Reply on RC1

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Water vapor plays an important role in the greenhouse effect, rendering it an atmospheric constituent that requires continuous and global monitoring by different types of remote sensing instruments. The TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI/S5P) Total Column Water Vapor (TCWV) is a new product retrieved from the visible blue spectral range (435–455 nm), using an algorithm that was originally developed for the GOME-2/MetOp sensors. For the purposes of this work, 2.5 years of continuous satellite observations at high spatial resolution are validated against co-located (in space and in time) precipitable water Level 2.0 (quality-assured) ground-based measurements from the NASA AERONET (AErosol RObotic NETwork). The network uses Cimel Sun photometers located at approximately 1300 stations globally to monitor precipitable water among other products. Based on data availability, 369 of the stations were used in this study. The two datasets, satellite- and ground-based, were co-located, and the relative differences of the comparisons were calculated and statistically analyzed. The Pearson correlation coefficient of the two products is found to be 0.91, and the mean bias of the overall relative percentage differences is of the order of <span class="inline-formula">−2.7</span> %. For the Northern Hemisphere midlatitudes (30–60<span class="inline-formula">^∘</span> N), where the density of the ground-based stations is high, the mean relative bias was found to be <span class="inline-formula">−1.8</span> %, while in the tropics (<span class="inline-formula">±15</span><span class="inline-formula">^∘</span>) the TROPOMI TCWV product has a relative dry bias of up to <span class="inline-formula">−10</span> %. The effect of various algorithm and geophysical parameters, such as air mass factor, solar zenith angle, clouds and albedo, is also presented and discussed. It was found that the cloud properties affect the validation results, leading the TCWV to a dry bias of <span class="inline-formula">−20</span> % for low cloud heights (cloud top pressure (CTP) <span class="inline-formula">&gt;800</span> hPa). Moreover, cloud albedo introduces a wet bias of 15 % when it is below 0.3 and a dry bias up to <span class="inline-formula">−25</span> % when the clouds are more reflective. Overall, the TROPOMI/S5P TCWV product, on a global scale and for moderate albedo and cloudiness, agrees well at <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><mo>-</mo><mn mathvariant="normal">2.7</mn><mo>±</mo><mn mathvariant="normal">4.9</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="52pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="93d29de78384017cd1900da90d2be30e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-16-57-2023-ie00001.svg" width="52pt" height="10pt" src="amt-16-57-2023-ie00001.png"/></svg:svg></span></span> % with the AERONET observations but probably within about <span class="inline-formula">−8</span> % to <span class="inline-formula">−13</span> % with respect to the “truth”.