The temporal convolutional network (TCN) approach in deep learning is used to predict the daily value of F10.7. The prediction results for 1–3 d ahead during solar cycle 24 have a high correlation coefficient (R) of 0.98 and a root mean square error (RMSE) of only 5.04–5.18 sfu.

We establish a new rain cell precipitation parameter and visible infrared and microwave signal dataset combining with the multi-instrument observation data on the Tropical Rainfall Measuring Mission (TRMM). The purpose of this dataset is to promote the three-dimensional study of rain cell precipitation system, and reveal the spatial and temporal variations of the scale morphology and intensity of the system.

The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.

Secular variations in CO₂ concentration and geomagnetic field can affect the dynamics of the upper atmosphere. We examine how these two factors influence the dynamics of the upper atmosphere during the Holocene, using two sets of ~ 12 000-year control runs by the coupled thermosphere–ionosphere model. The main results show that (a) increased CO₂ enhances the thermospheric circulation, but non-linearly; and (b) geomagnetic variation induced a significant hemispheric asymmetrical effect.

On timescales longer than the solar cycle, secular changes in CO₂ concentration and geomagnetic field play a key role in influencing the thermosphere. We performed four sets of ~12000-year control runs with the coupled thermosphere–ionosphere model to examine the effects of the geomagnetic field, CO₂, and solar activity on thermospheric density and temperature, deepening our understanding of long-term changes in the thermosphere and making projections for future thermospheric changes.

Ground-based observations of aerosols and aerosol data verification is important for satellite and climate model modification. Here we present an evaluation of aerosol microphysical, optical and radiative properties measured using a multiwavelength photometer with a highly integrated design and smart control performance. The validation of this product is discussed in detail using AERONET as a reference. This work contributes to reducing AOD uncertainties in China and combating climate change.

Global precipitable water vapor (PWV) derived from MERSI-II (Medium Resolution Spectral Imager) is compared with PWV from the Integrated Global Radiosonde Archive (IGRA). Our results show a good agreement between PWV from MERSI-II and IGRA and that MERSI-II PWV is slightly underestimated on the whole, especially in summer. The bias between MERSI-II and IGRA grows with a larger spatial distance between the footprint of the satellite and the IGRA station, as well as increasing PWV.

The result shows dust aerosols from the Taklimakan Desert have higher aerosol scattering during dust storm cases of this paper, and this caused higher negative direct radiative forcing efficiency (DRFEdust) than aerosols from the Sahara. The microphysical properties and particle shapes of dust aerosol significantly influence DRFEdust. The satellite-based equi-albedo method has a unique advantage in DRFEdust estimation: it could validate the results derived from the numerical model directly.