The Added Value of Seasonal Climate Forecasts for Integrated Risk Management Dec...
The central objective of SECLI-FIRM is to demonstrate how the use of improved climate forecasts, out to several months ahead, can add practical and economic value to decision-making processes and outcomes, primarily in the energy...
The central objective of SECLI-FIRM is to demonstrate how the use of improved climate forecasts, out to several months ahead, can add practical and economic value to decision-making processes and outcomes, primarily in the energy sector, but also in the water sector. Specifically for the energy sector, SECLI-CLIM will assess the impact on operational planning and portfolio management, such as hedging and asset optimization, thus enabling quantification of the value-add provided by seasonal forecasts which have been calibrated, evaluated and tailored for each specific application. Improvements in management decisions will ultimately lead to an improved supply-demand balance and therefore to a more efficient energy system, particularly with respect to renewable energy, with corresponding benefits for climate change mitigation.
A simple, but effective, methodology will be used to assess value added. A control case will only utilise climatological conditions based on historical averaged values – currently the most common approach – while a test case will also consider individually optimised and tailored state-of-the-art probabilistic seasonal forecasts. This will be done for nine case studies for Europe and South America: recent seasons with anomalous/extreme climate conditions leading to problematic and quantifiable impacts for the energy and/or water industry. Crucially for success, the case studies will be co-designed by industrial and research partners.
These case studies will provide the basis for developing pilot climate services for a number of specific applications, allowing evaluation of the added value of near real-time information for decision making. Thus SECLI-FIRM will promote research advances in the optimization of seasonal forecasts for specific applications (e.g. by evaluating both local processes and large-scale teleconnections), as well as promoting the uptake of seasonal forecasts by industry and hence expansion of the climate services market.ver más
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