Prediction of turbulence in the air has an important role in the world of aviation. Turbulence occurs when changes in wind movements are very fast and random. The turbulence classification is divided into weak turbulence, moderate turbulence, and high turbulence. The effect of high turbulence is that the aircraft is difficult to control. The amount of turbulence can be expressed by Richardson Numbers (Ri). The value of Richardson numbers is influenced by altitude, wind speed, air temperature, and air pressure parameters. High turbulence is indicated by the value of Richardson numbers which are less than 0.25. Analysis of turbulence parameters is carried out to obtain optimal wind speed sensor placement. Optimization of turbulence parameters using the Particle Swarm Optimization method. The data used for optimization is the Juanda Surabaya Climatology Station data from May 2018 to April 2019. This optimization resulted in the placement of an optimal wind speed sensor at an altitude of 32 meters with a wind speed value of 6.4 knots, a pressure value of 100916 Pascal, and a temperature value of 30.2 Celsius.