Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions

<p>Space profiling lidars offer a unique insight into cloud properties in Earth's atmosphere and are considered the most reliable source of total (column-integrated) cloud amount (CA), and true (geometrical) cloud top height (CTH). However, lidar-based cloud climatologies suffer from infrequent sampling: every <span class="inline-formula"><i>n</i></span> days, and only along the ground track. This study therefore evaluated four lidar missions, namely CALIPSO (revisit every <span class="inline-formula"><i>n</i>=16</span> d), EarthCARE (<span class="inline-formula"><i>n</i>=25</span>), Aeolus (<span class="inline-formula"><i>n</i>=7</span>), and ICESat-2 (<span class="inline-formula"><i>n</i>=91</span>), to test the hypothesis that each mission provides accurate data on CA and CTH. CA/CTH values for a hypothetical daily revisit mission were used as reference (data simulated with Meteosat 15 min cloud observations, assumed to be a proxy for ground truth). Our results demonstrated that this hypothesis is invalid, unless individual lidar transects are averaged over an area <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">10</mn><mo>×</mo><mn mathvariant="normal">10</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="42pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="4ec6dc02ec3e5bbcc6653dd76da67955"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-15-4307-2022-ie00001.svg" width="42pt" height="11pt" src="amt-15-4307-2022-ie00001.png"/></svg:svg></span></span> in longitude and latitude (or larger). If this is not the case, the required accuracy of 1 % (for CA) or 150 m (for CTH) cannot be met, either for a single-year annual or monthly mean, or for a <span class="inline-formula">&gt;10</span> year climatology. A CALIPSO-focused test demonstrated that the annual mean CA estimate is very sensitive to infrequent sampling, and that this factor alone can result in 14 % or 7 % average uncertainty with 1 or 2.5<span class="inline-formula">^∘</span> resolution data, respectively. Consequently, applications that use gridded lidar data should consider calculating confidence intervals, or a similar measure of uncertainty. Our results suggest that CALIPSO, and its follow-on mission EarthCARE, are very likely to produce consistent cloud records despite the difference in sampling frequency.</p>