Spectral Effect
Lee and Panchula
Where precipitable water data are present in the input data supplied, the spectral effect is calculated as described by Lee and Panchula in [14].
$$M = b_0 + b_1 \AM_{a} + b_2\ \Pwat + b_3 \sqrt{\AM_a} + b_4 \sqrt{\Pwat} + b_5 \frac{\AM_a}{\sqrt{\Pwat}}$$
Where:
\(\AM_a\) absolute air mass, as described in Air Mass;
\(\Pwat\) precipitable water content of the atmosphere, i.e. the depth of water in a column of the atmosphere, if all the water in that column were precipitated as rain, measured in cm.
\(\Pwat\) is available directly in some climate datasets, or can be estimated from air temperature and either relative humidity or dewpoint if needed, as described in Precipitable Water.
The coefficients \(b_0\) to \(b_5\) vary by module technology and are as follows (from [16]):
| Technology | \(b_0\) | \(b_1\) | \(b_2\) | \(b_3\) | \(b_4\) | \(b_5\) |
|---|---|---|---|---|---|---|
| CdTe | 0.86273 | -0.038948 | -0.012506 | 0.098871 | 0.084658 | -0.0042948 |
| mSi, xSi | 0.85914 | -0.02088 | -0.0058853 | 0.12029 | 0.026814 | -0.001781 |
| polySi, multiSi | 0.8409 | -0.027539 | -0.0079224 | 0.1357 | 0.038024 | -0.0021218 |
| CIGS | 0.85252 | -0.022314 | -0.0047216 | 0.13666 | 0.013342 | -0.0008945 |
| aSi | 1.12094 | -0.04762 | -0.0083627 | -0.10443 | 0.098382 | -0.0033818 |