scholarly journals Review on “ Retrieval of liquid water cloud properties from POLDER-3 measurements using a neural network ensemble approach” by Di Noia et al.

2019 ◽  
Author(s):  
Anonymous
2019 ◽  
Vol 12 (3) ◽  
pp. 1697-1716 ◽  
Author(s):  
Antonio Di Noia ◽  
Otto P. Hasekamp ◽  
Bastiaan van Diedenhoven ◽  
Zhibo Zhang

Abstract. This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument aboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization and has been applied to the processing of 1 year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) products show that the neural network algorithm has a low bias of around 2 in cloud optical thickness (COT) and between 1 and 2 µm in the cloud effective radius. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval, at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.


2018 ◽  
Author(s):  
Antonio Di Noia ◽  
Otto P. Hasekamp ◽  
Bastiaan van Diedenhoven ◽  
Zhibo Zhang

Abstract. This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument, on board the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization, and has been applied to the processing of one year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate resolution Imaging Spectroradiometer (MODIS) products show negative biases around −2 in retrieved cloud optical thicknesses (COTs) and between −1 and −2 μm in retrieved cloud effective radii. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.


2020 ◽  
Vol 237 ◽  
pp. 07005
Author(s):  
Cristofer Jimenez ◽  
Albert Ansmann ◽  
Ronny Engelmann ◽  
Patric Seifert ◽  
Robert Wiesen ◽  
...  

In this work we evaluate the possibilities to assess aerosol-cloud interactions in short time scales (2 min.) on an observational base. Retrievals of the cloud effective radius and number concentration in a liquid-water cloud by using the multiple scattering technique Dual-FOV Polarization lidar, together with the aerosol extinction coefficient in the boundary layer has shown a correspondence between the aerosol and cloud properties in the 6 hours case presented, obtaining a value of ACIN = 0.76 ± 0.29, which corroborates the potential of lidar observations to study the relation between aerosols and clouds on small scales.


2016 ◽  
Vol 142 (701) ◽  
pp. 3063-3081 ◽  
Author(s):  
Odran Sourdeval ◽  
Laurent C.‐Labonnote ◽  
Anthony J. Baran ◽  
Johannes Mülmenstädt ◽  
Gérard Brogniez

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