Sensitivity analysis of polarimetric O&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; A-band spectra for potential cloud retrievals using OCO-2/GOSAT measurements

Sanghavi, S.; Lebsock, Matthew; Stephens, Graeme L.

doi:10.5194/amt-8-3601-2015

Cited by 12 publications

(7 citation statements)

References 59 publications

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“…A number of A‐band sensors are currently available, but the majority of them have wide instrument line shapes and so are unable to sample a wide range of effective oxygen absorption coefficients in the A‐band, which fundamentally limits their ability to extract information about photon path length and therefore cloud properties. OCO‐2 and GOSAT both offer much higher spectral resolution and while GOSAT retrieves more polarimetric information that is informative of clouds [ Sanghavi et al ., ], it has a much larger footprint than OCO‐2 (total area >20 times greater), meaning that cloud heterogeneity would be a greater issue. Additionally, we have been able to directly exploit OCO‐2's formation flying with Aqua and CALIPSO which provide cloud optical properties with their MODIS and CALIOP instruments, respectively.…”

Section: Discussionmentioning

confidence: 99%

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The OCO‐2 oxygen A‐band response to liquid marine cloud properties from CALIPSO and MODIS

et al. 2017

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Spectra of reflected sunlight in the oxygen A‐band contain information about cloud properties such as cloud top pressure, optical depth, and pressure thickness. Here we show, for the first time, that high‐spectral‐resolution A‐band Orbiting Carbon Observatory‐2 (OCO‐2) spectra respond largely as simulated to the optical properties of water clouds over ocean during November 2015 (N = 184,318) using input cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Cloud‐Aerosol Lidar with Orthogonal Polarization on Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). In A‐band continuum channels the standard deviation of simulated minus observed radiance is ±37%. Selecting horizontally homogeneous clouds to mitigate three‐dimensional cloud effects and collocation error with the other satellites, the standard deviation of the residuals is reduced to ±18%. Using a look‐up table developed from simulations, OCO‐2's estimated cloud top pressure for low clouds (Ptop > 680 hPa) has a standard deviation of ±61 hPa relative to CALIPSO retrievals, and bias is dependent on assumed cloud pressure thickness, with our smallest value being −5 hPa. Versus MODIS optical depth, the standard deviation is ±9.0 and the bias is −2.0, although these shrink for clouds of τ < 30. These values include collocation error between the different satellites, meaning that they place an upper bound on the OCO‐2 retrieval uncertainty. The theoretical precision limit from OCO‐2's instrumental uncertainty is shown to be ±2.4 hPa in above‐cloud path and ±0.2% in optical depth for a two‐channel retrieval. Options for retrieving cloud optical depth, cloud top pressure, and pressure thickness are discussed in the context of a formal OCO‐2 cloud property retrieval.

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Section: Discussionmentioning

confidence: 99%

“…Sanghavi et al . [] assess the effect of cloud properties on A‐band radiances by studying radiative transfer model output for theoretical cloud cases and their paper provides detailed theoretical explanations for the radiance responses expected and observed here.…”

Section: Introductionmentioning

confidence: 99%

The OCO‐2 oxygen A‐band response to liquid marine cloud properties from CALIPSO and MODIS

et al. 2017

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“…Simultaneous observation of two liner polarizations: TANSO-FTS is the only space-borne instrument that measures two linear polarizations with high spectral res-olution. This capability has the potential to provide improved retrieval of cloud and aerosol (Sanghavi et al, 2015).…”

Section: Summary and Discussionmentioning

confidence: 99%

Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space

et al. 2016

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Abstract. A data set containing more than 6 years (February 2009 to present) of radiance spectra for carbon dioxide (CO 2 ) and methane (CH 4 ) observations has been acquired by the Greenhouse gases Observing SATellite (GOSAT, available at http://data.gosat.nies.go.jp/ GosatUserInterfaceGateway/guig/GuigPage/open.do), nicknamed "Ibuki", Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS). This paper provides updates on the performance of the satellite and TANSO-FTS sensor and describes important changes to the data product, which has recently been made available to users. With these changes the typical accuracy of retrieved column-averaged dry air mole fractions of CO 2 and CH 4 (X CO 2 and X CH 4 , respectively) are 2 ppm or 0.5 % and 13 ppb or 0.7 %, respectively. Three major anomalies of the satellite system affecting TANSO-FTS are reported: a failure of one of the two solar paddles in May 2014, a switch to the secondary pointing system in January 2015, and most recently a cryocooler shutdown and restart in August 2015. The Level 1A (L1A) (raw interferogram) and the Level 1B (L1B) (radiance spectra) of version V201 described here have longterm uniform quality and provide consistent retrieval accuracy even after the satellite system anomalies. In addition, we discuss the unique observation abilities of GOSAT made possible by an agile pointing mechanism, which allows for optimization of global sampling patterns.

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“…The geometrical thickness can also be inferred from total and/or polarized reflectances measured in oxygen absorption bands (Sanghavi et al, 2015;Richardson et al, 2019) or by retrieving cloud base using lidar or using multi-angle observations (Böhm et al, 2019). When exploiting passive observations together with lidar, N d at cloud top can be robustly inferred as the ratio of in-cloud extinction (lidar) and extinction cross section (passive).…”

Section: Considering R E Rather Than N Dmentioning

confidence: 99%

Constraining the Twomey effect from satellite observations: Issues and perspectives

Quaas¹,

Arola²,

Cairns³

et al. 2020

Preprint

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Abstract. The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd,ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions which also comprises rapid adjustments. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd,ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large scale (hundreds of kilometres) ΔNd,ant remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and vertical wind and by droplet sink processes. These operate at scales on the order of 10s of metres at which only localized observations are available and at which no approach exists yet to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are three key uncertainties in determining ΔNd,ant, namely the quantification (i) of the cloud-active aerosol – the cloud condensation nuclei concentrations (CCN) at or above cloud base –, (ii) of Nd, as well as (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data. A fourth uncertainty, the anthropogenic perturbation to CCN concentrations, is also not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: In terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, the non-direct relation to the concentration of aerosols, the impossibility to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilizing colocated polarimeter and lidar instruments, ideally including high spectral resolution lidar capability at two wavelengths to maximize vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity, and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd – to – CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

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Sensitivity analysis of polarimetric O<sub>2</sub> A-band spectra for potential cloud retrievals using OCO-2/GOSAT measurements

Cited by 12 publications

References 59 publications

The OCO‐2 oxygen A‐band response to liquid marine cloud properties from CALIPSO and MODIS

The OCO‐2 oxygen A‐band response to liquid marine cloud properties from CALIPSO and MODIS

Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space

Constraining the Twomey effect from satellite observations: Issues and perspectives

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