Time resolution of wind speed data introduces errors in wind power density assessment

• Revealed systematic underestimation of wind power density (WPD) with decreasing time resolution. • Analyzed the key mechanism of WPD errors by combining power law exponent and Weibull factors. • Daily data leads to an underestimation of WPD by about 25%. • Proposed a novel regression method to mitigate WPD errors using coarse time resolution data. Wind energy is critical in the global shift towards renewable energy sources, necessitating accurate potential assessments for informed decision-making and strategic development in this transition. Despite the widespread use of wind speed data with varying time resolutions for estimating wind energy, the influence of this variability on the accuracy of wind energy assessment remains uncertain. In this study, we investigate the impact of wind speed data’s time resolution on wind power density (WPD) assessment, utilizing high-frequency, in-situ observations collected from eight anemometer towers in China. Through analysis of wind speed data at nine resolutions, ranging from 10-minute to monthly intervals, we uncover significant errors introduced by coarser time resolutions in WPD calculations. Specifically, it reveals a systematic underestimation of WPD with decreasing time resolution, highlighting the importance of time resolution in wind energy evaluation. While hourly wind speed data yield acceptable WPD errors, daily and monthly resolutions lead to substantial underestimation due to the smoothing effect of fluctuations. We have also delved into the underlying mechanisms contributing to these errors, including variations in the power law exponent and changes in the Weibull distribution shape factor with time resolution. Furthermore, we propose a novel method to mitigate WPD calculation errors using coarse time resolution data by regressing Weibull distribution factors. The findings offer valuable insights into wind speed data selection and accurate wind energy assessment, with implications for renewable energy planning and policy-making in the context of the global energy transition.