# Synergistic Potential of Optical and Radar Remote Sensing for Snow Cover Monitoring
## 4 Results
### Potential of the Combined Use of SAR and MODIS for Snow Monitoring  
An analysis of the contribution of SAR and MODIS to the total SCA and the PWSAI (defined as the probability of having a day with additional wet snow under cloud cover) was carried out in the Pyrenees (the only mountainous system of the Iberian Peninsula represented in the HRS&I SWS product) to evaluate the potential of SAR for the completion of optical SCA. The PWSAI consistently remains close to 100% throughout each month of the snow season (Figure 8a), indicating that nearly every day, the HRS&I product (wet snow) provides additional SCA information as regards MODIS. Only in November and December does the PWSAI slightly drop below 100%, highlighting SAR's potential to fill spatial gaps in SCA derived from optical sensors, specifically MODIS. Examining the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Month/Range** & **Sierra Nevada** & **Central System** & **Iberian Range** & **Cantabrian System** & **Pyrenees** \\ \hline November & \(-1.6\) & \(-1.17\) & \(-1.17\) & \(-1.12\)\({}^{1}\) & \(-1.13\) \\ December & \(-2.71\) & \(-4.45\) & \(-2.98\) & \(-4.39\) & \(-2.65\) \\ January & \(-3.41\) & \(-2.54\) & \(-3.15\) & \(-6.26\) & \(-1.08\) \\ February & \(-1.9\) & \(-1.42\) & \(-0.51\) & \(+0.17\) & \(-0.99\) \\ March & \(-2.82\) & \(-2.06\) & \(-2.45\) & \(-1.76\) & \(+0.88\) \\ April & \(-0.6\) & \(+0.32\) & \(+0.04\) & \(+0.2\) & \(-0.99\) \\ May & \(-1.08\) & \(-0.18\) & \(-0.1\) & \(-0.33\) & \(-0.75\) \\ \hline \hline \end{tabular} \({}^{\dagger}\) Magnitude of the trend estimates with Sen’s slope estimator (non-parametric method).  
\end{table} 
Table 1: Magnitude of the trend (%/lustrum) of the temporal changes in the Probability of Snow Cover Presence Index (PSCPI) of each month over the entire domain of the main-snow dominated mountain ranges of the Iberian Peninsula. Figure 7: Five-year period temporal evolution of SCA in terms of the average PSCPI for the entire domain of the mountain ranges of the Iberian Peninsula on a monthly basis. contribution of SCA relative to the total SCA, MODIS predominates during late autumn and winter (approximately 85% to 90%); however, the contribution from wet snow (HRS&I SWS) is notably significant (ranging from 10% to 15%) (Figure 8a). As the snowmelt season progresses, MODIS's contribution to the total SCA decreases considerably, while the contribution from HRS&I SWS (wet snow) begins to gain relevance, increasing significantly the supplied additional SCA information (27-40%). It is important to note that the HRS&I SWS contribution suddenly decreases in May (Figure 8a). This is due to the fact that, in the Pyrenees, the snowmelt phase mainly occurs during April, so that, in May, snow is predominantly restricted to higher elevations (above 2500 m.a.s.l.). At these elevations, temperatures frequently remain below 0 \({}^{\circ}\)C, which leads to a reduced contribution of wet snow relative to the total SCA. Figure 9 illustrates examples of SAR and MODIS data integration for SCA monitoring in the Pyrenees. The top panel shows an image from mid-winter, whereas the bottom panel shows an image from early spring. Figure 8: (**a**) Monthly PWSAI distribution and contribution of MODIS and HRS&I SWS (wet snow) products in relation to the total SCA over an average year in the Pyrenees. (**b**) Monthly variation of the contribution of HRS&I SWS product to the total SCA over an average year in the Pyrenees. The red line indicates the median, and the edges of the box (blue color) represent the first quartile (bottom edge) and third quartile (top edge). The upper adjacent is the furthest observation within one and a half times the interquartile range of the lower end of the box, and the upper adjacent is the furthest observation within one and a half times the interquartile range of the upper end of the box. Outliers are considered as the values greater than the upper adjacent.