Improved Fog and Marine Layer Prediction via Microwave Remote Sensing

Current fog forecast skill is limited by sparse observational data. We present continuous atmospheric boundary layer measurements by microwave profiling radiometers and describe initial efforts using these data to improve fog forecasting. We find that radiometer temperature, humidity, and liquid profiles and derived parameters at San Francisco and other locations are clearly linked to fog and marine layer formation and dissipation processes. We present fog and marine layer prediction results using algorithms derived from statistical radiometer data analysis.