Articles | Volume 7, issue 10
https://doi.org/10.5194/amt-7-3233-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-3233-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Oct 2014
Research article |
| 01 Oct 2014
Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing
S. Kox
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
now at: European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany
L. Bugliaro
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
A. Ostler
Karlsruher Institut für Technologie, Institut für Meteorologie und Klimaforschung (IMK-IFU), Garmisch-Partenkirchen, Germany
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Cited
51 citations as recorded by crossref.
- VIIRS Edition 1 Cloud Properties for CERES, Part 2: Evaluation with CALIPSO C. Yost et al.
- 25-Year analysis of tropical cirrus clouds: insights from ground and space-based LIDAR observations P. Mol et al.
- Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm D. Miller et al.
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 1. Development D. Piontek et al.
- Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts B. Gasparini et al.
- A Multi-Stage Deep Learning Framework for Multi-Source Cloud Top Height Retrieval from FY-4A/AGRI Data Y. Cheng et al.
- Particle reflectivity and movements in cirrus clouds over Beijing from four years of Ka radar measurements J. Huo et al.
- Seasonal distribution of cirrus cloud characteristics and their rapid descent from polarization lidar measurements at the west coast of India M. Aswini et al.
- Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks J. Strandgren et al.
- An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions M. Plu et al.
- Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network S. Sun-Mack et al.
- Cirrus Clouds A. Heymsfield et al.
- GVCCS: a dataset for contrail identification and tracking on visible whole sky camera sequences G. Jarry et al.
- Development of neural network retrievals of liquid cloud properties from multi-angle polarimetric observations M. Segal-Rozenhaimer et al.
- A Cloud Detection Neural Network Approach for the Next Generation Microwave Sounder Aboard EPS MetOp-SG A1 S. Larosa et al.
- Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method P. Minnis et al.
- Evaluation of Visible Infrared Imaging Radiometer Suite (VIIRS) neural network cloud detection against current operational cloud masks C. White et al.
- How Well Can Persistent Contrails Be Predicted? K. Gierens et al.
- Observing long-lived longwave contrail forcing A. Sonabend-W et al.
- Algorithm for Interpreting Light Backscattering Matrices of Cirrus Clouds for the Retrieval of Their Microphysical Parameters V. Shishko et al.
- How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties J. Mayer et al.
- Constraining Ice Water Content of Thin Antarctic Cirrus Clouds Using Ground-Based Lidar and Satellite Data S. Alexander & A. Klekociuk
- Properties of ice cloud over Beijing from surface Ka-band radar observations during 2014–2017 J. Huo et al.
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al.
- Retrieval of Vertical Profile of Cirrus Cloud Effective Particle Size Using Reflected Line Spectra in 1.38 μm Band Y. Gu et al.
- Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants T. Sirch et al.
- Bayesian cloud-top phase determination for Meteosat Second Generation J. Mayer et al.
- Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking A. Taravat et al.
- CloudSat and CALIPSO within the A-Train: Ten Years of Actively Observing the Earth System G. Stephens et al.
- Neural network cloud top pressure and height for MODIS N. Håkansson et al.
- 基于神经网络反演中国南海海域透明卷云参数 陆. Lu Wenqiang et al.
- Theoretical assessment of measurement conditions for a near-infrared polarimetric instrument adapted for stratospheric aerosols observation Y. Yukhymchuk et al.
- A global record of single-layered ice cloud properties and associated radiative heating rate profiles from an A-Train perspective E. Dolinar et al.
- Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al.
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 2. Validation D. Piontek et al.
- Contrail altitude estimation using GOES-16 ABI data and deep learning V. Meijer et al.
- An extended lidar-based cirrus cloud retrieval scheme: first application over an Arctic site K. Nakoudi et al.
- Deep-Learning-Based Daytime COT Retrieval and Prediction Method Using FY4A AGRI Data F. Xu et al.
- Ice water path retrievals from Meteosat-9 using quantile regression neural networks A. Amell et al.
- Atmospheric Correction Above Clouds for FY-4A AGRI Based on RTTOV Y. Wang et al.
- Remote Sensing Retrieval of Cloud Top Height Using Neural Networks and Data from Cloud-Aerosol Lidar with Orthogonal Polarization Y. Cheng et al.
- VADUGS: a neural network for the remote sensing of volcanic ash with MSG/SEVIRI trained with synthetic thermal satellite observations simulated with a radiative transfer model L. Bugliaro et al.
- Cloud identification and property retrieval from Himawari-8 infrared measurements via a deep neural network X. Wang et al.
- ML-CIRRUS: The Airborne Experiment on Natural Cirrus and Contrail Cirrus with the High-Altitude Long-Range Research Aircraft HALO C. Voigt et al.
- Retrieval of Cloud Optical Thickness During Nighttime from FY-4B AGRI Using a Convolutional Neural Network D. Xia et al.
- CERES MODIS Cloud Product Retrievals for Edition 4—Part II: Comparisons to CloudSat and CALIPSO C. Yost et al.
- Neural network radiative transfer for imaging spectroscopy B. Bue et al.
- Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI J. Strandgren et al.
- Cirrus cloud shape detection by tomographic extinction retrievals from infrared limb emission sounder measurements J. Ungermann et al.
- Probing the Explainability of Neural Network Cloud-Top Pressure Models for LEO and GEO Imagers C. White et al.
- Estimation of cloud optical thickness, single scattering albedo and effective droplet radius using a shortwave radiative closure study in Payerne C. Aebi et al.
51 citations as recorded by crossref.
- VIIRS Edition 1 Cloud Properties for CERES, Part 2: Evaluation with CALIPSO C. Yost et al.
- 25-Year analysis of tropical cirrus clouds: insights from ground and space-based LIDAR observations P. Mol et al.
- Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm D. Miller et al.
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 1. Development D. Piontek et al.
- Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts B. Gasparini et al.
- A Multi-Stage Deep Learning Framework for Multi-Source Cloud Top Height Retrieval from FY-4A/AGRI Data Y. Cheng et al.
- Particle reflectivity and movements in cirrus clouds over Beijing from four years of Ka radar measurements J. Huo et al.
- Seasonal distribution of cirrus cloud characteristics and their rapid descent from polarization lidar measurements at the west coast of India M. Aswini et al.
- Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks J. Strandgren et al.
- An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions M. Plu et al.
- Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network S. Sun-Mack et al.
- Cirrus Clouds A. Heymsfield et al.
- GVCCS: a dataset for contrail identification and tracking on visible whole sky camera sequences G. Jarry et al.
- Development of neural network retrievals of liquid cloud properties from multi-angle polarimetric observations M. Segal-Rozenhaimer et al.
- A Cloud Detection Neural Network Approach for the Next Generation Microwave Sounder Aboard EPS MetOp-SG A1 S. Larosa et al.
- Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method P. Minnis et al.
- Evaluation of Visible Infrared Imaging Radiometer Suite (VIIRS) neural network cloud detection against current operational cloud masks C. White et al.
- How Well Can Persistent Contrails Be Predicted? K. Gierens et al.
- Observing long-lived longwave contrail forcing A. Sonabend-W et al.
- Algorithm for Interpreting Light Backscattering Matrices of Cirrus Clouds for the Retrieval of Their Microphysical Parameters V. Shishko et al.
- How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties J. Mayer et al.
- Constraining Ice Water Content of Thin Antarctic Cirrus Clouds Using Ground-Based Lidar and Satellite Data S. Alexander & A. Klekociuk
- Properties of ice cloud over Beijing from surface Ka-band radar observations during 2014–2017 J. Huo et al.
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al.
- Retrieval of Vertical Profile of Cirrus Cloud Effective Particle Size Using Reflected Line Spectra in 1.38 μm Band Y. Gu et al.
- Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants T. Sirch et al.
- Bayesian cloud-top phase determination for Meteosat Second Generation J. Mayer et al.
- Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking A. Taravat et al.
- CloudSat and CALIPSO within the A-Train: Ten Years of Actively Observing the Earth System G. Stephens et al.
- Neural network cloud top pressure and height for MODIS N. Håkansson et al.
- 基于神经网络反演中国南海海域透明卷云参数 陆. Lu Wenqiang et al.
- Theoretical assessment of measurement conditions for a near-infrared polarimetric instrument adapted for stratospheric aerosols observation Y. Yukhymchuk et al.
- A global record of single-layered ice cloud properties and associated radiative heating rate profiles from an A-Train perspective E. Dolinar et al.
- Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al.
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 2. Validation D. Piontek et al.
- Contrail altitude estimation using GOES-16 ABI data and deep learning V. Meijer et al.
- An extended lidar-based cirrus cloud retrieval scheme: first application over an Arctic site K. Nakoudi et al.
- Deep-Learning-Based Daytime COT Retrieval and Prediction Method Using FY4A AGRI Data F. Xu et al.
- Ice water path retrievals from Meteosat-9 using quantile regression neural networks A. Amell et al.
- Atmospheric Correction Above Clouds for FY-4A AGRI Based on RTTOV Y. Wang et al.
- Remote Sensing Retrieval of Cloud Top Height Using Neural Networks and Data from Cloud-Aerosol Lidar with Orthogonal Polarization Y. Cheng et al.
- VADUGS: a neural network for the remote sensing of volcanic ash with MSG/SEVIRI trained with synthetic thermal satellite observations simulated with a radiative transfer model L. Bugliaro et al.
- Cloud identification and property retrieval from Himawari-8 infrared measurements via a deep neural network X. Wang et al.
- ML-CIRRUS: The Airborne Experiment on Natural Cirrus and Contrail Cirrus with the High-Altitude Long-Range Research Aircraft HALO C. Voigt et al.
- Retrieval of Cloud Optical Thickness During Nighttime from FY-4B AGRI Using a Convolutional Neural Network D. Xia et al.
- CERES MODIS Cloud Product Retrievals for Edition 4—Part II: Comparisons to CloudSat and CALIPSO C. Yost et al.
- Neural network radiative transfer for imaging spectroscopy B. Bue et al.
- Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI J. Strandgren et al.
- Cirrus cloud shape detection by tomographic extinction retrievals from infrared limb emission sounder measurements J. Ungermann et al.
- Probing the Explainability of Neural Network Cloud-Top Pressure Models for LEO and GEO Imagers C. White et al.
- Estimation of cloud optical thickness, single scattering albedo and effective droplet radius using a shortwave radiative closure study in Payerne C. Aebi et al.
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