Data assimilation of CALIPSO aerosol observations

Abstract

Abstract.We have developed an advanced data assimilation system for a global aerosol model with a four-dimensional ensemble Kalman filter in which the Level 1B data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were successfully assimilated for the first time, to the best of the authors' knowledge. A onemonth data assimilation cycle experiment for dust, sulfate, and sea-salt aerosols was performed in May 2007. The results were validated via two independent observations: 1) the ground-based lidar network in East Asia, managed by the National Institute for Environmental Studies of Japan, and 2) weather reports of aeolian dust events in Japan. Detailed four-dimensional structures of aerosol outflows from source regions over oceans and continents for various particle types and sizes were well reproduced. The intensity of dust emission at each grid point was also corrected by this data assimilation system. These results are valuable for the comprehensive analysis of aerosol behavior as well as aerosol forecasting.

An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band

“…In particular, studies have shown notable improvements in aerosol forecasting through the assimilation of satellite aerosol products, mostly from daytime observations (e.g., Zhang et al, 2008aZhang et al, , 2011Zhang et al, , 2014Yumimoto et al, 2008;Uno et al, 2008;Benedetti et al, 2009;Schutgens et al, 2010;Sekiyama et al, 2010). To capture the diurnal cycle, the aerosol modeling community requires nighttime satellite aerosol data hav-ing broad spatial coverage and high temporal resolution to further advance aerosol, visibility, and air quality forecasts (e.g., Zhang et al, 2011Zhang et al, , 2014.…”

Preliminary investigations toward nighttime aerosol optical depth retrievals from the VIIRS Day/Night Band

“…Recent advances in aerosol climate studies (e.g., Kaufman et al, 2002;Zhang et al, 2005a, b) and aerosol and visibility forecasting (e.g., Zhang et al, 2008aZhang et al, , 2011Benedetti et al, 2009;Sekiyama et al, 2010) have responded to the growing demand for nighttime aerosol retrievals from satellite observations. For example, by using multisensor aerosol products from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging Spectroradiometer (MISR), and the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP), Zhang et al (2011) show improvements in aerosol forecasts using combined 2-D/3-D VAR aerosol assimilation.…”

Integrated Study of AD-Net Mie-Lidar Network and Data Assimilated CTM for Asian Dust Epidemiology in Japan

“…Then the accuracy of calculated concentration of dust is the key factor. Recently data assimilation technique is combined with CTM, and lidar data can be included in this system [3,4]. Thus, dust extinction estimated by the lidar network will raise the reliability of concentration predicted by CTM, and such results are the most suitable for epidemiology.…”