## 5 Conclusions
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & \multicolumn{2}{c}{**Energy-Limited**} & \multicolumn{2}{c}{**Water-Limited**} \\
**Delay in SM respect to \(ET_{a}\)** & \multicolumn{2}{c}{**(NDJF)**} & \multicolumn{2}{c}{**(MAMJJASO)**} \\ \cline{2-5}  & **R** & **N (days)** & **R** & **N (days)** \\ \hline Same day & \(0.05\) \({}^{\star}\) & 120 & 0.54 & 245 \\
1 day after & \(-0.07\) \({}^{\star}\) & 119 & 0.59 & 244 \\
2 days after & \(-0.08\) \({}^{\star}\) & 118 & 0.61 & 243 \\
3 days after & \(-0.17\) \({}^{\star}\) & 117 & 0.62 & 242 \\
4 days after & \(-0.18\) & 116 & 0.62 & 241 \\
5 days after & \(-0.20\) & 115 & 0.62 & 240 \\ \hline \hline \end{tabular} \({}^{\star}\) Non-significant R values (\(p_{value}\ >\ 0.05\)) are marked with an asterisk.  
\end{table} 
Table 2: Correlation (R) of \(ET_{a}\) from HidroMORE and in situ SM from the REMEDHUS network, and number of observations (N) under energy-limited and water-limited conditions along 2014, considering the delayed SM with respect to the \(ET_{a}\) day (delay = 0, 1, 2, 3, 4 or 5 days). of SM from an individual precipitation event has an important impact on LST in very dry conditions due to its low thermal inertia. Differences in the correlation during winter with the direct variables and during summer with the anomalies could be due to the different spatial scales represented by the remotely sensed and ground-based data. Similar conclusions could be extracted from the normalized occurrence frequency density diagrams displayed per seasons, where the triangular shape is better defined in transitional seasons (autumn and spring) due to the higher dynamic range of SM and LST. Collocated SM and LST time-series display SM-LST coupling periods, approximately corresponding to spring, summer and autumn, and SM-LST decoupling periods, approximately corresponding to winter. These two behaviors can be identified in both in situ and satellite measurements. A method to estimate the critical SM from the crossing points of these SM-LST coupling/decoupling transitions was proposed. A critical SM of \(\sim\)0.12 m\({}^{3}\)/m\({}^{3}\) is estimated using both in situ and spaceborne observations. This value is consistent with field measurements of soil field capacity and wilting point. Since the SM-LST coupling/decoupling periods are related to water/energy-limited regimes, respectively, the temporal evolution of the evapotranspiration is further analyzed for a specific year (2014). The actual evapotranspiration is simulated using the regional hydrological model HidroMORE. The correlation between the daily SM and the modeled actual evapotranspiration \(ET_{a}\) confirm that SM and \(ET_{a}\) only interact under water-limited conditions (with R \(\approx\) 0.6) with a temporal lag between them of 2-3 days. A non-significant correlation between SM and \(ET_{a}\) is observed under energy-limited conditions. This study contributes to furthering present knowledge of SM and LST interactions in land surface, hydrological and climate models. Results presented could be applicable to microwave/optical synergistic SM retrieval algorithms and, particularly, for the improvement of applications based on the SM-LST link, related to evapotranspiration. Further research is needed to study the possible dependency of the different Earth's land covers/climate types in the SM-LST relationship, and also to analyze this relationship using geostationary LST data. Thanks to [PERSON], from the University of Salamanca (USAAL), for providing the daily averaged precipitation data. Thanks to [PERSON], from Consejo Superior de Investigaciones Cientificas (CSIC), for providing insights on the frequency density diagrams analysis. Additionally, the authors want to thank [PERSON] and the Remote Sensing & GIS Group from the Institute for Regional Development of the University of Castilla-La Mancha for the HidroMORE implementation.