CloudnetPy: A Python package for processing cloud remote sensing data
Simo Tukiainen, Ewan O’Connor, Anniina Korpinen
Abstract
Active ground-based remote sensing instruments such as cloud radars and lidars provide vertical profiles of clouds and aerosols with high vertical and temporal resolution. Cloud radars typically operate in the sub-millimeter wavelength region, around 35 or 94 GHz, and are sensitive to clouds, particularly ice clouds, rain and insects. Lidars operating at visible and nearinfrared wavelengths on the other hand, are more sensitive to liquid clouds and aerosols. Combining these two complementary data sources with temperature and humidity profiles from a numerical weather prediction model or radiosonde makes it possible to accurately classify the various scattering hydrometeors in the atmosphere, diagnosing them as: rain drops, ice particles, melting ice particles, liquid droplets, supercooled liquid droplets, drizzle drops, insects and aerosol particles. Furthermore, adding a passive microwave radiometer, an instrument measuring liquid water path, attenuation corrections and quantitative retrievals of geophysical products such as ice water content, liquid water content and drizzle properties become feasible