## 4 Results and Discussion
### PlanetQi-NWP Models Comparison
#### 4.3.2 PlanetIQ-ECMWF Model Comparison
Regarding temperature difference percentage, the ECMWF exhibits a slight escalation around the equator and poles. The maximum difference reaches \(\pm 2.5\%\) in specific regions highlighted on the map, which is a slightly higher value than the GFS temperature difference. The WVP difference is normally less than \(\pm 0.5\%\), except for specific distributed areas where it may reach up to \(\pm 3\%\), particularly around the equator. This pattern is consistent with the GFS results. The refractivity difference typically ranges between \(\pm 4\%\), with higher concentrations near the equator and decreasing toward the poles. This aligns with the distribution observed in the GFS results. In his research findings, [PERSON]. [34] also found no indications of instrument degradation, temporal inhomogeneities in the RO records, or temporal trends in sampling patterns. After correcting for sampling errors using ECMWF analysis fields, refractivity deviations were reduced to less than 0.05% in almost any month, and dry temperature deviations were reduced to less than 0.05 K (<0.02% relative) for almost every satellite and month. These findings highlight the robustness and reliability of RO climatologists from different satellites, underscoring their value for climate monitoring in the upper troposphere and lower stratosphere. Figure 20 shows the boxplot for the RMSE across atmospheric variables to show the differences between the PlanetQ profiles and the GFS and ECMWF profiles. The RMSE values for differences between PlanetIQ observations and ECMWF/GFS models across meteorological parameters reveal notable distinctions. The median air pressure estimates for the ECMWF and GFS are around 1.67 mb and 1.82 mb, respectively. GFS has a slightly higher mean RMSE of 3.47 mb compared to ECMWF's 3.28 mb, indicating a larger overall discrepancy. The ECMWF has a moderate IQR of 0.14, while the GFS has a little lower IQR of 0.10 mb, with similar whisker min and max values. The ECMWF and GFS have different median values for refractivity, with 0.53 and 0.61, respectively. The GFS has a slightly higher mean RMSE, 1.20, than the ECMWF's 1.11. The IQR for refractivity in GFS is notably smaller at 0.05, reflecting a more concentrated spread, whereas the ECMWF's IQR is 0.14. The whisker min and max values for both models fall within their respective IQRs. For temperature, the ECMWF and GFS have median values of 1.05 and 1.29, respectively, with mean RMSE values of 1.21 \({}^{\circ}\)C and 1.49 \({}^{\circ}\)C. The ECMWF temperature data has a larger IQR of 0.60 compared to the GFS's 0.69 \({}^{\circ}\)C. The whisker min and max values for both models extend beyond their respective IQRs, indicating the presence of outliers. In the case of WVP, the ECMWF and GFS have median values of 0.19 mb and 0.05 mb, respectively. The GFS has a lower mean RMSE (0.18 mb) than the ECMWF (0.25 mb). The IQR for WVP in ECMWF is 0.30 mb, reflecting a broader spread, while the GFS IQR is 0.26 mb. Whisker min and max values in WVP exhibit differences in distribution for both models. Figure 19: Diff.% contour maps for all variables at altitude 3 km between PlanetQ and ECMWF. In summary, the varying levels of agreement between PlanetIQ observations and ECMWF/GFS models across meteorological parameters are evident from the differences in mean RMSE, IQR, and whisker values. In agreement with our research findings, Ref. [40] evaluated the ROM SAF gridded monthly mean climate data record, demonstrating good agreement with the ERA-Interim reanalysis and highlighting the internal consistency among RO satellite missions. Their assessment revealed that in the 8-30 km altitude region, the observational data record exhibits a high degree of internal consistency, with global mean bending angle, refractivity, and global mean dry temperature showing consistency levels better than 0.04%, 0.05%, and 0.15 K, respectively.