Cloud-Top Altitude Measurements from Satellites

Saiedy, F.; Hilleary, D. T.; Morgan, W. A.

doi:10.1364/ao.4.000495

Cited by 30 publications

(16 citation statements)

References 8 publications

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“…Because of the strength of the O 2 A-band, this method is sensitive to both high and low clouds and appears to be insensitive to temperature inversions. The method is widely applied both to measurements taken from airplanes (e.g., Lindstrot et al 2006) and to satellite data (see Saiedy et al 1965;Vanbauce et al 1998;Koelemeijer et al 2001;Preusker et al 2007; Lelli et al 2012;Desmons et al 2013). However, because this method only accounts approximately for the penetration and multiple scattering of photons inside the cloud, it tends to systematically overestimate cloud-top pressures (hence, it underestimates cloud-top altitudes; Vanbauce et al 1998).…”

Section: Introductionmentioning

confidence: 99%

The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

Fauchez

Rossi

Stam

2017

ApJ

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Earth-like, potentially habitable exoplanets are prime targets in the search for extraterrestrial life. Information about their atmospheres and surfaces can be derived by analyzing thelight of the parent star reflected by the planet. We investigate the influence of the surface albedo A s , the optical thickness b cloud ,thealtitude of water clouds, and the mixing ratio of biosignature O 2 on the strength of the O 2 A-band (around 760 nm) in theflux and polarization spectra of starlight reflected by Earth-like exoplanets. Our computations for horizontally homogeneous planets show that small mixing ratios (η<0.4) will yield moderately deep bands in flux and moderate-to-small band strengths in polarization, and that clouds will usually decrease the band depth in flux and the band strength in polarization. However, cloud influence will be strongly dependent onproperties such as optical thickness, top altitude, particle phase, coverage fraction, andhorizontal distribution. Depending on the surface albedoand cloud properties, different O 2 mixing ratios η can give similar absorption-band depths in flux and band strengths in polarization, especially if the clouds have moderate-to-high optical thicknesses. Measuring both the flux and the polarization is essential to reduce the degeneracies, although it will not solve them,especiallynot for horizontally inhomogeneous planets. Observations at a wide range of phase angles and with a high temporal resolution could help to derive cloud properties and, once those are known, the mixing ratio of O 2 or any other absorbing gas.

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Section: Introductionmentioning

confidence: 99%

The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

Fauchez

Rossi

Stam

2017

ApJ

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“…As was stated in the earlier literature (Yamamoto and Wark, 1961;Saiedy et al, 1965), multiple scattering within cloud layers enhances absorption of radiation by dioxygen, and thus affects the relevance and accuracy of the retrieved cloud pressure from A-band measurements. It partly explains the difference between apparent and actual cloud top pressures, which has been largely recognized for the different measurement approaches described previously.…”

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confidence: 88%

Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band

et al. 2013

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This paper describes new advances in the exploitation of oxygen A-band measurements from POLDER3 sensor onboard PARASOL, satellite platform within the A-Train. These developments result from not only an account of the dependence of POLDER oxygen parameters to cloud optical thickness τ and to the scene's geometrical conditions but also, and more importantly, from the finer understanding of the sensitivity of these parameters to cloud vertical extent. This sensitivity is made possible thanks to the multidirectional character of POLDER measurements. In the case of monolayer clouds that represent most of cloudy conditions, new oxygen parameters are obtained and calibrated from POLDER3 data colocalized with the measurements of the two active sensors of the A-Train: CALIOP/CALIPSO and CPR/CloudSat. From a parameterization that is (μ_s, τ) dependent, with μ_s the cosine of the solar zenith angle, a cloud top oxygen pressure (CTOP) and a cloud middle oxygen pressure (CMOP) are obtained, which are estimates of actual cloud top and middle pressures (CTP and CMP). Performances of CTOP and CMOP are presented by class of clouds following the ISCCP classification. In 2008, the coefficient of the correlation between CMOP and CMP is 0.81 for cirrostratus, 0.79 for stratocumulus, 0.75 for deep convective clouds. The coefficient of the correlation between CTOP and CTP is 0.75, 0.73, and 0.79 for the same cloud types. The score obtained by CTOP, defined as the confidence in the retrieval for a particular range of inferred value and for a given error, is higher than the one of MODIS CTP estimate. Scores of CTOP are the highest for bin value of CTP superior in numbers. For liquid (ice) clouds and an error of 30 hPa (50 hPa), the score of CTOP reaches 50% (70%). From the difference between CTOP and CMOP, a first estimate of the cloud vertical extent h is possible. A second estimate of h comes from the correlation between the angular standard deviation of POLDER oxygen pressure σ_P_O₂ and the cloud vertical extent. This correlation is studied in detail in the case of liquid clouds. It is shown to be spatially and temporally robust, except for clouds above land during winter months. The analysis of the correlation's dependence on the scene's characteristics leads to a parameterization providing h from σ_P_O₂. For liquid water clouds above ocean in 2008, the mean difference between the actual cloud vertical extent and the one retrieved from σ_P_O₂ (from the pressure difference) is 5 m (−12 m). The standard deviation of the mean difference is close to 1000 m for the two methods. POLDER estimates of the cloud geometrical thickness obtain a global score of 50% confidence for a relative error of 20% (40%) of the estimate for ice (liquid) clouds over ocean. These results need to be validated outside of the CALIPSO/Clou...

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“…This oxygen sensitivity to cloud height, along with its constant vertical abundance all through the troposphere, can serve as a basis for the design of retrieval algorithms. This approach was firstly proposed by Saiedy et al (1965Saiedy et al ( , 1967, who also noticed that the assumption of a cloud as a perfect Lambertian reflector with zero transmittance leads to lower values of cloud heights. When light scattering inside and below the cloud are taken into account in the forward modeling, the geometrical thickness (CGT) of a cloud can also be retrieved, being beneficial for the accuracy of cloud top height (Fischer and Grassl, 1991;Kuji and Nakajima, 2002;Ferlay et al, 2010;Schuessler et al, 2013).…”

Section: The Sacura Algorithmmentioning

confidence: 99%

Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data

Lelli

Weber

Burrows

2016

Front. Environ. Sci.

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This paper reports on the evaluation of long-term cloud products as retrieved from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument with the DLR/ESA processor in its version 5.02 and the operational implementation of the Semi-Analytical CloUd Retrieval Algorithm SACURA. The comparison is performed against spaceborne and ground-based cloud data. The satellite records are the SCIAMACHY/SACURA in its scientific implementation and the Global retrieval of ATSR cloud parameters and evaluation (GRAPE) data set, in its version 3.2, generated for the nadir view of the Advanced Along-Track Scanning Radiometer (AATSR) instrument onboard ENVISAT. Ground-based data are derived from profiles of micro-pulse lidars, continuously operated at three Atmospheric Radiation Measurement (ARM) research facilities. They are, namely, North Slope Alaska, Southern Great Plains and Tropical Western Pacific-Nauru, located in three different latitude belts. It has been found that SCIAMACHY cloud top heights, inferred in the visible-near infrared, have a seasonal dependent overestimation in range 0.6-1.0 km when compared to the thermal infrared-derived AATSR cloud top heights. The comparison with the in-situ cloud retrievals reveals that SCIAMACHY cloud altitudes are more accurate for local cloud cover values > 0.6.

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Cloud-Top Altitude Measurements from Satellites

Cited by 30 publications

References 8 publications

The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band

Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data

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Cloud-Top Altitude Measurements from Satellites

Cited by 30 publications

References 8 publications

The O2 A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

The O2 A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band

Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data

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The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets

The O₂ A-Band in the Fluxes and Polarization of Starlight Reflected by Earth-Like Exoplanets