Surveillance cameras have emerged as a new low-cost, high-resolution Near Surface Precipitation Type observer. A novel deep learning approach is developed to classify rain, snow, and graupel, achieving 93 % accuracy in real-world observations. The model remains robust to camera parameter variations and maintains reliable performance at wind speeds below 5 m s⁻¹, demonstrating strong potential for large-scale practical applications.