## 3D Multi-layer Heatmap of Electron Density  
The COSMIC-1 (Constellation Observing System for Meteorology, Ionosphere, and Climate-1)/FORMOSAT-3 satellite constellation, launched in 2006, pioneered global atmospheric profiling using GNSS radio occultation. Comprising six polar-orbiting satellites (800 km altitude), it delivered over 2500 daily vertical profiles of atmospheric parameters and ionospheric electron density, establishing foundational datasets for numerical weather  
Figure 2: Three-dimensional multilayer heatmap of electron density. The figure shows the layered distribution of the global electron density by altitude at 12:00 UTC on March 21, 2011. Electron density is expressed in natural logarithmic scale (\(\ln(\mathrm{m}^{-3})\)) to accommodate its wide dynamic range. The plot reveals altitude-dependent features of the ionosphere, including dense equatorial ionization near 300 km (F-layer) and weaker ionization at higher and lower altitudes. prediction and space weather studies [25]. In this study, the source of electron density used for training is reconstructed from COSMIC-1 observations. COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere, and Climate-2) is a second-generation satellite constellation for meteorological, ionospheric, and climate observation, launched in 2019. With the primary objective of acquiring high-precision, high-vertical-resolution atmospheric and ionospheric profile data through GNSS radio occultation techniques, it aims to enhance weather forecasting, space weather monitoring, and climate studies. The constellation comprises six low-inclination orbit satellites, delivering dense observational coverage from tropical to mid-latitude regions (\(\pm 45^{\circ}\)), and providing approximately 5000 daily vertical radio occultation profiles of atmospheric parameters and electron density [26]. This study employs its 2019 electron density (Ne) observations as a benchmark observational dataset to validate the output accuracy of the decomposition model. The 2019 COSMIC-2 data used in this study were obtained from official sources as raw.tar.gz archive files, whose filenames incorporate the day of the year (DOY). The DOY range for 2019 data spans 274-365. After decompression, each archive yields multiple NetCDF-format files, each containing spatiotemporal metadata (e.g., timestamp, satellite ID) encoded in filenames. Hourly parameters were extracted from filenames, while altitude, latitude, longitude, and electron density (Ne) were retrieved from file contents. Data cleaning followed three criteria:  
* Missing Value Removal: Rows containing placeholder values (\(-\)999) were discarded. * Physical Validity Filtering: Observations with Ne < 0 (non-physical values) were excluded. * Altitude Thresholding: Data below 60 km were truncated to align with the training data range. After applying these cleaning criteria to the 2019 COSMIC-2 electron density observations (from DOY 274-365), a total of 38,609,157 valid data points were retained for subsequent modeling. The cleaned satellite altitude distribution is illustrated in Figure 3.  
1. IRI-2020  
The International Reference Ionosphere (IRI) is an empirical standard model constructed from extensive global ionospheric observational data. By integrating ground-based and satellite observations, it systematically characterizes the global distribution of key ionospheric parameters, including but not limited to electron density (Ne) vertical profiles, ion composition ratios, electron/ion temperatures, and ionospheric drift velocities [27]. This study utilizes electron density (Ne) outputs from IRI-2020 (current latest version) as a comparative reference to evaluate the modeling performance of the data-driven approach through systematic comparisons with predictions from the deep learning model. The IRI-2020 model has improved empirical algorithms and integrated next-generation observational datasets compared to its predecessors, significantly enhancing its capability to characterize ionospheric spatiotemporal variations.