Comment on egusphere-2026-111

<strong class="journal-contentHeaderColor">Abstract.</strong> The WaLiNeAs campaign took place along the north-western Mediterranean coast between October 2022 and January 2023. This period was marked by unusual weather conditions associated with dry autumn and winter. In such conditions and for the first time, eight ground-based stations equipped with water vapour Raman lidars were strategically deployed by four European countries. We studied the consistency of this network with the water vapour mixing ratio (WVMR) products derived from the Infrared Atmospheric Sounding Interferometer (IASI) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5), which assimilate IASI radiances. The statistical metrics used in the comparison are the mean bias (MB, defined as lidar &ndash; IASI or ERA5), the root mean square error (RMSE) and the correlation coefficient (COR). A positive MB of approximately 0.9 g kg^{<span>&minus;</span>1} (respectively 0.6 g kg^{<span>&minus;</span>1}) between 0.2 and 5 km above mean sea level (amsl) indicates a systematic underestimation of the WVMR by IASI (respectively ERA5). RMSE values range from 1 to 2 g kg^{<span>&minus;</span>1} across all lidar stations for IASI and ERA5, while the measurement uncertainties of the lidars are typically below 0.4 g kg^{<span>&minus;</span>1}. COR presents little variation between stations, it ranges from 0.7 to 0.8 and remains almost constant between 0.2 and 5 km amsl. Both the IASI and the ERA5 products appear to accurately reproduce the temporal variability of the vertical structure of water vapour in the low troposphere. Nevertheless, they show MB and RMSE significantly above the uncertainties of lidar measurements.