi Arabia. More specifically, we discuss the characteristics of the dust production processes using the RAMS/ICLAMS multiscale model. A series of very high resolution simulations have been performed and potential mitigation actions are discussed. A reduction in dust concentration is evident by changing the landscape characteristics. Extreme dust events affect the study areas despite the tested activities and changes. A characteristic example is the “haboobs”.

The physical and chemical characteristics of aerosols are considered as critical for nucleation processes, cloud formation and evolution. The Mediterranean Region is well known for the mixture of aerosols from different origins such as desert dust, sea salt and anthropogenic and biomass burning. Sea salt is in relatively small quantities compared to dust amounts during episodes but its constant presence plays a key role in cloud formation, especially concerning the initial stage. In this work we discuss modeling results related to nucleation processes and cloud formation in the Eastern Mediterranean. Emphasis is given in the impact of sea salt on Marine Boundary Layer (MBL) and orographic cloud formation. The role of other sources of aerosols is also discussed. The modeling tool used for the simulations is the RAMS/ICLAMS fully-coupled modeling system. Satellite data and in situ measurements have been also used for a more comprehensive analysis.

This paper addresses the aerosol effects on radiation and the feedback on meteorology and photochemical activity, applying the online model RAMS/ICLAMS. The model treats meteorology and chemical pollutants on an interactive way. Cloud condensation nuclei (CCN), giant cloud condensation nuclei, and ice nuclei are treated as predictive quantities. The calculation of the aerosol optical properties accounts for size-resolved mineral dust and size- and humidity-dependent optical properties of sea salt. The simulations with and without aerosol impacts reveal the complex direct and indirect mechanisms through which the alteration of radiation fluxes influences meteorology and photochemical processes. For the specific dust event, the reduction in the surface shortwave radiation over cloudless regions affected by dust averages at ~ −75 W m−2 at 12:00 UTC per unit dust loading (1 g m−2). The increase on downwelling longwave radiation over the same areas and time averages at ~ 40 W m−2 per unit dust loading (1 g m−2). Surface upwelling longwave radiation over Mediterranean exhibits a complex daytime behavior. During midnight, the inclusion of dust leads to larger upwelling longwave radiation fluxes over the African continent. The net downward longwave radiation over cloudless areas exhibits an increase both during noon and midnight with the inclusion of dust. The results show that the vertical structure of the dust layer governs the magnitude of the feedback on radiation. The activation of natural particles as CCN causes small changes in radiation fluxes and temperature. Precipitation is influenced more by the indirect rather than the direct and semidirect effects.

Online coupled mesoscale meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and regional climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. Two ways of online coupling can be distinguished: online integrated and online access coupling. Online integrated models simulate meteorology and chemistry over the same grid in one model using one main time step for integration. Online access models use independent meteorology and chemistry modules that might even have different grids, but exchange meteorology and chemistry data on a regular and frequent basis. This article offers a comprehensive review of the current research status of online coupled meteorology and atmospheric chemistry modelling within Europe. Eighteen regional online coupled models developed or being used in Europe are described and compared. Topics discussed include a survey of processes relevant to the interactions between atmospheric physics, dynamics and composition; a brief overview of existing online mesoscale models and European model developments; an analysis on how feedback processes are treated in these models; numerical issues associated with coupled models; and several case studies and model performance evaluation methods. Finally, this article highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities: air quality, numerical meteorology modelling (including weather prediction) and climate modelling. This review will be of particular interest to model developers and users in all three fields as it presents a synthesis of scientific progress and provides recommendations for future research directions and priorities in the development, application and evaluation of online coupled models. This work was realised within and supported by the COST Action ES1004 EuMetChem. Several authors of this article are grateful for the support received from the following projects: EC FP7 TRANSPHORM and PEGASOS, Nordic EnsCLIM, the RF SOL No 11.G34.31.0078 and No 14.B37.21.0880 at RSHU, the US NSF EaSM program (AGS-1049200) at NCSU, the German Science Foundation grant No SCHL-499-4, the Spanish projects “Supercomputación y eCiencia” (CSD2007-0050) and CGL2010-19652, Estonian grants ETAG 7895 and SF0180038s08, and the NASA’s Air Quality Science Team (AQAST) programme. Acknowledgements go to Ralf Wolke (IfT Leipzig, COSMOMUSCAT); Kristian Nielsen, Ashraf Zakey and Roman Nuterman (DMI, Enviro-HIRLAM), Jacek Kaminski, Joanna Struzewska (GEM-AQ); Fabien Solmon (ICTP, RegCM), Maud Leriche, Christine Lac (Meso-NH), Malte Uphoff (Univ. Hamburg, M-SYS), Erik van Meijgaard (KNMI, RACMO2), Claas Teichmann (CSC, REMO-HAM), Bärbel Langmann (Univ. Hamburg, REMOTE), Rohit Mathur, Jon Pleim, Christian Hogrefe (US EPA, WRFCMAQ) for providing detailed information on the named model systems and for valuable comments, Carlos Pérez García-Pando for permission of his figure use, Sabine Ehrenreich for a technical support with the manuscript revision, and all COST ES1004 members for collaboration and productive discussions during COST meetings. The editor David Topping, as well as David Schultz, Jaakko Kukkonen, Mark Z. Jacobson, Shaocai Yu, Peter Builtjes, Rahul Zaveri, Carsten A. Skjoth, Paul A. Makar and 3 anonymous reviewers are thanked for thorough reviews, and for many valuable comments that substantially improved this article.

In this study, the authors investigate the use of high-resolution simulations from the Weather Research and Forecasting Model (WRF) for evaluating satellite rainfall biases of flood-inducing storms in mountainous areas. A probability matching approach is applied to evaluate a power-law relationship between satellite-retrieved and WRF-simulated rain rates over the storm domain. Satellite rainfall in this study is from the NOAA Climate Prediction Center morphing technique (CMORPH). Results are presented based on analyses of five heavy precipitation events that induced flash floods in northern Italy and southern France complex terrain basins. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar rainfall estimates. The authors show that the adjustment procedure reduces the underestimation of high rain rates, thus moderating the magnitude dependence of CMORPH rainfall bias. The Heidke skill score for the WRF-based adjusted CMORPH was consistently higher for a range of rain rate thresholds. This is an indication that the adjustment procedure ameliorates the satellite rain rates to provide a better estimation. Results also indicate that the low rain detection of CMORPH technique is also identifiable in the WRF–CMORPH comparison; however, the adjustment procedure herein does not incorporate this effect on the satellite rainfall bias adjustment.

Mineral dust aerosols exert a significant effect on both solar and terrestrial radiation. By absorbing and scattering, the solar radiation aerosols reduce the amount of energy reaching the surface. In addition, aerosols enhance the greenhouse effect by absorbing and emitting outgoing longwave radiation. Desert dust forcing exhibits large regional and temporal variability due to its short lifetime and diverse optical properties, further complicating the quantification of the direct radiative effect (DRE). The complexity of the links and feedbacks of dust on radiative transfer indicate the need for an integrated approach in order to examine these impacts. In order to examine these feedbacks, the SKIRON limited area model has been upgraded to include the RRTMG (Rapid Radiative Transfer Model – GCM) radiative transfer model that takes into consideration the aerosol radiative effects. It was run for a 6 year period. Two sets of simulations were performed, one without the effects of dust and the other including the radiative feedback. The results were first evaluated using aerosol optical depth data to examine the capabilities of the system in describing the desert dust cycle. Then the aerosol feedback on radiative transfer was quantified and the links between dust and radiation were studied. The study has revealed a strong interaction between dust particles and solar and terrestrial radiation, with several implications on the energy budget of the atmosphere. A profound effect is the increased absorption (in the shortwave and longwave) in the lower troposphere and the induced modification of the atmospheric temperature profile. These feedbacks depend strongly on the spatial distribution of dust and have more profound effects where the number of particles is greater, such as near their source.

The issue of wind power prediction is approached in this work by means of numerical and statistical prediction models. Two high resolution regional atmospheric systems are employed in order to provide accurate local wind forecasts while a combination of statistical post processes is utilized targeting to the local adaptation of the results and the reduction of possible systematic biases. A variety of power estimation models are employed for the prediction of the wind power potential in real time applications over two areas of Greece: the islands of Crete and Kefalonia. The results obtained prove that accurate power prediction can be reached if the local environmental conditions are credibly estimated while the use of the power output in previous time steps do not contribute significantly to the improvement of the final forecast.

Se comparan las mediciones del espesor optico de aerosoles (AOD) de polvo del Sahara realizadas en Camaguey, Cuba, durante Julio del 2009 con valores pronosticados de AOD por el modelo SKIRON y con mediciones de AOD realizadas por los satelites MODIS. Las diferencias entre las medias diarias del AOD pronosticado por SKIRON y medido por MODIS (tanto Terra como Aqua) son menores que las diferencias entre los maximos diarios. Los resultados demuestran la capacidad de desarrollar un sistema de alerta y seguimiento de los eventos de polvo del Sahara a traves del Atlantico.

The issue of ocean wave analysis and forecasting is today of increasing importance for a variety of scientific and social-economic purposes. In this framework, a number of state-of-the-art research and operational tools have been developed, mainly based on numerical modeling and advanced statistical techniques. The performance of the latter is essentially dependant on the utilization of external information (remote sensing and in situ measurements). In this work, a combination of ocean wave numerical models, statistical Kalman filters and data assimilation techniques is used for improvement of simulation-accuracy. More precisely, the systematic deviations of the wave model results are minimized by the use of Kalman filtering algorithms in areas with continuous flow of observations. Then, the improved outputs are assimilated by an optimum interpolation scheme, into the forecasting period of the wave model, in order to extend the assimilation impact in time and space. The case studied concerns four one-monthly intervals in the North Atlantic Ocean.

The formation and propagation of density currents are well studied processes in fluid dynamics with many applications in other science fields. In the atmosphere, density currents are usually meso-β/γ phenomena and are often associated with storm downdrafts. These storms are responsible for the formation of severe dust episodes (haboobs) over desert areas. In the present study, the formation of a convective cool pool and the associated dust mobilization are examined for a representative event over the western part of Sahara desert. The physical processes involved in the mobilization of dust are described with the use of the integrated atmospheric-air quality RAMS/ICLAMS model. Dust is effectively produced due to the development of near surface vortices and increased turbulent mixing along the frontal line. Increased dust emissions and recirculation of the elevated particles inside the head of the density current result in the formation of a moving "dust wall". Transport of the dust particles in higher layers – outside of the density current – occurs mainly in three ways: (1) Uplifting of preexisting dust over the frontal line with the aid of the strong updraft (2) Entrainment at the upper part of the density current head due to turbulent mixing (3) Vertical mixing after the dilution of the system. The role of the dust in the associated convective cloud system was found to be limited. Proper representation of convective processes and dust mobilization requires the use of high resolution (cloud resolving) model configuration and online parameterization of dust production. Haboob-type dust storms are effective dust sources and should be treated accordingly in dust modeling applications.

Flash floods develop over small spatiotemporal scales, an attribute that makes their predictability a particularlychallenging task. The serious threat they pose for human lives, along with damage estimates that canexceed one billion U.S. dollars in some cases, urge toward more accurate forecasting. Recent advances in mputational science combined with state-of-the-art atmospheric models allow atmospheric simulations atvery fine (i.e., subkilometer) grid scales, an element that is deemed important for capturing the initiation andevolution of flash flood–triggering storms. This work provides some evidence on the relative gain that can beexpected from the adoption of such subkilometer model grids.Anecessary insight into the complex processesof these severe incidents is provided through the simulation of three flood-inducing heavy precipitation eventsin the Alps for a range of model grid scales (0.25, 1, and 4 km) with the Regional Atmospheric ModelingSystem–Integrated Community Limited Area Modeling System (RAMS–ICLAMS) atmospheric model. Adistributed hydrologic model [Kinematic Local Excess Model (KLEM)] is forced with the various atmospheric simulation outputs to further evaluate the relative impact of atmospheric model resolution on thehydrologic prediction. The use of a finer grid is beneficial in most cases, yet there are events where theimprovement is marginal. This underlines why the use of finer scales is a step in the right direction but not asolitary component of a successful flash flood–forecasting recipe.

Air-sea interaction is a very complicated problem with many parameters that need to be studied. Wind profile near the sea surface is significantly affected by the wave characteristics (e.g. white cap formation, wave height), sea spraying and droplet evaporation. Moreover, sea spraying could be responsible for alterations in the stability conditions and the flow might become over-stable and semi-laminar. Working towards the analysis and study of the above issues, the development of a direct coupled system between the atmospheric system RAMS/ICLAMS and the wave model WAM is proposed with the additional online implementation of wave parameters into the atmospheric model. Test cases of different coupling approaches over the Atlantic and Mediterranean shoreline are performed towards the quantification of improvement of relevant high resolution wave and wind forecasts.

Within a complex and competitive framework set by today’s research activities in environmental sciences, atmospheric datasets of high accuracy are required along with statistical analysis beyond the conventional standards. In particular, the credible evaluation of potential extreme conditions related to wind speed, is of critical importance for a number of applications such as wind farm siting, marine applications, pollutant dispersion associated to accidents etc. In the present work, a multi-parametric approach based on the principles of Extreme Value Theory is discussed. This approach is focused both on the upper and lower tail of wind speed probability distribution. More specifically Intensity-Duration-Frequency (IDF) curves are adopted to depict the relation between wind speed and the duration of the event in terms of return periods. The outcomes of the IDF curves are compared to other methodologies while various tools are employed for the fine tuning of the proposed techniques and the quantification of the associated uncertainties. For the needs of the study, a 10-year, hindcast simulation of the numerical atmospheric model Skiron coupled with the wave model WAM is utilized. The study area is the Mediterranean, focusing especially on areas with increased interest for renewable energy activities.

Geographical Information Systems (GIS) are commonly used in renewable energy resource analysis to establish optimal locations for development. Previous work focuses either on a single technology with fixed site-selection criteria, or on small, localised areas. The potential for combining or co-locating different offshore energy technologies, particularly over a large region, has been explored previously but at a relatively low level of detail. Here, bespoke resource data from high resolution co-located, co-temporal wind and wave models are presented in a GIS with a range of additional environmental and physical parameters. Dedicated decision-support tools have been developed to facilitate flexible, multi-criteria site selections specifically for combined wind-wave energy platforms, focusing on the energy resources available. Time-series tools highlight some of the more detailed factors impacting on a site-selection decision. The results show that the main potential for combined technologies in Europe is focused to the north and west due to strong resources and acceptable depth conditions, but that there are still obstacles to be overcome in terms of constructability and accessibility. The most extreme conditions generally coincide with the maximum energy output, and access to these sites is more limited.

Airborne particles of anthropogenic and/or natural origin have certain direct and indirect effects in the atmosphere. Radiative transfer is the category of processes related to aerosols and clouds (direct effects). Indirect effects are always associated with condensates at various atmospheric layers. Condensation within the tropospheric layers is mainly related to aerosol physical and chemical properties, thermodynamical and dynamical processes. As it was found in various studies, there is a strong relationship between aerosols and extreme weather events such as deep convection and extreme rainfall. Low-level condensation is associated with low-cloud formation and fog. In this presentation we will discuss the condensation processes within the lower and upper troposphere and how they are affected by the various types of aerosols. New model development related to nucleation processes and condensation at different levels is discussed. The model used for development and application is the fully-coupled atmospheric modeling system RAMS/ICLAMS. Model simulations have been performed for selected cases related to (i) extreme precipitation events and (ii) low-level condensation and fog formation in the Euro-Mediterranean and Arabian Peninsula. The sensitivity tests showed that the explicit activation of aerosols as CCN and IN causes changes in the precipitation distribution as well as in its spatiotemporal patterns. Fog formation near the coastline and low-cloud formation mechanisms are controlled by the thermal cooling and moisture evaporation by the surface. The accurate simulation of the microphysical processes involved in formation and dissipation of fog depends on several variables.

Marine Geophysical Research, DOI 10.1007/s11001-011-9142-0 The article of record as published may be located at http://dx.doi.org/10.1007/s11001-011-9142-0 In this paper the main wave height characteristics in the Mediterranean Sea are studied from both observational and numerical perspectives. The numerical wave model WAM is employed on a high spatial resolution mode and in two different versions, one of which incorporates information for sea surface currents. Altimeter data obtained from all available satellite missions over the area are also utilized. The data sets are analyzed both by conventional statistical measures as well as by advanced techniques provided by a relatively new branch of mathematics, information geometry, in the framework of which the data under study and the distributions that they form are treated as elements of non Euclidean spaces. In this framework, novel ideas for the estimation of the deviations between the observed and modeled values are proposed.

Hourly solar and photovoltaic (PV) forecasts for horizons between 0 and 48h ahead were developed using Environment Canada’s Global Environmental Multiscale model. The motivation for this research was to explore PV forecasting in Ontario, Canada, where feed-in tariffs are driving rapid growth in installed PV capacity. The solar and PV forecasts were compared with irradiance data from 10 North-American ground stations and with alternating current power data from three Canadian PV systems. A 1-year period was used to train the forecasts, and the following year was used for testing. Two post-processing methods were applied to the solar forecasts: spatial averaging and bias removal using a Kalman filter. On average, these two methods lead to a 43% reduction in root mean square error (RMSE) over a persistence forecast (skill score=0.67) and to a 15% reduction in RMSE over the Global Environmental Multiscale forecasts without post-processing (skill score=0.28). Bias removal was primarily useful when considering a “regional”forecast for the average irradiance of the 10 ground stations because bias was a more significant fraction of RMSE in this case. PV forecast accuracy was influenced mainly by the underlying (horizontal) solar forecast accuracy, with RMSE ranging from 6.4% to 9.2% of rated power for the individual PV systems. About 76% of the PV forecast errors were within � 5% of the rated power for the individual systems, but the largest errors reached up to 44% to 57% of rated power. © Her Majesty the Queen in Right of Canada 2011. Reproduced with the permission of the Minister of Natural Resources Canada.

The main characteristics of the significant wave height in an area of increased interest, the north Atlantic ocean, are studied based on satellite records and corresponding simulations obtained from the numerical wave prediction model WAM. The two data sets are analyzed by means of a variety of statistical measures mainly focusing on the distributions that they form. Moreover, new techniques for the estimation and minimization of the discrepancies between the observed and modeled values are proposed based on ideas and methodologies from a relatively new branch of mathematics, information geometry. The results obtained prove that the modeled values overestimate the corresponding observations through the whole study period. On the other hand, 2-parameter Weibull distributions fit well the data in the study. However, one cannot use the same probability density function for describing the whole study area since the corresponding scale and shape parameters deviate significantly for points belonging to different regions. This variation should be taken into account in optimization or assimilation procedures, which is possible by means of information geometry techniques.

This paper describes the development of a decision support system (DSS) for prevention planning and emergency management of forest fire events that incorporates weather data management, a geographical data viewer, a priori danger forecasting and fire propagation modeling, automatic fire detection, and optimal resource dispatching. Collection, input, storage, management, and analysis of the information rely on advanced and automated methodologies using remote sensing, GPS, digital mapping, and geographic information systems. The results included short-term dynamic fire danger indices developed for improved and realistic prevention and pre-suppression planning. An automatic fire detection technology based on infrared video was developed and successfully tested on site. Several models for understanding fire propagation on forest fires have been proposed for practical application. Additionally, a DSS was developed with the innovation of covering wildland fire hazard management entirely, providing a complete coverage of technical and administrative activities that support decision makers in real time. The DSS was tested for high fire seasons in two different sites in South Europe.