<p>This work performs exploratory analysis on 120 m and 100 m mast measured wind resource data which are obtained with temporal resolutions of 10-min and 5-min at two separate locations in the southern and western regions in India. The objective of this work is to understand the underlying processes of wind speed time series measured at professionally operated weather monitoring stations using the background of stochastic modeling and time series analysis techniques. At the outset, summary statistics of the data are obtained. Then, the correlation structures underlying the time series are discovered at 10-min and 5-min resolutions. Thereafter, Autoregressive Integrated Moving Average (ARIMA) models are fitted to the time series data. Subsequently, hourly average values of the measured wind speed are computed to evaluate the stochastic nature of the data. This is obtained by fitting ten number of marginal and four number of mixture distributions. In the next step, the turbulence characteristics is investigated by computing the turbulence index at 10-min and 5-min resolutions. In the final step, the expected energy capture and yearly emission reduction values are evaluated. The broad significance of the work is to enrich existing literature on wind resource assessment by focusing on the regional variation of wind resource.</p>