## 3 Results and Discussions
### Ground-Based Validation  
For a range of atmospheric conditions, the two investigated single-channel LST models match the accuracy of the GSW model (Figure 3). A summary of the bias and the RMSD associated with the different LST models is provided in Tables 3 and 4.  
For dry to medium-moist atmospheres (TCWV up to 45 mm), RMSDs of the PMW and the SMW model ranged between 1.8 K and 2.6 K (Table 3). This is close to the 2 K target accuracy of the GSW-based LSA SAF dataset. For the Evora and RMZ sites, the PMW model matched the accuracy of the GSW with RMSDs of 1.9 K (PMW) and 1.9-2.0 K (GSW) and had an absolute bias \(<\) 1 K. For the sites Gobabeb and Dahra, the PMW (RMSD 1.8 K and 2.6 K) was slightly less accurate than the GSW (RMSD 1.5 K and 2.3 K), while the SMW's RMSD was up to 0.5 K larger (TCWV up to 45 mm; Table 3). [PERSON] _et al._[21] have recently compared PMW and GSW LSTs from the Landsat satellite against 41 ground observations from the Surface Radiation (SUFRAD) Budget Network in moderate climate zones. They have reported the highest accuracy for the PMW with a difference in RMSD of only 0.1 K compared to the GSW: Our analysis does not confirm this finding. We show that PMW agrees with GSW to within 0.1-0.5 K for most atmospheric conditions tested here.  
In Gobabeb, RMZ and Dahra, the PMW and SMW performed very similarly (\(\Delta\)RMSD 0.2 K) for TCWV \(<\) 45 mm. In Evora, the PMW had a 0.6 K lower RMSD and 0.7 K lower bias compared to the SMW. At very high TCWVs (\(>\)45 mm), we observe a 1 K higher RMSD for the PMW compared to the SMW at Dahra. Hence, the computationally-expensive PMW model outperforms the SMW only at one out of four investigated stations.  
Observed RMSD matches the theoretical uncertainties (Section 3.1) to within 0.3-1 K for dry to medium-moist atmospheres (Tables 2 and 3). Slightly larger RMSDs can reflect uncertainty and scaling differences of the ground measurements not included in the theoretical uncertainty analysis.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & \multicolumn{2}{c}{**PMW**} & \multicolumn{2}{c}{**SMW**} \\ \hline  & **RMSD (K)** & **BIAS (K)** & **RMSD (K)** & **BIAS (K)** \\ \cline{2-5} TCWV \(\leq\) 45 mm & 1.6 & \(-\)0.2 & 1.6 & \(-\)0.1 \\ TCWV \(>\) 45 mm & 3.3 & \(-\)1.1 & 3.4 & \(-\)0.6 \\ \hline \end{tabular}
\end{table}
Table 2: Theoretical uncertainty for MSG/SEVIRI LST estimates for the PMW and SMW. RMSD and bias associated with both model and input uncertainty.  
For very moist atmospheres, which are only encountered at the Dahra station, we observed a distinctly higher RMSD (\(\Delta\)2.9 K-\(\Delta\)1.9 K) and bias (\(\Delta\)2.1-\(\Delta\)0.8 K) for the two single-channel models compared to the GSW (Table 4) and a higher RMSD (\(>\)3 K) compared to the theoretical error analysis (Figure 2). In addition, we observed different model performances for selected TCWV classes and sites (Figure 3). We investigated those differences and provide possible explanations in the following sections.  
Figure 3: Comparison of LST between _in situ_ measurements from the KIT sites and Meteosat-based retrievals for different TCWV classes. The boxplots show the median, the first and third quartile with whiskers at the 95 th and fifth percentiles. GSW: the Satellite Application Facility on Land Surface Analysis’s (LSA SAF) operational GSW. **(a)** KIT Gobabeb station; **(b)** KIT Evora station; **(c)** KIT Dahra station; **(d)** KIT RMZ station.