Analysis of cirrus cloud spectral signatures in the far infrared

Maestri, Tiziano; Rizzi, Rolando; Tosi, E.; Veglio, P.; Palchetti, Luca; Bianchini, Giovanni; Girolamo, Paolo Di; Masiello, Guido; Serio, Carmine; Summa, Donato

doi:10.1016/j.jqsrt.2014.02.030

Cited by 25 publications

(32 citation statements)

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“…Radiative transfer computation are performed with the RTX code (Rizzi et al, ) that is an extension of the RT3 doubling and adding code introduced by Evans and Stephens (). RTX is a plane parallel, line‐by‐line multiple scattering radiative transfer algorithm used as a reference tool for faster radiative codes (Bozzo et al, ), for validation/calibration experiments (Maestri et al, ), for theoretical studies (Harries et al, ), for cloud properties studies (Bozzo et al, ), and in support of cloud properties retrievals (i.e., in Maestri et al, ).…”

Section: Microphysical Assumptions and Radiative Computations Setupmentioning

confidence: 99%

“…An a priori analysis concerning the expansion of particles phase function in terms of Legendre polynomials is required as a compromise between model accuracy and computing time. Maestri et al () show that using nz = 16 zenith angles for each hemisphere is insufficient to obtain an accurate computation of the radiance spectral field, especially in presence of ice particle with large dimensions. The number of zenith angles used in the radiance field computations affect the representation accuracy of the phase function that is expanded in terms of Legendre coefficients ( nc ).…”

Section: Microphysical Assumptions and Radiative Computations Setupmentioning

confidence: 99%

“…The analysis of the ECOWAR‐COBRA cloudy data proved to be a pilot test study for the Antarctic deployment of the REFIR‐PAD sensor, which will be described in this paper. Both Cox et al () and Maestri et al () analyze few hours of cirrus observations and refer to the specific atmospheric condition encountered during the experiment.…”

Section: Introductionmentioning

confidence: 99%

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Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹

et al. 2019

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One year (2013) of high spectral resolution measurements of downwelling radiance in the 100–1,400 cm−1 range, taken by the Fourier Transform Spectrometer REFIR‐PAD at the research station Concordia (Antarctic Plateau), is analyzed. Optically thin ice clouds are identified by means of a new identification/classification tool based on a Support Vector Machine algorithm. The use of transparent microwindow channels in the Far InfraRed (FIR) spectral region (100–667 cm−1) is shown to be of great importance in the identification and classification of cloud type. In particular, the channels between 380 and 575 cm−1 are key channels for the clear/cloud and phase identification due to their sensitivity to cloud properties; in addition, FIR channels down to 238 cm−1 are exploited for the selection of precipitating or nonprecipitating cases because of their sensitivity also to water vapor content. A subset of 26 cases of nonprecipitating ice clouds is selected based on the presence of colocated LIDAR and radiosonde data. REFIR‐PAD channel in the 800–1,000 cm−1 are used to derived optical and microphysical properties for four different assumptions concerning the crystal habits. Results, showing a correlation between cloud base temperature, optical depth, and particle size distribution effective dimensions, are compared with what found in literature. Based on the retrievals, forward simulations are also run over the whole sensor spectral interval, and results are compared to data. The simulation‐data residuals in the FIR are evaluated for selected “window” channels and analyzed in relation to crystal's habit assumption, cloud retrieved features, and atmospheric water vapor content.

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Section: Microphysical Assumptions and Radiative Computations Setupmentioning

confidence: 99%

Section: Microphysical Assumptions and Radiative Computations Setupmentioning

confidence: 99%

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Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹

et al. 2019

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“…The contribution of the far infrared region (FIR) below 667 cm −1 (wavelength > 15 µm) is also very important (Maestri et al, 2014) because in this region the emitted spectrum is extremely sensitive to the cloud particle effective diameter, in particular for small particle sizes ( 20-30 µm). The sensitivity to the effective diameter is enhanced in the FIR because of the strong modulation of the imaginary part of the refractive index of ice (Lynch et al, 2002;Baran, 2007), which has a peak at 800 cm −1 and a minimum at 400 cm −1 .…”

Section: Introductionmentioning

confidence: 99%

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

et al. 2017

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Abstract. The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared -Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230-980 cm −1 spectral band. To simulate atmospheric radiative transfer, the LineBy-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the singlescattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg-Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

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“…The FIRR was developed as a technology demonstrator for the Thin Ice Clouds in Far-InfraRed Experiment (TICFIRE; Blanchet et al, 2011) satellite mission, the primary focus of which is on the water cycle in the Arctic, and ice clouds in particular. Like cirrus at midlatitudes (Cox et al, 2010;Maestri et al, 2014), ice clouds encountered in the Arctic significantly affect the atmosphere radiative budget in the FIR, especially because they can fill the whole troposphere (Grenier et al, 2009). In very dry conditions, they act as particularly efficient emitters that radiatively cool the atmosphere (Blanchet et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Airborne observations of far-infrared upwelling radiance in the Arctic

Libois¹,

Ivanescu

Blanchet³

et al. 2016

Atmos. Chem. Phys.

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Abstract. The first airborne measurements of the FarInfraRed Radiometer (FIRR) were performed in April 2015 during the panarctic NETCARE campaign. Vertical profiles of spectral upwelling radiance in the range 8-50 µm were measured in clear and cloudy conditions from the surface up to 6 km. The clear sky profiles highlight the strong dependence of radiative fluxes to the temperature inversion typical of the Arctic. Measurements acquired for total column water vapour from 1.5 to 10.5 mm also underline the sensitivity of the far-infrared greenhouse effect to specific humidity. The cloudy cases show that optically thin ice clouds increase the cooling rate of the atmosphere, making them important pieces of the Arctic energy balance. One such cloud exhibited a very complex spatial structure, characterized by large horizontal heterogeneities at the kilometre scale. This emphasizes the difficulty of obtaining representative cloud observations with airborne measurements but also points out how challenging it is to model polar clouds radiative effects. These radiance measurements were successfully compared to simulations, suggesting that state-of-the-art radiative transfer models are suited to study the cold and dry Arctic atmosphere. Although FIRR in situ performances compare well to its laboratory performances, complementary simulations show that upgrading the FIRR radiometric resolution would greatly increase its sensitivity to atmospheric and cloud properties. Improved instrument temperature stability in flight and expected technological progress should help meet this objective. The campaign overall highlights the potential for airborne far-infrared radiometry and constitutes a relevant reference for future similar studies dedicated to the Arctic and for the development of spaceborne instruments.

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Analysis of cirrus cloud spectral signatures in the far infrared

Cited by 25 publications

References 50 publications

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

Airborne observations of far-infrared upwelling radiance in the Arctic

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Analysis of cirrus cloud spectral signatures in the far infrared

Cited by 25 publications

References 50 publications

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm−1

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm−1

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

Airborne observations of far-infrared upwelling radiance in the Arctic

Contact Info

Product

Resources

About

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹

Antarctic Ice Cloud Identification and Properties Using Downwelling Spectral Radiance From 100 to 1,400 cm⁻¹