Wind Speed and Direction Estimation in Japan Based on Pressure-Gradient Interpolation and Geostrophic Wind Approximation

Accurately estimating wind speed and direction is essential for assessing wind energy potential, as precise estimates enable better identification of optimal generation periods and improved resource planning. While NWP models like ERA5 and JMA MSM provide valuable insights, they often entail substantial computational complexity and time dependence, limiting their practical applicability for local-scale assessments. This study proposes an efficient framework that combines IDW interpolation, logarithmic wind-profile theory, and Ekman spiral dynamics to estimate wind speed and direction from nearby weather stations. Unlike complex NWP models, our approach requires fewer computational resources, making it suitable for distributed, station-based applications. We evaluate the proposed method using five years of JMA AMeDAS data from 806 stations and compare performance against ERA5 and JMA MSM using multiple statistical metrics. Results show that the method achieves lower average and median RMSE, MAE, and MedAE, validating it as a viable alternative to conventional NWP models to estimate wind speed and direction at 10 m height. By combining simpler methods, this method offers an alternative tool to find wind speed and direction in unknown locations without the overhead of complex numerical models.