## 3 Results and Discussion
### Algorithm Performance for LST Forecasts
#### 3.1.1 The First Case-Study: The Pedemontana Motorway
Scatterplot between observed vs. forecasted LST over the “Ponte Olona” station point during cloudy sky days (**bottom**). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Index** & **Station Point** & \
\begin{tabular}{c} **Hourly Solar** \\ **Radiation as Input** \\ \end{tabular} &
\begin{tabular}{c} **Moving Average (of the Previous** \\ **3 h) of Solar Radiation as Input** \\ \end{tabular} \\ \hline
**Nash-Sutcliffe** & \begin{tabular}{c} Ponte Olona \\ **Efficiency (NSE)** [–] \\ \end{tabular} & \begin{tabular}{c} Gorla \\ **Root Mean Square** \\ \end{tabular} & \
\begin{tabular}{c} 0.86–0.87 \\ 0.84–0.85 \\ 5.50–5.60 \\ 5.90–6.10 \\ \end{tabular} &
\begin{tabular}{c} 0.91–0.92 \\ 0.89–0.90 \\ 4.30–4.40 \\ 4.80–5.00 \\ 4.80–5.00 \\ 0.96–0.97 \\ 0.95–0.96 \\ 0.92–0.93 \\ 0.86–0.88 \\ 0.89–0.91 \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistical indexes during clear sky days between observed and simulated LST values by the MEC algorithm using the hourly solar radiation and the 3 h-moving average as input. A lower performance in these analyses is only found for the forecasted LST values vs. observed ones during cloudy days, mainly due to errors in solar radiation predictions by the WRF model: in fact, the NSE index drops from about 0.90 to 0.60 and the determination coefficient from about 0.92 to 0.80, respectively for clear and cloudy sky days. Nevertheless, a general satisfactory reliability of the algorithm using both the simulated and forecasted data as input is achieved. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multirow{2}{*}{**Station Point**} & \multicolumn{2}{c}{**Hourly Solar**} & \multicolumn{2}{c}{**Moving Average (of the Previous**} \\  & & **Radiation as Input** & **3 h) of Solar Radiation as Input** \\ \hline
**Nash-Sutcliffe** & Ponte Olona & 0.90–0.91 & 0.90–0.92 \\
**Efficiency (NSE) [–]** & Gorla & 0.93 & 0.93 \\
**Root Mean Square** & Ponte Olona & 1.60–1.70 & 1.50–1.70 \\
**Error (RMSE) [\({}^{\circ}\)C]** & Gorla & 1.40–1.50 & 1.40–1.50 \\
**Pearson Correlation** & Ponte Olona & 0.97 & 0.97 \\
**coefficient (r) [–]** & Gorla & 0.97 & 0.97 \\
**Determination** & Ponte Olona & 0.93 & 0.94 \\
**coefficient (R2) [–]** & Gorla & 0.93 & 0.94 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Statistical indexes during cloudy days between observed and simulated LST values by the MEC algorithm using the hourly solar radiation and the 3 h-moving average as input. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multirow{2}{*}{**Station Point**} & \multicolumn{2}{c}{**Hourly Solar**} & \multicolumn{2}{c}{**Moving Average (of the Previous**} \\  & & **Radiation as Input** & **3 h) of Solar Radiation as Input** \\ \hline
**Nash-Sutcliffe** & SP2 & 0.86–0.87 & 0.90–0.91 \\
**Efficiency (NSE) [–]** & Ponte Olona & 0.84–0.85 & 0.90 \\
**Gorla** & 0.84–0.85 & 0.89–0.90 \\
**Root Mean Square** & SP2 & 5.20–5.40 & 4.40–4.50 \\
**Error (RMSE) [\({}^{\circ}\)C]** & Ponte Olona & 5.80 & 4.70 \\
**Gorla** & 5.90–6.00 & 4.80–4.90 \\
**Pearson Correlation** & SP2 & 0.94 & 0.96 \\
**coefficient (r) [–]** & Ponte Olona & 0.93 & 0.96 \\
**Determination** & Gorla & 0.92–0.93 & 0.95–0.96 \\
**Determination** & SP2 & 0.88 & 0.92–0.93 \\
**coefficient (R2) [–]** & Ponte Olona & 0.86–0.87 & 0.92–0.93 \\
**coefficient (R2) [–]** & Gorla & 0.85–0.87 & 0.91–0.93 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Statistical indexes during clear sky days between observed and forecasted LST values by the MEC algorithm using the hourly solar radiation and the 3 h-moving average as input.