No abstract

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

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.

Solar systems based on the coupling of parabolic concentrating collectors and thermal engines (i.e. dish-Stirling systems) are among the most efficient generators of solar power currently available. This study focuses on the modelling of functioning data from a 32 kWe dish-Stirling solar plant installed at a facility test site on the University of Palermo campus, in Southern Italy. The proposed model, based on real monitored data, the energy balance of the collector and the partial load efficiency of the Stirling engine, can be used easily to simulate the annual energy production of such systems, making use of the solar radiation database, with the aim of encouraging a greater commercialisation of this technology. Introducing further simplifying assumptions based on our experimental data, the model can be linearised providing a new analytical expression of the parameters that characterise the widely used Stine empirical model. The model was calibrated against datacorresponding to the collector with clean mirrors and used to predict the net electric production of the dish-Stirling accurately. A numerical method for assessing the daily level of mirror soiling without the use of direct reflectivity measures was also defined. The proposed methodology was used to evaluate the history of mirror soiling for the observation period, which shows a strong correlation with the recorded sequence of rains and dust depositions. The results of this study emphasise how desert dust transport events, frequent occurrences in parts of the Mediterranean, can have a dramatic impact on the electric power generation of dish-Stirling plants.

The climate of the Arabian Peninsula is characterized by significant spatial and temporal variations, due to its complex topography and the large-scale atmospheric circulation. Furthermore, the role of dust in the formation of regional climate is considered to be crucial. In this work, the regional climatology for the Arabian Peninsula has been studied by employing a high resolution state of the art atmospheric model that included sophisticated physical parameterization schemes and online treatment of natural aerosol particles. The simulations covered a 30-year period (1986–2015) with a temporal resolution of 3 h and a spatial distance of 9 km. The main focus was given to the spatial and temporal variations of mean temperature and temperature extremes, wind speed and direction, and relative humidity. The results were evaluated using in situ measurements indicating a good agreement. An examination of possible climatic changes during the present climate was also performed through a comprehensive analysis of the trends of mean temperature and temperature extremes. The statistical significant trend values were overall positive and increased over the northwestern parts of the examined area. Similar spatial distributions were found for the daily minimum and maximum temperatures. Higher positive values emerged for the daily maxima.