Satellite remote sensing helps monitor dust storms. Our study compared five satellite products that use ground-based PM₁₀ data. Most products agreed on the daily dust distribution, with absorbing aerosol index (AAI) performing best under cloud cover. Overall, the Sentinel-5P AAI has the highest probability of correct detection (POCD) in dust events but is unstable and has a high probability of false detection (POFD). The FY4A/B infrared difference dust index (IDDI) has the lowest POCD, but it is relatively stable, and its POFD is low.

The GIM data of 2 years from high solar activity (2014) and low solar activity (2021) provided by CODE (Center for Orbit Determination in Europe) are selected to calculate the total electron content (TEC) difference for each grid point in this paper. Based on the calculation of the spatial and temporal variations in the difference values, both spatial and temporal characteristics of the TEC difference values of the four grid points within the grid are analyzed in detail.

We used the spherical harmonic function (SHF) and the local spherical symmetry (LSS) assumption methods to calculate the hourly and daily LEO satellite GPS differential code bias (DCB). The SHF method is more stable and precise than the LSS assumption. The daily DCB estimation is more accurate and stable than the hourly DCB due to more observation data. Hourly DCBs have large changes in one day, mainly be attributed to random errors because these error time series have a normal distribution.

We investigated the possible widening of the tropical belt along with the probable drivers and impacts based on high-accuracy, high-resolution GNSS RO data (2001–2020). The results show that the tropical belt has significant expansion in the Northern Hemisphere, while the Southern Hemisphere has no significant expansion.