Abstract

Computational fluid dynamics and particle tracing simulations are presented for a cloud droplet sensor. Airspeeds and streamlines around the sensor are calculated at several wind speeds and their effect on the droplet sampling are examined. Particle tracing is used to study the effect of different wind speeds and droplet sizes on the sampling of the cloud droplets. Simulated droplet concentrations are confirmed by comparing them with measured wind tunnel data. Results demonstrate clear sampling effects that are functions of both wind speed and droplet size. Optimal compromise between maximal measurement volume and sampling effects is found and a simple approximation for sensor’s sampling bias is presented. The results show that CFD simulations can give valuable information about the sampling of droplets in an ideal environment with known droplet concentrations. Even in a wind tunnel, the true test conditions are often impossible to accurately determine. Thus by simulating the sampling effects in different conditions, the sensor can be calibrated for a wide range of naturally occurring cloud conditions.