Presentations

Abstract

During 2021, the UK  and Ireland experienced the lowest wind anomalies over the last 40 years, in particular from June to August. In some areas, this lead to a decrease to 20% below average wind speeds from June to August[1] resulting in a significant reduction in power generation. This event caught the attention of the industry[2] and media, raising questions about long-term wind resource trends[3].  When similar situations are identified by developers and asset managers at the specific locations of their farms, questions about the competitiveness and long term viability of the project arise.  Are these isolated worst-case events or are they part of a longer trend? Can we understand the large scale drivers of these episodes? Is this global stilling? Will this become more frequent and/or intense as a result of global warming? If so, what are the implications for the energy yield assessment (EYA)?  Here, we provide a framework to address these questions and we showcase this with a number of example locations in major wind energy development regions around the world. As a first step, our approach involves a detailed analysis of past wind variability. This is done by looking at a long historical record of wind speed using reanalysis (70+ years) and identifying anomalous conditions. We further decompose the wind speed time series and analyse the different time scales of variability (multidecadal, decadal cycles, interannual variability and long-term/climate trend).  What we typically observe is that * multidecadal variability can mask, or compound with a potential climate signal, and, * both, multidecadal and decadal variability have an impact in the magnitude of the ten or twenty year averages typically used for EYAs. * In some cases, recent very anomalous years are not particularly exceptional when considered within the context of multidecadal or decadal variability. In the next step, the results are linked with typical time scales of natural cycles of climate variability, such as atmospheric variability, sea-air and land-sea interactions, or other factors such as changes in land cover. This helps identifying potential drivers of the past and future wind variability and extremes. The described approach provides the understanding for explaining climate trends that are ultimately driven by anthropogenic global warming. This is a crucial aspect for the interpretation of climate projections of  future wind resources. Lastly, we developed an index to distinguish between the interanual variability and long-term trends, including both low-frequency fluctuations and climate change signals. This index serves as a site-specific indicator, revealing the predominant type of variability at a given location providing a way to assess climate risks associated with wind regime alterations driven by climate change. Our studies highlight the importance of monitoring and understanding wind variability on time scales longer than the typically used for EYA, and how this variability may change in the future.  1:https://climate.copernicus.eu/esotc/2021/low-winds  2:Lizcano, A novel tool for climate change risk analysis: using the 2021 UK summer low wind anomalies to build 'storylines' of future wind regimes in the midlatitudes, Wind Europe Technology Workshop 2022.  3:https://www.ft.com/content/d53b5843-dbe0-4724-8adf-75c66127ea80