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Meteorological and Climate Modelling Services Tailored to Viticulturists

Atmospheric and Climate Sciences 2021年第1期11卷 148-164页

作者： ignasi porras Josep Maria Solé Raül Marcos Raúl Arasa Meteosim SL Barcelona Spain Barcelona Supercomputing Center (BSC) Barcelona Spain

Grape production is likewise inherently interconnected to climate and weather, and, although grapes may grow worldwide, premium wine-grape production occurs in Mediterranean-like climate ranges. Changes in climate and weather patterns are threatening premium wine-grapes, directly affecting the European wine industry. This is because grapevines are extremely sensitive to their surrounding environment, with seasonal variations in yield much higher than other common crops, such as cereals. With a view to making South European wine industry resilient to climate change, VISCA (Vineyards Integrated Smart Climate Application) project has deployed a Climate Service (CS) Decision Support System (DSS) tool that provides to wine producers with well-founded information to be able to apply correctly adaptation strategies on specific grape varieties and locations, and to achieve optimum production results (e.g., yield and quantity). In this paper we show the meteorological, seasonal and climatic models and data sets used to answer the viticulturist needs;from short-term and mid-term forecast to seasonal forecast and climate projections.

关键词： Weather Extreme Events Adaptation to Climate Change Climate Services Wine Industry VISCA

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Assessment of Climate Change in Nicaragua: Analysis of Precipitation and Temperature by Dynamical Downscaling over a 30-Year Horizon

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Atmospheric and Climate Sciences 2016年第3期6卷 445-474页

作者： Josep Maria Solé Raúl Arasa Miquel Picanyol Mª Ángeles González Anna Domingo-Dalmau Marta Masdeu ignasi porras Bernat Codina Technical Department Meteosim S.L. Barcelona Spain Department of Astronomy and Meteorology University of Barcelona Barcelona Spain

The present study has generated and analyzed Climate Change projections in Nicaragua for the period 2010-2040. The obtained results are to be used for evaluating and planning more resilient transport infrastructures in the next decades. This study has focused its efforts to pay attention into the effect of Climate Change on precipitation and temperature from a mean and extreme event perspective. Dynamical Downscaling approach on a 4 km resolution grid has been chosen as the most appropriate methodology for the estimation of the projected climate, being able to account for local-scale factors like complex topography or local land uses properly. We selected MPI-ESM-MR as the global climate model with the best skill scores in terms of precipitation and temperature in Nicaragua. MPI-ESM-MR was coupled to a mesoscale model. We chose WRF mesoescale model as the most appropriate regional model and we optimized their physical and dynamical options in order to minimize the model uncertainty in Nicaragua. For this, model output against the available in-situ measurements from the national meteorological station network and satellite data were compared. Climate change signal was estimated by comparing the different climate statistics calculated from a model run over an historical period, 1980-2009, with a model run over a projected period, 2010-2040. The obtained results from the projected climate show an increase of the mean temperature between 0.6°C and 0.8°C and an increase of the number of days per year with maximum daily temperatures higher than 35°C. Regarding precipitation, annual projected amounts do not change remarkably with respect to the historical period. However, significant changes in the distribution of the precipitation within the wet period (May-October) were observed. Moreover, an increment between 5% and 10% of the number of days without precipitation is expected. Finally, Intensity-Duration-Frequency (IDF) projected curves show an increment of the rainfall

关键词： WRF Climate Change Global Warming Dynamical Downscaling Precipitation Projections IDF

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Defining a Standard Methodology to Obtain Optimum WRF Configuration for Operational Forecast: Application over the Port of Huelva (Southern Spain)

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Atmospheric and Climate Sciences 2016年第2期6卷 329-350页

作者： Raúl Arasa ignasi porras Anna Domingo-Dalmau Miquel Picanyol Bernat Codina Mª Ángeles González Jésica Piñón Technical Department Meteosim S.L. Barcelona Spain Department of Astronomy and Meteorology University of Barcelona Barcelona Spain

In this contribution, we calibrate the meteorological model weather and research forecasting (WRF) for operational forecasting in the Port of Huelva managed by the Authority Port of Huelva. Meteorological forecasting will allow reducing the impact of the meteorological phenomena over weather sensitive activities in the region. Concretely, the meteorological modeling developed will be used to analyze meteorological hazard impacts and to improve the management of the local air quality. To achieve these goals, numerous sensitive analyses corresponding to different model options have been developed. These analyses consider different physical and dynamical options, the coupling of very high resolution physiographic database (topography and land uses), and data assimilation. Comparing experiments, results with observational measures provide us by the Spanish National Meteorology Agency (AEMET). During a representative period, the optimum WRF configuration for the region is obtained. Calibration has been focused on wind due to this is the main risk factor in the region. When the model is satisfactorily calibrated, WRF is evaluated using whole modeling years 2012 and 2013, working with very high horizontal resolution, up to 0.333 km of horizontal grid resolution. Results obtained from the evaluation indicate that the numerical weather prediction system developed has a confidence level of 70% for the temperature, 81% and 66% for the wind speed and wind direction respectively, and 90% for the relative humidity. Methodology designed defines the quality control assurance of high-accuracy forecasting services of Meteosim S.L.

关键词： WRF Sensitive Analysis Meteorological Modelling Physical Options LES High Resolution

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