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ABSTRACTWind power forecasts are useful tools for power load balancing, energy trading and wind farm operations. Long range monthly‐to‐seasonal forecasting allows the prediction of departures from average weather conditions beyond traditional weather forecast timescales, months in advance. However, it has not yet been demonstrated how these forecasts can be optimally transformed to wind power. The predictable part of a seasonal forecast is for longer monthly averages, not daily averages, but to use monthly averages misses information on variability. To investigate, here a model relating average weather conditions to average wind power output was built, based on the relationship between instantaneous wind speed and power production and incorporating fluctuations in air density due to temperature and wind speed variability. Observed monthly average power output from UK stations was used to validate the model and to investigate the optimal temporal resolution for the data used to drive the model. Multiple simulations of wind power were performed based on reanalysis data, making separate simulations based on monthly, daily and sub‐daily averages, using a distribution defined by the mean across the period to incorporate information on variability. Basing the simulation on monthly averages alone is sub‐optimal: using daily average winds gives the highest correlation against observations. No improvement over this is gained by using sub‐daily averages or including temperature variability. This signifies that to transform seasonal forecasts to wind power a compromise must be made between using the daily averages with debatable skill and the more predictable monthly averages, losing information on day‐to‐day variability.

The objective of this paper is to explain novel sustainable robotics solutions for cities. Those new proposals appear under the ECHORD++ project which is a good tool to meet academia and industry with the objective of providing innovative technological solutions. In this paper, authors explain the tool as well as the methodology to promote robotics research in urban environments, and the on-going experience will demonstrate that huge advances are made in this field. Peer Reviewed

AbstractSki tourism is a major sector of mountain regions economy, which is under the threat of long-term climate change. Snow management, and in particular grooming and artificial snowmaking, has become a routine component of ski resort operations, holding potential for counteracting the detrimental effect of natural snow decline. However, conventional snowmaking can only operate under specific meteorological conditions. Whether snowmaking is a relevant adaptation measure under future climate change is a widely debated issue in mountainous regions, with major implications on the supply side of this tourism industry. This often lacks comprehensive scientific studies for informing public and private decisions in this sector. Here we show how climate change influences the operating conditions of one of the main ski tourism markets worldwide, the French Alps. Our study addresses snow reliability in 129 ski resorts in the French Alps in the 21st century, using a dedicated snowpack model explicitly accounting for grooming and snowmaking driven by a large ensemble of adjusted and downscaled regional climate projections, and using a geospatial model of ski resorts organization. A 45% snowmaking fractional coverage, representative of the infrastructures in the early 2020s, is projected to improve snow reliability over grooming-only snow conditions, both during the reference period 1986–2005 and below 2 °C global warming since pre-industrial. Beyond 3 °C of global warming, with 45% snowmaking coverage, snow conditions would become frequently unreliable and induce higher water requirements.

The energy consumption of the current building stock represents about 40% of the total final energy consumption in Europe. New gamification techniques may play a significant role in helping users adopt new and more energy efficient behaviours. This paper presents the advances achieved within the context of the EU-funded project EnerGAware - Energy Game for Awareness of energy efficiency in social housing communities. The main objective of the project, funded by the European Union under the Horizon2020 programme, is to reduce the energy consumption and carbon emissions in a sample of European social housing by changing the energy efficiency behaviour of the social tenants through the implementation of a serious game linked to the real energy use of the participants’ homes. Peer Reviewed

SEPServer is a three-year collaborative project funded by the seventh framework programme (FP7-SPACE) of the European Union. The objective of the project is to provide access to state-of-the-art observations and analysis tools for the scientific community on solar energetic particle (SEP) events and related electromagnetic (EM) emissions. The project will eventually lead to better understanding of the particle acceleration and transport processes at the Sun and in the inner heliosphere. These processes lead to SEP events that form one of the key elements of space weather. In this paper we present the first results from the systematic analysis work performed on the following datasets: SOHO/ERNE, SOHO/EPHIN, ACE/EPAM, Wind/WAVES and GOES X-rays. A catalogue of SEP events at 1 AU, with complete coverage over solar cycle 23, based on high-energy (~68-MeV) protons from SOHO/ERNE and electron recordings of the events by SOHO/EPHIN and ACE/EPAM are presented. A total of 115 energetic particle events have been identified and analysed using velocity dispersion analysis (VDA) for protons and time-shifting analysis (TSA) for electrons and protons in order to infer the SEP release times at the Sun. EM observations during the times of the SEP event onset have been gathered and compared to the release time estimates of particles. Data from those events that occurred during the European day-time, i.e., those that also have observations from ground-based observatories included in SEPServer, are listed and a preliminary analysis of their associations is presented. We find that VDA results for protons can be a useful tool for the analysis of proton release times, but if the derived proton path length is out of a range of 1 AU < s[3 AU, the result of the analysis may be compromised, as indicated by the anti-correlation of the derived path length and release time delay from the asso ciated X-ray flare. The average path length derived from VDA is about 1.9 times the nominal length of the spiral magnetic field line. This implies that the path length of first-arriving MeV to deka-MeV protons is affected by interplanetary scattering. TSA of near-relativistic electrons results in a release time that shows significant scatter with respect to the EM emissions but with a trend of being delayed more with increasing distance between the flare and the nominal footpoint of the Earth-connected field line.

38 Pags.- 3 Figs. The definitive version is available at: http://link.springer.com/journal/13593 Dryland areas cover about 41 % of the Earth’s surface and sustain over 2 billion inhabitants. Soil carbon (C) in dryland areas is of crucial importance to maintain soil quality and productivity and a range of ecosystem services. Soil mismanagement has led to a significant loss of carbon in these areas, which in many of them entailed several land degradation processes such as soil erosion, reduction in crop productivity, lower soil water holding capacity, a decline in soil biodiversity, and, ultimately, desertification, hunger and poverty in developing countries. As a consequence, in dryland areas proper management practices and land use policies need to be implemented to increase the amount of C sequestered in the soil. When properly managed, dryland soils have a great potential to sequester carbon if financial incentives for implementation are provided. Dryland soils contain the largest pool of inorganic C. However, contrasting results are found in the literature on the magnitude of inorganic C sequestration under different management regimes. The rise of atmospheric carbon dioxide (CO2) levels will greatly affect dryland soils, since the positive effect of CO2 on crop productivity will be offset by a decrease of precipitation, thus increasing the susceptibility to soil erosion and crop failure. In dryland agriculture, any removal of crop residues implies a loss of soil organic carbon (SOC). Therefore, the adoption of no-tillage practices in field crops and growing cover crops in tree crops have a great potential in dryland areas due to the associated benefits of maintaining the soil surface covered by crop residues. Up to 80 % reduction in soil erosion has been reported when using no-tillage compared with conventional tillage. However, no-tillage must be maintained over the long term to enhance soil macroporosity and offset the emission of nitrous oxide (N2O) associated to the greater amount of water stored in the soil when no-tillage is used. Furthermore, the use of long fallow periods appears to be an inefficient practice for water conservation, since only 10–35 % of the rainfall received is available for the next crop when fallow is included in the rotation. Nevertheless, conservation agriculture practices are unlikely to be adopted in some developing countries where the need of crop residues for soil protection competes with other uses. Crop rotations, cover crops, crop residue retention, and conservation agriculture have a direct positive impact on biodiversity and other ecosystem services such as weed seed predation, abundance and distribution of a broad range of soil organisms, and bird nesting density and success. The objective of sequestering a significant amount of C in dryland soils is attainable and will result in social and environmental benefits. This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (grants AGL 2013-49062-C4-1-R and AGL 2013-49062-C4-4-R). Peer reviewed