Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth

Garnier, Anne; Pelon, Jacques; Dubuisson, Philippe; Faivre, M.; Chomette, Olivier; Pascal, Nicolas; Kratz, David P.

doi:10.1175/jamc-d-11-0220.1

Cited by 98 publications

(127 citation statements)

References 34 publications

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“…Aside from being a ground-based retrieval approach in its own right (in tandem with a lidar system), this method can also be used for comparison with CALIPSO's level 2 products. The CALIPSO remote sensing suite technique employs an onboard imaging IR radiometer and the CALIOP lidar to enable the retrieval of particle size and optical depth across a narrow swath image (Garnier et al, 2012). Our retrieval, viewed as a CALIPSO validation technique is rendered all the more interesting because of the geographic position of the PEARL site; it is a high-Arctic site that sees frequent thin-cloud events and its position near the maximum latitude of the CALIOP polar orbit ensures that there are frequent overpasses of that sensor package (within a radius of hundreds of kilometers).…”

Section: Discussionmentioning

confidence: 99%

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

et al. 2017

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Abstract. Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80 • N, 86 • W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.

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Section: Discussionmentioning

confidence: 99%

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

et al. 2017

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“…In this section, we list possible sources of uncertainty. A temperature defined by a centroid altitude (Garnier et al, 2012) would better account for the cloud vertical profile and could give a better estimate of the equivalent radiative temperature. However, our results show that the CRE is mainly driven by Z …”

Section: Limitations Of the Olr Linear Expressionmentioning

confidence: 99%

The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated

et al. 2017

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Abstract. According to climate model simulations, the changing altitude of middle and high clouds is the dominant contributor to the positive global mean longwave cloud feedback. Nevertheless, the mechanisms of this longwave cloud altitude feedback and its magnitude have not yet been verified by observations. Accurate, stable, and long-term observations of a metric-characterizing cloud vertical distribution that are related to the longwave cloud radiative effect are needed to achieve a better understanding of the mechanism of longwave cloud altitude feedback. This study shows that the direct measurement of the altitude of atmospheric lidar opacity is a good candidate for the necessary observational metric. The opacity altitude is the level at which a spaceborne lidar beam is fully attenuated when probing an opaque cloud. By combining this altitude with the direct lidar measurement of the cloud-top altitude, we derive the effective radiative temperature of opaque clouds which linearly drives (as we will show) the outgoing longwave radiation. We find that, for an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m −2 . Similarly, the longwave cloud radiative effect of optically thin clouds can be derived from their top and base altitudes and an estimate of their emissivity. We show with radiative transfer simulations that these relationships hold true at single atmospheric column scale, on the scale of the Clouds and the Earth's Radiant Energy System (CERES) instantaneous footprint, and at monthly mean 2 • × 2 • scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin-cloud coverage is 36 % and contributes 27 % of the global mean cloud radiative effect. The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated provides a simple formulation of the cloud radiative effect in the longwave domain and so helps us to understand the longwave cloud altitude feedback mechanism.

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“…King et al, 1998;Vaughan et al, 2009;Winker et al, 2010;Garnier et al, 2012Garnier et al, , 2013. The emergence of such possibilities of synergism was a notable factor in the resurgence of algorithms based on variational methods, such as optimal estimation (e.g.…”

Section: Introductionmentioning

confidence: 99%

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

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et al. 2014

Quart J Royal Meteoro Soc

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This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path of one ice-cloud layer and the optical thickness and droplet effective radius of up to two liquid-water cloud layers, along with rigorous uncertainties. In order to perform the retrievals, radiometric measurements in five channels ranging from the visible to the thermal infrared are utilized. The position of cloud layers is currently provided by lidar information, which narrows the retrievals to its track. In the first part of this article, theoretical information content analyses are performed under different atmospheric conditions, over an oceanic surface. This type of analysis quantifies prior to the retrievals the amount of information that should be available regarding each parameter to be retrieved and helps to identify which set of channels provides this information. It is observed that strong information can be expected for retrieving each parameter in double-layer cases, while yet stronger limitations appear in triple-layer cases. In the second part of this article, our methodology is applied to a case study. In agreement with a priori expectations, accurate retrievals of ice and liquid cloud properties are obtained. These results are later compared with the products of a single-layer retrieval method, CloudAerosol Lidar with Orthogonal Polarization (CALIOP) operational products and in situ estimates. We show that a much better consistency with the latter two is found when retrieving the properties of each layer simultaneously. However, further statistical analyses and comparisons with various operational products should be undertaken for validation of the methodology. Such results will be presented in the second part of this study.

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Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth

Cited by 98 publications

References 34 publications

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated

A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study

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