A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight

Sun, Wenbo; Baize, Rosemary R.; Videen, Gorden; Hu, Yongxiang; Fu, Qiang

doi:10.5194/acp-15-11909-2015

Cited by 18 publications

(12 citation statements)

References 35 publications

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“…In summary, our modeling results show that the DOP of scattered sunlight can be used to detect aerosols. Figure 2 also shows that the AOLP of scattered light from nonspherical dust particles are very different from that of light scattered by clouds as reported in Sun et al (2014;2015). This can be used to differentiate aerosols from clouds, regardless of the ocean surface conditions.…”

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confidence: 76%

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A simple method for retrieval of dust aerosol optical depth with polarized reflectance over oceans

Sun

Baize

et al. 2019

Preprint

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<p><strong>Abstract.</strong> Our previous study shows that the angle of linear polarization (AOLP) of solar radiation that is scattered from clouds at near-backscatter angles can be used to detect super-thin cirrus clouds over oceans. Such clouds are too thin to be sensed using any current passive satellite instruments that only measure light's total intensity, because of the uncertainty in surface reflection. In this report, we show that with a method similar to the super-thin clouds detection algorithm, dust aerosols may also be detected and differentiated from clouds. We also show that the degree of polarization of reflected light can be used for retrieving the optical depth of dust aerosols in the neighborhood of the backscatter angle, regardless of the reflecting surface conditions. This is a simple and robust algorithm, which could be used to survey dust aerosols over midlatitude and tropical oceans.</p>

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confidence: 76%

“…We can see that at near-backscatter angles, AOLPs from the model and satellite data are significantly different. The PARASOL results have a glory pattern at near-backscatter angles that indicates transparent cloud particles such as water droplets or ice crystals (Sun et al 2014;2015). This means the PARASOL OC2 aerosol product has clouds contamination.…”

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confidence: 99%

A simple method for retrieval of dust aerosol optical depth with polarized reflectance over oceans

Sun

Baize

et al. 2019

Preprint

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“…CALIOP, which is a lidar providing high‐resolution vertical profiles of clouds, was used to detect and classify the cloud properties based on nadir viewing [ Vaughan et al ., , ]. Especially, CALIOP can detect superthin clouds within small parts of the atmosphere, whereas passive satellite instruments cannot [ Sun et al ., ]. To reflect the observation differences between GOCI and CALIPSO, a parallax correction, which can reduce the positional errors between two instruments, was applied to the CALIPSO data; the correction is discussed in more detail in section 2.5.…”

Section: Methodsmentioning

confidence: 99%

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model‐based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

et al. 2017

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In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model‐based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle‐dependent geostationary sensor geometry. For quantitative validation, Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).

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“…Although recent reports describe the fact that optically very thin clouds are detectable with the data from passive sensors (e.g., Sun et al, 2014Sun et al, , 2015, the most accurate measurements of clouds and aerosols are obtained using an active sensor, light detection and ranging (lidar), which emits a visible or near-infrared laser beam and which subsequently receives their back-scattered components. Its detection accuracy is higher than that of passive sensors.…”

Section: Data Sets and Radiative Transfer Modelsmentioning

confidence: 99%

A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data

et al. 2016

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Abstract. An algorithm based on CO 2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. Selection of the reconstructed channel pairs was optimized for several atmospheric profile patterns using simultaneous studies assuming a cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). Results were compared with those obtained from the space-borne lidar instrument on-board CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement, except for some cases, and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect lowlevel clouds with cloud top heights as low as approximately 1.5 km.

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A method to retrieve super-thin cloud optical depth over ocean background with polarized sunlight

Cited by 18 publications

References 35 publications

A simple method for retrieval of dust aerosol optical depth with polarized reflectance over oceans

A simple method for retrieval of dust aerosol optical depth with polarized reflectance over oceans

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model‐based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data

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