49 research outputs found

    Evaluation of future diurnal variability and projected changes in extremes of precipitation and temperature and their impacts on crop production over regional case studies (e.g. Agroscenari case studies)

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    The daily weather of the four decades were used as input to EPIC simulation model to test the effects on crop yield, crop evapotranspiration, number of days with water and nitrogen stress in the silage maize -Italian ryegrass irrigated cropping systems in the Oristanese case study area.The monthly DTR (diurnal temperature range) pattern predicted for the FC (future climate, 2020-2030) indicates that spring and summer months are the most sensitive to DTR increase. The increase ryegrass yield simulated by EPIC under FC was interpreted as the positive effects on increased temperature on the winter-spring grass growth rates. The decreased production of maize was attributed to a shortening of the crop cycle, which reduced the intercepted radiation. The simulations run to assess the pure effect of DTR shift indicated almost no effects on crop yield but significant effects on crop evapotranspiration, whose increase observed under FC was largely associated to DTR, particularly in maize. The stochastic generation of daily weather with WXGEN indicates a sufficient accuracy for average DTR patterns and the central part of the daily DTR distribution, while the range of absolute values increased substantially, in relation to the increased probability of extremes in one century vs one decade.(Abstract supplied by the publisher

    A synoptic characterization of the dust transport and associated thermal anomalies in the Mediterranean basin

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    Presentación realizada para las XXXII Jornadas Científicas de la Asociación Meteorológica Española y 13º Encuentro Hispano-Luso de Meteorología celebrados en Alcobendas (Madrid), del 28 al 30 de mayo de 2012

    a novel computational model of the wheat global market with an application to the 2010 russian federation case

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    In this paper, we build a computational model for the analysis of international wheat spot price formation, its dynamics and the dynamics of quantities traded internationally. The model has been calibrated using FAOSTAT data to evaluate its in-sample predictive power. The model is able to generate wheat prices in twelve international markets and traded wheat quantities in twenty-four world regions. The time span considered is from 1992 to 2013. In our study, particular attention was paid to the impact of the Russian Federation's 2010 grain export ban on wheat price and quantities traded internationally. Among other results, we found that the average weighted world wheat price in 2013 would have been 3.55% lower than the observed one if the Russian Federation had not imposed the export ban in 2010

    Competencies based innovative learning solutions for co-development of climate services in West Africa

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    Abstract. In developing countries, and particularly in West Africa, the role of Climate Services (CS) for sustainable development is growing thanks to wide spreading collaboration among European institutions, including National Meteorological and Hydrological Services (NMHS) research centers, universities, and homologue local institutions. Operationally, the implementation of CSs in developing countries is mainly pivoted on NMHS, which, according to the World Meteorological Organization (WMO), are dramatically affected by unmet learning demand. The global scale of learning needs for co-development of CSs calls for innovative solutions and a range of flexible modalities to reach learners in a variety of ways, and for sharing resources and successful strategies within the global education and training community. In order to harmonize expected learning outcomes, WMO defined a competency framework (CF) for CSs to be used in the implementation of training initiatives and knowledge sharing tools. This paper presents the strategic and methodological approach adopted in the implementation of the TOPaCS, a new knowledge-based distance learning initiative, aiming to provide a flexible learning environment within the CSs CF of WMO ensuring coherence with other WMO education initiatives (Global Campus, other RTCs, etc.). The methodological approach adopted is based on the competency-based approach to training, where competencies are composed by elements of knowledge and skill. TOPaCS integrates the WMO CF for CSs into a taxonomy co-designed with stakeholders at different levels, and allows the definition of learning paths, which are a further interactive opportunity for co-development of CSs within the TOPaCS learning ecosystem. Indeed, the approach aims also to guide further instructional strategies and assessments and becomes a starting point to build a common language enabling a better cooperation and exchange between the different CSs training initiatives

    Perceptions of Present and Future Climate Change Impacts on Water Availability for Agricultural Systems in the Western Mediterranean Region

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    Many Mediterranean countries have experienced water shortages during the last 20 years and future climate change projections foresee further pressure on water resources. This will have significant implications for irrigation water management in agricultural systems in the future. Through qualitative and quantitative empirical research methods carried out on a case study on four Mediterranean farming systems located in Oristano, Italy, we sought to understand the relationship between farmers' perceptions of climate change (i.e., increased temperature and decreased precipitation) and of present and future water availability for agriculture as forecasted by climatic and crop models. We also explored asymmetries between farmers' perceptions and present and future climate change and water scenarios as well as factors influencing perceptions. Our hypotheses were that farmers' perceptions are the main drivers of actual water management practices and that sustainable practices can emerge from learning spaces designed from the understanding of the gaps between perceptions and scientific evidences. Results showed that most farmers perceived that climate change is occurring or will occur in their area. They also perceived that there has been an increased temperature trend, but also increased precipitation. Therefore, they are convinced that they have and will have enough irrigation water for agriculture in the near future, while climate change projections foresee an increasing pressure on water resources in the Mediterranean region. Such results suggest the need for (i) irrigation management policies that take into account farmers' perceptions in order to promote virtuous behaviors and improve irrigation water use efficiency; (ii) new, well-designed learning spaces to improve the understanding on climate change expectations in the near future in order to support effective adaptive responses at the farm and catchment scales

    Within-season predictions of durum wheat yield over the Mediterranean Basin

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    Crop yield is the result of the interactions between weather in the incoming season and how farmers decide to manage and protect their crops. According to Jones et al. (2000), uncertainties in the weather of the forthcoming season leads farmers to lose some productivity by taking management decisions based on their own experience of the climate or by adopting conservative strategies aimed at reducing the risks. Accordingly, predicting crop yield in advance, in response to different managements, environments and weathers would assist farm-management decisions(Lawless and Semenov, 2005). Following the approach described by Semenov and Doblas-Reyes (2007), this study aimed at assessing the utility of different seasonal forecasting methodologies in predicting durum wheat yield at 10 different sites across the Mediterranean Basin. The crop model, SiriusQuality (Martre et al., 2006), was used to compute wheat yield over a 10-years period. First, the model was run with a set of observed weather data to calculate the reference yield distributions. Then, starting from 1st January, yield predictions were produced at a monthly time-step using seasonal forecasts. The results were compared with the reference yields to assess the efficacy of the forecasting methodologies to estimate within-season yields. The results indicate that  durum wheat phenology and yield can be accurately predicted under Mediterranean conditions well before crop maturity, although some differences between the sites and the forecasting methodologies were revealed. Useful information can be thus provided for helping farmers to reduce negative impacts or take advantage from favorable conditions
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