The visualisation and communication of probabilistic climate forecasts to renewable energy policy makers

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Conference contribution (talk)
AGU Fall Meeting 2013
Francisco J. Doblas-Reyes
Sophie Steffen
Rachel Lowe
Melanie Davis
Xavier Rodó
Monday, December 9, 2013 to Friday, December 13, 2013
Despite the strong dependence of weather and climate variability on the renewable energy industry, and several initiatives towards demonstrating the added benefits of integrating probabilistic forecasts into energy decision making process, they are still under-utilised within the sector. Improved communication is fundamental to stimulate the use of climate forecast information within decision-making processes, in order to adapt to a highly climate dependent renewable energy industry. This paper focuses on improving the visualisation of climate forecast information, paying special attention to seasonal to decadal (s2d) timescales. This is central to enhance climate services for renewable energy, and optimise the usefulness and usability of inherently complex climate information. In the realm of the Global Framework for Climate Services (GFCS) initiative, and subsequent European projects: Seasonal-to-Decadal Climate Prediction for the Improvement of European Climate Service (SPECS) and the European Provision of Regional Impacts Assessment in Seasonal and Decadal Timescales (EUPORIAS), this paper investigates the visualisation and communication of s2d forecasts with regards to their usefulness and usability, to enable the development of a European climate service. The target end user will be renewable energy policy makers, who are central to enhance climate services for the energy industry. The overall objective is to promote the wide-range dissemination and exchange of actionable climate information based on s2d forecasts from Global Producing Centres (GPC's). Therefore, it is crucial to examine the existing main barriers and deficits. Examples of probabilistic climate forecasts from different GPC's were used to prepare a catalogue of current approaches, to assess their advantages and limitations and finally to recommend better alternatives. In parallel, interviews were conducted with renewable energy stakeholders to receive feedback for the improvement of existing visualisation techniques of forecasts. The overall aim is to establish a communication protocol for the visualisation of probabilistic climate forecasts, which does not currently exist. Global Producing Centres show their own probabilistic forecasts with limited consistency in their communication across different centres, which complicates the understanding for the end user. A communication protocol for both the visualisation and description of climate forecasts can help to introduce a standard format and message to end users from several climate-sensitive sectors, such as energy, tourism, agriculture and health. It is hoped that this work will facilitate the improvement of decision-making processes relying on forecast information and enable their wide-range dissemination based on a standardised approach.


RESILIENCE aims to strengthen the efficiency and security of wind power supply within energy networks, by providing robust information of the future variability in wind power resources based on probabilistic climate predictions.