March monthly accumulated precipitation in the central and western regions of the Iberian Peninsula presents a clear continuous decline of 50% during the 1960-97 period. A finer analysis using daily data reveals that this trend is exactly confined to the month of March. However, this is merely the most visible aspect of a larger phenomenon over the North Atlantic/European sector. The European precipitation trends in March for the period 1960-2000 show a clear distribution of increasing precipitation in the northern regions (the British Isles and parts of Scandinavia) together with decreasing trends throughout the western Mediterranean Basin.Relevant circulation changes over the North Atlantic and European sectors explain these precipitation trends. First, a regional Eulerian approach by means of a weather-type (WT) classification shows that the major rainfall contributors in March display significantly decreasing frequencies for the Iberian Peninsula, in contrast to the corresponding "wet" weather types for the U.K./Ireland sector, which display increasing frequencies. Within a larger context, a Lagrangian approach, based on the analysis of storm tracks over Europe and the North Atlantic region, reveals dramatic changes in the location of cyclones in the last four decades that coincide with the corresponding precipitation trends in Europe. The North Atlantic Oscillation is suggested to be the most important large-scale factor controlling both the circulation changes and the precipitation trends over the Euro-Atlantic area in March. Finally, the potential impact of reduced precipitation for rivers and water resources in the Iberian Peninsula is considered.
An analysis of the frequency of cyclones and surface wind velocity for the Euro-Atlantic sector is performed by means of an objective methodology. Monthly and seasonal trends of cyclones and wind speed magnitude are computed and trends between 1960 and 2000 evaluated. Results reveal a significant frequency decrease (increase) in the western Mediterranean (Greenland and Scandinavia), particularly in December, February, and March. Seasonal and monthly analysis of wind magnitude trends shows similar spatial patterns. We show that these changes in the frequency of low-pressure centers and the associated wind patterns are partially responsible for trends in the significant height of waves. Throughout the extended winter months (October-March), regions with positive (negative) wind magnitude trends, of up to 5 cm/s/year, often correspond to regions of positive (negative) significant wave height trends. The cyclone and wind speed trends computed for January-March are well matched by the corresponding trends in significant wave height, with February being the month with the highest trends (negative south of lat 50 degrees N up to -3 cm/year, and positive up to 5 cm/year just north of Scotland). Trends in European precipitation are assessed using the Climatic Research Unit data set. The results of the assessment emphasize the link with the corresponding tendencies of cyclone frequencies. Finally, it is shown that these changes are associated, to a large extent, with the preferred phases of major large-scale atmospheric circulation modes, particularly with the North Atlantic Oscillation, the eastern Atlantic pattern, and the Scandinavian pattern.
Wake losses are perceived as one of the largest uncertainties in energy production estimates (EPEs) for new offshore wind projects. In recent years, significant effort has been invested to improve the accuracy of wake models. However, it is still common for a standard wake loss uncertainty of 50% to be assumed in EPEs for new offshore wind farms. This paper presents a body of evidence to support reducing that assumed uncertainty. It benchmarks the performance of four commonly used wake models against production data from five offshore wind farms. Three levels of evidence are presented to substantiate the performance of the models:• Case studies, i.e. efficiencies of specific turbines under specific wind conditions; • Array efficiencies for the wind farm as a whole for relatively large bins of wind speed and direction; and • Validation wake loss, which corresponds to the overall wake loss within the proportion of the annual energy production where validation is possible.The most important result for predicting annual energy production is the validation wake loss. The other levels of evidence demonstrate that this result is not unduly reliant on cancellation of errors between wind speed and/or wind direction bins.All of the root-mean-squared errors in validation wake loss are substantially lower than the 50% uncertainty commonly assumed in EPEs; indeed, even the maximum errors are below 25%. It is therefore concluded that there is a good body of evidence to support reducing this assumed uncertainty substantially, to a proposed level of 25%.
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