The absolute spectral calibration is characterized by two metrics (Table I) at the physical spectel level. The baseline of the analysis (called option 1 hereafter) is to gather all measurement points for each channel (Table IV, Table V and Table VI) to fit an absolute calibration model that minimizes the residuals. The instrument’s design leads to a quasi-linear spectral calibration. Hence, to account for the deviations to linearity of the grating dispersion law, a polynomial function becomes the choice for fitting the calibration data. Specifically, a fourth-degree polynomial function was chosen as it accurately fits the data points across both channels while limiting overfitting artifacts. Second-degree polynomial fitting results in a significantly larger Sum of Squared Errors (SSE) (multiple data points are consistently 1 nm or further away from the fitting polynomial). Higher-degree polynomial fitting improves the SSE only marginally at the expense of much more significant overfitting artifacts at the edges of the wavelength range. Third-degree polynomial fitting also provides a good balance with a relatively low SSE without overfitting artifacts, but the fourth-degree polynomial was preferred for its overall slightly better consistency with the data and theoretical sampling.
We noticed that the data points acquired with OP1-LDO and OP5 exhibited a distinct trend compared to those for OP0, OP1-IAS, and OP3 for both channels. In particular, the best fit at wavelengths greater than 1400 nm misses many data points of these sources even when accounting for their error margins. Therefore, we considered a second option in which the minimization procedure was performed using only the data points from OP0, OP1-IAS, and OP3. The restricted data set of this option (called option 2 below) was a priori given higher confidence for several reasons. The atmospheric signatures can be taken with increased confidence, and the ICU (OP0) is specifically designed for the spectral calibration of the instrument. For the IR channel, we also investigated an option 2 without OP1-IAS data because the data were inconsistent with atmospheric signatures by several nm.
For both channels, the solution provided by option 1 has high uncertainty, as expected, while the fit with option 2 matches very well with all the data points, suggesting that these data sets are more consistent. This leads to low error margins in the resulting calibration (~ 0.7 nm for the VISNIR channel and ~ 2 nm for the IR channel). The results of the derived CWL are shown in Fig. 11 and Fig. 12 for the center of each channel. The polynomial coefficients (a_0 being the coefficient of the constant term and a_4 the coefficient of the fourth-degree term) as well as the resulting spectral ranges are summarized in Table VII.
Table VII. Spectral range comparison for both channels and both options

|  |  | Spectral Range (nm) | Error Margin (nm) | a 0 _ | a 1 _ | a 2 _ | a 3 _ | a 4 _ |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Option 1 | VISNIR | 489 – 2349 | 2 | 4.886e2 | 1.795 | 2.310e-4 | -3.322e-7 | 1.401e-10 |
|  | IR | 2268 – 5556 | 3.5 | 2.269e3 | 2.991 | 4.093e-4 | -3.138e-7 | 1.502e-10 |
| Option 2 | VISNIR | 491 – 2358 | 0.7 | 4.902e2 | 1.768 | 3.639e-4 | -5.518e-7 | 2.604e-10 |

IR 2271 – 5555 2 2.270e3 2.991 3.801e-4 -2.536e-7 1.170e-10