Fast cloud parameter retrievals of MIPAS/Envisat

Abstract

The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. <br><br> Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 10<sup>7</sup> μm<sup>2</sup> cm<sup>−2</sup> and an ice water content of 10<sup>−5</sup> g m<sup>−3</sup> is estimated, depending on the horizontal and vertical extent of the cloud. <br><br> Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e.g. applyin...

A multi-wavelength classification method for polar stratospheric cloud types using infrared limb spectra

“…Its main strength is the classification of clouds where the radiances are dominated by NAT particles with radii smaller than 3 µm (Höpfner et al, 2006a). However, Spang et al (2012) already showed that ice particles can overlap the STS region, and vice versa; STS with large VDP may overlap the region attributed to ice (Fig. 3).…”

“…For example, 3 km below the cloud bottom of a 2 km thick cloud layer, the effective cloud path shrinks to 2 × 57 km = 114 km; for a cloud layer of only 0.5 km thickness a cloud path of ∼ 31 km remains. Spang et al (2012) showed that detection sensitivity and optical thickness in the limb strongly relate to the integrated volume density path (VDP) or the integrated area density path (ADP) along the line of sight. Subject to the particle median radius r, optical thickness is dominated by ADP for cloud types with larger particles (r > 5 µm, typically ice clouds) and VDP for small particles (r < 5 µm, like STS, NAT, and sulfate aerosols).…”

“…Finally, note the cloud index correlates well with VDP and ADP, depending on the cloud type. Spang et al (2012) showed that CI is a useful proxy for the optical thickness of the cloud and that it is possible to estimate VDP or ADP from the CI measurements depending on the particle type.…”

A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation

“…The instantaneous field of view of MIPAS covers 3-4 km (elevation) × 30 km (azimuth). Several studies have demonstrated that MIPAS was capable of detecting PSCs based on specific spectral signatures in the mid-infrared (Spang et al, 2004(Spang et al, , 2005Höpfner et al, 2006a, b;Spang et al, 2012). A particular advantage of MIPAS was its sensitivity to low particle concentrations due to the long integration paths of the limb observation geometry.…”

Satellite observations of cirrus clouds in the Northern Hemisphere lowermost stratosphere

“…The IR limb sounder detection sensitivity for clouds is in the range of spaceborne lidar measurements (Höpfner et al, 2009;Spang et al, 2012). A 100 km or even 1 km horizontally extended cirrus cloud is detectable by an IR limb sounder with an ice water content (IWC) of 3 × 10 −6 and 3 × 10 −4 g m −3 respectively , assuming that the cloud fills the vertical field of view of the instrument completely.…”