## 3 Results
### Evaluation of Single Sensor
#### 3.3.2 Repeat Interval Analysis  
The results of the repeat interval analysis are presented in Table 6. The repeat interval represents an averaged viewing of sensors across space and time as computed from a simulation of an entire year and averaged across the northern hemisphere by each individual snow class. The repeat interval reflects how frequently an observation could be obtained  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Snow Class**} \\ \hline  & **Sensor ID** & **Tundra** & **Taiga** & **Maritime** & **Ephemeral** & **Prairie** & **Alpine** \\ \hline \multirow{5}{*}{1-day} & PMW & **98.8** & 0.00 & 0.00 & 67.1 & 77.0 & 0.00 \\  & Ku-band SAR & 55.2 & 0.00 & 34.5 & 22.1 & 25.2 & 33.5 \\  & C-band SAR & 29.3 & 0.00 & 17.5 & 10.2 & 12.5 & 17.9 \\  & Wide LiDAR & 1.88 & 1.83 & 0.795 & 0.802 & 0.768 & 1.61 \\  & Narrow LiDAR & 0.686 & 0.374 & 0.316 & 0.344 & 0.346 & 0.447 \\  & Low-inclination & 0.0901 & 0.105 & 0.211 & 0.522 & 0.158 & 0.163 \\ \hline \multirow{5}{*}{3-day} & PMW & **100** & 0.00 & 0.00 & **93.7** & **95.8** & 0.00 \\  & Ku-band SAR & **93.8** & 0.00 & **80.5** & 58.5 & 63.7 & 75.8 \\  & C-band SAR & 68.6 & 0.00 & 47.4 & 30.6 & 35.7 & 46.1 \\  & Wide LiDAR & 5.20 & 3.71 & 2.08 & 2.44 & 2.07 & 2.73 \\  & Narrow LiDAR & 1.92 & 1.14 & 0.832 & 1.04 & 0.911 & 0.913 \\  & Low-inclination & 0.269 & 0.303 & 0.597 & 1.17 & 1.23 & 0.519 \\  & LiDAR & & & & & & \\ \hline \multirow{5}{*}{30-day} & PMW & **100** & 0.00 & 0.00 & **98.2** & **97.8** & 0.00 \\  & Ku-band SAR & **97.7** & 0.00 & **96.0** & **93.3** & **90.3** & **94.3** \\ \cline{1-1}  & C-band SAR & **94.9** & 0.00 & **91.5** & **87.7** & **82.2** & **88.9** \\ \cline{1-1}  & Wide LiDAR & 18.3 & 13.8 & 8.84 & 11.4 & 9.22 & 9.70 \\ \cline{1-1}  & Narrow LiDAR & 10.6 & 7.80 & 5.18 & 7.00 & 5.32 & 5.18 \\ \cline{1-1}  & Low-inclination & 2.00 & 2.12 & 3.60 & 8.20 & 7.30 & 3.01 \\ \cline{1-1}  & LiDAR & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Effective coverage of sensors (in units of percent) for different snow classes with integration periods of 1 day, 3 days, and 30 days. Values greater than 80% are in bold font.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Integration Period**} & \multicolumn{5}{c}{**Efficacy**} \\ \hline  & **0.1** & **0.2** & **0.3** & **0.4** & **0.5** \\ \hline
1-day & 9.8 & 20 & 29 & 39 & 49 \\
3-day & 9.9 & 20 & 30 & 40 & 50 \\
30-day & 10 & 20 & 30 & 40 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Percent effective viewing coverage in taiga snow regions using PMW radiometers in conjunction with efficacies ranging from 0.1 to 0.5. The different rows represent different integration periods.  
for each sensor. In addition to the taiga snow class, the ephemeral snow class is relatively difficult to view given the lower-latitude position of these snow classes when viewed using polar-orbiting sensor configuration. Even with a 500 km wide swath, the Ku-band SAR does not fully view the ephemeral snow class at a synoptic scale (i.e., approximately 3-day period). The narrow-swath LiDAR takes a long time to revisit a given location, especially for locations at low latitudes. Compared to a polar-orbiting LiDAR, the low inclination LiDAR views the snow classes at low latitudes (e.g., ephemeral snow) more frequently but less so for snow classes at high latitudes (e.g., tundra snow). The wide-swath LiDAR requires over 50 days to revisit the same location depending on the latitude and cloud conditions. This suggests a LiDAR with a swath width larger than 20 km or a constellation with several LiDARs would be required in order to achieve a monthly (or less) repeat interval across the northern hemisphere. All variations of LiDAR explored here have a longer interval to revisit maritime snow as compared to other snow classes because cloud attenuation is more prevalent over maritime snow.