Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band

Abstract

This paper describes new advances in the exploitation of oxygen A-band measurements from POLDER3 sensor onboard PARASOL, satellite platform within the A-Train. These developments result from not only an account of the dependence of POLDER oxygen parameters to cloud optical thickness <i>τ</i> and to the scene's geometrical conditions but also, and more importantly, from the finer understanding of the sensitivity of these parameters to cloud vertical extent. This sensitivity is made possible thanks to the multidirectional character of POLDER measurements. In the case of monolayer clouds that represent most of cloudy conditions, new oxygen parameters are obtained and calibrated from POLDER3 data colocalized with the measurements of the two active sensors of the A-Train: CALIOP/CALIPSO and CPR/CloudSat. From a parameterization that is (<i>&mu;</i>_s, <i>τ</i>) dependent, with <i>&mu;</i>_s the cosine of the solar zenith angle, a cloud top oxygen pressure (CTOP) and a cloud middle oxygen pressure (CMOP) are obtained, which are estimates of actual cloud top and middle pressures (CTP and CMP). Performances of CTOP and CMOP are presented by class of clouds following the ISCCP classification. In 2008, the coefficient of the correlation between CMOP and CMP is 0.81 for cirrostratus, 0.79 for stratocumulus, 0.75 for deep convective clouds. The coefficient of the correlation between CTOP and CTP is 0.75, 0.73, and 0.79 for the same cloud types. The score obtained by CTOP, defined as the confidence in the retrieval for a particular range of inferred value and for a given error, is higher than the one of MODIS CTP estimate. Scores of CTOP are the highest for bin value of CTP superior in numbers. For liquid (ice) clouds and an error of 30 hPa (50 hPa), the score of CTOP reaches 50% (70%). From the difference between CTOP and CMOP, a first estimate of the cloud vertical extent <i>h</i> is possible. A second estimate of <i>h</i> comes from the correlation between the angular standard deviation of POLDER oxygen pressure <i>&sigma;</i>_<i>P</i>_O₂ and the cloud vertical extent. This correlation is studied in detail in the case of liquid clouds. It is shown to be spatially and temporally robust, except for clouds above land during winter months. The analysis of the correlation's dependence on the scene's characteristics leads to a parameterization providing <i>h</i> from <i>&sigma;</i>_<i>P</i>_O₂. For liquid water clouds above ocean in 2008, the mean difference between the actual cloud vertical extent and the one retrieved from <i>&sigma;</i>_<i>P</i>_O₂ (from the pressure difference) is 5 m (−12 m). The standard deviation of the mean difference is close to 1000 m for the two methods. POLDER estimates of the cloud geometrical thickness obtain a global score of 50% confidence for a relative error of 20% (40%) of the estimate for ice (liquid) clouds over ocean. These results need to be validated outside of the CALIPSO/Clou...

Effects of long-range aerosol transport on the microphysical properties of low-level liquid clouds in the Arctic

“…Cloud top pressure is derived from the cloud oxygen pressure (Bréon and Colzy, 1999). Cloud top pressure retrieved by POLDER-3 appears to be a better proxy for low-level cloud height than MODIS cloud top pressure derived using a thermal signature assuming a given temperature profile (Buriez et al, 1997;Weisz et al, 2007;Tietze et al, 2011;Desmons et al, 2013).…”

Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI

“…Turning to narrowband bispectral multiangular measurements in the A-band, Ferlay et al (2010) suggested using the correlation between the angular standard deviation of the cloud oxygen pressure and the cloud geometrical thickness. The feasibility of this technique was later on confirmed by Desmons et al (2013), who compared POLDER3/PARASOL retrievals of cloud geometrical thickness to information derived from collocated active sensors (CALIOP/CLOUDSAT). At the same time, a similar approach proposed using the differential absorption occurring between single-view measurements in the O 2 A-and B-bands (Yang et al, 2013).…”

“…In contrast, passive sensors allow for a larger coverage but, so far, the accuracy of retrieved cloud top altitude is limited and the possibility of obtaining cloud geometrical thickness has yet to be consolidated (Ferlay et al, 2010;Desmons et al, 2013). Numerous techniques have been developed to retrieve cloud height from passive sensors.…”

“…Building on previous analyses by Ferlay et al (2010) and Desmons et al (2013), our present analysis aims to understand the feasibility of retrieving those parameters for all types of clouds (liquid/ice, thin/thick) and for a range of surface albedo values. But our study remains limited to homogeneous single-layer clouds without aerosols.…”

“…Several studies have demonstrated the great interest of combining multi-spectral, multi-angular and polarized measurements in the visible, near and shortwave infrared to better constrain retrievals of cloud microphysical (Bréon and Doutriaux-Boucher, 2005;Zhang et al, 2009;Riedi et al, 2010) and macrophysical (Ferlay et al, 2010;Desmons et al, 2013) properties. In this context, several missions that will fly a new generation of polarimetric multi-angular sensors that are currently being formulated.…”