Impacts of cloud heterogeneities on cirrus optical properties retrieved from space-based thermal infrared radiometry

Abstract

Abstract. This paper presents a study, based on simulations, of the impact of cirrus cloud heterogeneities on the retrieval of cloud parameters (optical thickness and effective diameter) for the Imaging Infrared Radiometer (IIR) on board CALIPSO. Cirrus clouds are generated by the stochastic model 3DCLOUD for two different cloud fields and for several averaged cloud parameters. One cloud field is obtained from a cirrus observed on 25 May 2007 during the airborne campaign CIRCLE-2 and the other is a cirrus uncinus. The radiative transfer is simulated with the 3DMCPOL code. To assess the errors due to cloud heterogeneities, two related retrieval algorithms are used: (i) the split-window technique to retrieve the ice crystal effective diameter and (ii) an algorithm similar to the IIR operational algorithm to retrieve the effective emissivity and the effective optical thickness. Differences between input parameters and retrieved parameters are compared as a function of different cloud properties such as the mean optical thickness, the heterogeneity parameter and the effective diameter. The optical thickness heterogeneity for each 1 km × 1 km observation pixel is represented by the optical thickness standard deviation computed using 100 m × 100 m subpixels. We show that optical thickness heterogeneity may have a strong impact on the retrieved parameters, mainly due to the plane-parallel approximation (PPA assumption). In particular, for cirrus clouds with ice crystal diameter of approximately 10 µm, the averaged error on the retrieved effective diameter and optical thickness is about 2.5 µm (∼ 25 %) and −0.20 (∼ 12 %), respectively. Then, these biases decrease with increasing effective size due to a decrease of the cloud absorption and, thus, the PPA bias. Cloud horizontal heterogeneity effects are greater than other possible sources of retrieval errors such as those due to cloud vertical heterogeneity impact, surface temperature or atmospheric temperature profile uncertainty and IIR retrieval uncertainty. Cloud horizontal heterogeneity effects are larger than the IIR retrieval uncertainty if the standard deviation of the optical thickness, inside the observation pixel, is greater than 1.

Scale dependence of cirrus horizontal heterogeneity effects on TOA measurements – Part I: MODIS brightness temperatures in the thermal infrared

“…In this study, we assume that TOA brightness temperature differences between BT computation assuming 1-D RT inside a homogeneous pixel and 3-D RT inside a heterogeneous pixel depend on two effects: (i) the optical thickness horizontal inhomogeneity leading to the planeparallel approximation bias and the (ii) horizontal radiative transport effect due to the independent pixel approximation error. The cloud vertical heterogeneities of optical properties are neglected here, based on the findings of Fauchez et al (2014Fauchez et al ( , 2015. As previous studies already showed, the PPHB is the larger heterogeneity effect for nadir observations at the typical spatial resolution of polar orbiters such as AIRS, MODIS or IIR.…”

“…Concerning infrared (IR) radiances or brightness temperatures (BTs), Fauchez et al (2012Fauchez et al ( , 2014 show that heterogeneity effects can significantly influence cirrus optical property retrievals at the 1 km scale of IIR thermal infrared observations, with potentially more than +10 K on TOA BT for heterogeneous pixels, depending also on the cloud altitude. Fauchez et al (2015) also show that these TOA BT effects result in an overestimate of the retrieved effective diameter by more than 50 % for small crystals (CED under 20 µm) and underestimate the retrieved optical thickness by up to 25 %. These errors could significantly influence the cirrus feedbacks assumed in global atmospheric models.…”

“…(ii) This paper is focused only on horizontal heterogeneities: we assume that the vertical variability in optical properties is negligible compared to the horizontal variability (see Fauchez et al, 2014Fauchez et al, , 2015.…”

Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder

“…Fauchez et al, 2015), errors that arise from a lack of precision, accuracy, or incomplete sampling in the atmospheric and surface state (e.g. Kahn et al, 2015), variability in mixtures of ice crystal habits and PSDs within a single satellite pixel (e.g.…”

Cloud heterogeneity effects on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

“…At 1 km pixel size, they found significant errors ranging between -0.3% to 14% (-5% to 30%) from nadir (oblique view) depending on the cloud heterogeneity. Some recent studies were also made in case of ice clouds and found non negligible errors on retrieved COT from IR measurements 10 (Fauchez et al, 2015) or from visible and near-infrared measurements (Zhou et al, 2017) In this paper, we investigate the impact of cloud heterogeneities on retrieved parameters on observations from the POLarization and Directionality of Earth Reflectance radiometer, POLDER, which was on board the platforms ADEOS1 in 1999, ADEOS2 in 2002and PARASOL between 2005. POLDER/PARASOL allows to measure multi-angular 15 total reflectances from 443 to 1020 nm and multi-angular polarized reflectances for three channels (490, 670 and 865 nm).…”