This article reviews the development of a global non-hydrostatic model, focusing on the
pioneering research of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM). Very …

Abstract Himawari‐8, a next‐generation geostationary meteorological satellite, was
launched on 7 October 2014 and became operational on 7 July 2015. The advanced imager …

In an attempt to improve the forecasting of atmospheric aerosols, the ensemble square root
filter algorithm was extended to simultaneously optimize the chemical initial conditions (ICs) …

An ensemble Kalman filter data assimilation (DA) system has been developed to improve air
quality forecasts using surface measurements of PM 10, PM 2.5, SO 2, NO 2, O 3, and CO …

A data assimilation capability has been built for the NMMB-MONARCH chemical weather
prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble …

In our previous study (Li et al., 2019a), using observational data, we found some evidences
of Taklimakan dust effects on the convective clouds over the Tibetan Plateau (TP) and then …

Atmospheric chemistry transport models have been extensively applied in aerosol forecasts
over recent decades, whereas they are facing challenges from uncertainties in emission …

The next‐generation geostationary satellite Himawari‐8 has a much higher observation
frequency of the aerosol field than polar‐orbiting satellites. Aerosol analyses with a …

We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol
forecast. In the retrieval algorithm, the short-term forecast from an aerosol data assimilation …

A data assimilation system for aerosol, based on an ensemble Kalman filter, has been
developed for the ECHAM–Hamburg Aerosol Model (ECHAM-HAM) global aerosol model …