Fit of wind speed and temperature profiles in the low atmosphere from rass sodar data

Abstract

Analysis of wind speed and temperature is important to describe momentum and heat exchanges and for wind energy applications. A near 20-month database from a Radio Acoustic Sounding System (RASS) sodar located on a plateau in Northern Spain was used. Autocorrelation functions calculated for wind speed and temperature at 40 and 200 m revealed that only the daily cycle is relevant for wind speed, whereas both yearly and daily cycles are for temperature. Cross correlations, calculated between 40 and 400 m (in 20 m steps), have shown a thermal lag of about 30 min at certain levels. Three filters (weighted moving average, moving median, and statistically based) were used with a time interval of about 2 h to eliminate noise, resulting in similar behaviour for filtered data. Wind speed and temperature profiles were fitted to simple two parameter expressions (linear, logarithmic, and power-law). Although the highest number of fits at the 1% significance level is for linear profiles, comparison of profiles showed that power-law profiles have the highest correlation coefficients for wind speed and linear profiles for temperature. The number of satisfactory fits increased when a filter was used. Hourly evolution of profiles was also studied and linear profiles were satisfactory for wind speed during the day. Autocorrelations of the two parameters used in the three fitting profiles were calculated and also modelled with a harmonic equation. No cyclic pattern was observed for wind speed profile parameters, although it was for temperature profile parameters. Finally, a weighted moving average filter and a robust calculation with 13 close in time profiles made the cycles of both parameters more noticeable.