Upper tropospheric humidity and cirrus geometrical and optical thickness: Relationships inferred from 1 year of collocated AIRS and CALIPSO data

Abstract

[1] Profiles of relative humidity with respect to ice (RHice) determined from spaceborne passive remote sensing suffer a lack of vertical and spatial resolutions. RHice distributions show dry biases compared to in situ observations because geometrically thin moist layers are integrated within coarser vertical resolutions, a direct effect being the underestimation of ice supersaturation (RHice > 100%) occurrence. Collocated data from the Atmospheric Infrared Sounder (AIRS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) provide the opportunity to investigate relationships between RHice and geometrical thickness and optical depth of high clouds near the tropopause. ''Apparent'' optical depths are derived for single-layer high clouds from CALIPSO. By comparing these ''apparent'' optical depths to cloud infrared emissivities derived from AIRS the multiple scattering contribution is estimated and the optical depths are corrected. Mean RHice increases with cloud geometrical thickness but remains low compared to 100% except for very vertically extended clouds. Optically thicker clouds show on average larger geometrical thickness and larger relative humidity than optically thinner clouds. However, for a comparable geometrical thickness, optically thinner clouds are on average slightly more humid. This study concludes that cloud geometrical thickness has a greater influence than cloud optical depth on RHice integrated within a coarse vertical resolution. Limitations of AIRS humidity observations regarding the detection of ice supersaturation are discussed.

A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat

“…4, being aware that this product is still not final and has large uncertainties also due to multiple scattering corrections (e.g. Lamquin et al, 2008). CALIPSO data were obtained through the NASA Atmospheric Sciences Data Center (ASDC) by the ICARE Thematic Center created by CNES (http://www-icare.univ-lille1.fr/) and its interface ClimServ at IPSL (http://climserv.ipsl.polytechnique.fr/).…”

Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data

“…We use version 5 of AIRS L2 data and retrieve RHi as in Lamquin et al (2008). Specific humidity q of an atmospheric layer is obtained from the given mixing ratio with q=w/(1+w), whereas temperatures are given at top and bottom of each layer.…”

“…We will, however, consider these cases as independent. In Lamquin et al (2008) collocations of AIRS and CALIPSO considered five pixels with an averaging of their vertical profiles and no large difference was inferred by considering the pixels independently. Since CALIPSO does not provide information on the relative humidity, we will use the data as an indication of presence, position and vertical extension of clouds in relationship to RHi from ECMWF.…”

“…Right: distribution of cloud cover from ECMWF for two categories of relative humidity wrt ice RHi E <50% and RHi E ∈[90%, 110%]. To investigate RHi of the moist mode further in relationship with clouds, we use in addition collocated AIRS-CALIPSO data (for the details on the collocation scheme see Lamquin et al, 2008). Figure 9 presents distributions of RHi A when RHi E >80% compared to distributions of RHi A in the presence of CALIPSO high clouds, separately for the same pressure layers as in Fig.…”

CALIPSO, des cristaux dans le ciel

“…En attendant la disponibilité de champs de vapeur d'eau finement résolus, les instruments spatiaux sont cependant les plus à même de documenter la haute troposphère à l'échelle globale. Plusieurs études (par exemple, Lamquin et al, 2008 ;Martins et al, 2011) …”