## 5 Discussion  
Upon synthesizing all the seven groups for all parameters except WSD, we found a maximum of 39 station pairs of data could be available for analysis for a weather parameter of interest. Specifically, the maximum number of pairs (i.e., 39) was seen for both AT and RH, 22 for SR (as these measurements were available at 2 m height only), 7 for both BP and PR, and 2 for SD. In the case of WSD, we observed that there were 12 station pairs for comparison, while the stations L1 and L2 did not have any measurements. Thus, it is imperative to establish protocols to measure the parameters of BP, PR, SR, and WSD at the missing stations to facilitate better comparisons and understanding across the landscape. Regarding AT and SR, our results indicated that strong relations (including r-values \(\geq\) 0.72 for at least 97% of the station pairs) and very limited acceptable similarities (with PS value \(\geq\) 75% for one station pair) (see Tables 2-4) were witnessed. In fact, SR mainly varies as a function of latitude, such as exhibiting gradual declination towards the higher latitudes, which also cause lower AT in the similar fashion [50,51]. Additionally, the SR regimes also vary with the atmospheric state like clear sky, partially cloud, overcast conditions, etc. [52]. On the contrary, AT regimes also depend on the land cover type as it determines the amount of absorption/reflection of the incident sunlight (SR), a key component defining the eventual temperature at a given location [53]. Thus, it might be possible to observe strong relations for AT and SR at two different latitudes for the same parameter; however, similarities might not exist. This implies that both AT and SR from a nearby station could be used to predict/model other stations' regimes; however, these must be thoroughly evaluated prior to implementation, which was beyond the scope of this study. Regarding RH, it is interesting to mention that both strong relations (i.e., r-values \(\geq\) 0.74 for about 97% of the station pairs) and acceptable similarities (i.e., PS values \(\geq\) 75% for about \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Group**} & \multirow{2}{*}{**Station**} & \multirow{2}{*}{**Network**} & \multicolumn{6}{c}{**Meteorological Parameter**} \\ \cline{3-10}  & & & **AT** & **RH** & **SR** & **BP** & **PR** & **SD** & **WSD** \\ \hline \multirow{3}{*}{G1} & C1 & OSM & & JE323 & & & & & \\ \cline{2-10}  & C4 & WQP & & JE323 & & & & C1 \\ \cline{2-10}  & JE323 & WBEA ES & & & & & & \\ \hline \multirow{3}{*}{G2} & JP316 & WBEA & & & & & & \\ \cline{2-10}  & JP316 & WT & & & & & & \\ \cline{2-10}  & JE316 & WBEA ES & & JP316 & & & & \\ \hline \multirow{3}{*}{G3} & C3 & OSM & & & & & & \\ \cline{2-10}  & C3 & WQP & JP104 & & & & & \\ \cline{2-10}  & JP107 & WBEA & & & & & & \\ \cline{2-10}  & JP311 & WT & & & & & & \\ \cline{2-10}  & JE306 & WBEA ES & & JP104 & & & & \\ \hline \multirow{3}{*}{G4} & C5 & OSM & & & & & & \\ \cline{2-10}  & C5 & WQP & JP213 & & & & & \\ \cline{2-10}  & JP201 & WBEA & & & & & & \\ \cline{2-10}  & JP213 & MT & & & & & & \\ \hline \multirow{3}{*}{G5} & L1 & OSM & & & L2 & & & \\ \cline{2-10}  & L2 & WQP & & & & & & \\ \cline{2-10}  & R2 & WQ & & & & & & \\ \cline{2-10}  & JE306 & WBEA ES & & L2 & & & & \\ \hline \multirow{3}{*}{G6} & C2 & OSM & & & & & & \\ \cline{2-10}  & C4 & WQP & & C2 & & & & C2 \\ \cline{2-10}  & JE323 & WBEA ES & & C2 & & & & \\ \hline \multirow{3}{*}{G7} & JE308 & & & & & & & & \\ \cline{2-10}  & JE312 & WBEA ES & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Group-specific required stations for each of the meteorological parameters. 74% of the station pairs) were observed. These findings refer to the fact that RH would be similar over a small area like this study [22,54]. In addition, regarding BP, about 57% of the station pairs showed strong relations (i.e., r-values \(\geq\) 0.77) and acceptable similarities (i.e., PS values \(\geq\) 75%).