Estimation of nighttime aerosol optical depths using the ground-based microwave radiometer

Abstract

Aerosol optical depth (AOD) is a crucial parameter for understanding the impact of aerosols on Earth's atmosphere and air quality. Nevertheless, most existing remote sensing techniques rely on the shortwave spectrum, precluding nighttime measurements. While lunar and stellar photometry can measure nighttime AOD, their data availability is limited due to the scarce moonlight for lunar photometry and the rarity of application for stellar photometry. In this study, we made a first attempt to retrieve AOD from ground-based microwave radiometer (MWR) measurements in Beijing Nanjiao Meteorological Observatory in China. Brightness temperatures (BTs) at the K-band (from 22.23 to 30.00 GHz) and V-band (from 51.25 to 58.80 GHz) are trained against daytime spectral AOD from sun photometer measurements together with the temperature profile using the random forest regression (RFR) retrieval model, and the model is then used to retrieve nighttime AOD. The algorithm demonstrates satisfactory performance, with reasonable agreement with lunar AOD retrievals from the lunar photometer (RCombining double low line0.91 and RMSE Combining double low line0.14). The results also reveal a distinct day-night cycle of AOD, with nighttime AOD typically higher than its daytime value for the Beijing-CAMS Aerosol Robotic Network (AERONET) site and AOD estimated based on MWR measurements. The physical basis of our approach is verified using vertical temperature and humidity profiles from sounding observation and simulation results from WRF-Chem as well as the monochromatic radiative transfer model (MonoRTM). Our study provides an effective and convenient approach to estimate nighttime aerosol loading from surface, which has great potential in environmental monitoring and climate forcing research.