29 Sep 2017
Research article | 29 Sep 2017
Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks
Johan Strandgren et al.
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17 citations as recorded by crossref.
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- Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI J. Strandgren et al. 10.5194/amt-10-4317-2017
- Formation and radiative forcing of contrail cirrus B. Kärcher 10.1038/s41467-018-04068-0
- On estimation of cloudiness characteristics and parameters of DOAS retrieval from spectral measurements using a neural network O. Postylyakov et al. 10.1088/1755-1315/489/1/012031
- Air traffic and contrail changes over Europe during COVID-19: a model study U. Schumann et al. 10.5194/acp-21-7429-2021
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al. 10.5194/amt-13-2257-2020
- The behavior of high-CAPE (convective available potential energy) summer convection in large-domain large-eddy simulations with ICON H. Rybka et al. 10.5194/acp-21-4285-2021
- The Added Value of Large-eddy and Storm-resolving Models for Simulating Clouds and Precipitation B. STEVENS et al. 10.2151/jmsj.2020-021
- An update on global atmospheric ice estimates from satellite observations and reanalyses D. Duncan & P. Eriksson 10.5194/acp-18-11205-2018
- The retrieval of ice cloud parameters from multi-spectral satellite observations of reflectance using a modified XBAER algorithm L. Mei et al. 10.1016/j.rse.2018.06.007
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 1. Development D. Piontek et al. 10.3390/rs13163112
- A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems S. Pfreundschuh et al. 10.5194/amt-11-4627-2018
- Aviation Contrail Cirrus and Radiative Forcing Over Europe During 6 Months of COVID‐19 U. Schumann et al. 10.1029/2021GL092771
- Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network H. Kalesse-Los et al. 10.5194/amt-15-279-2022
- 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. 10.5194/nhess-21-2973-2021
- Artificial neural networks for cloud masking of Sentinel-2 ocean images with noise and sunglint V. Kristollari & V. Karathanassi 10.1080/01431161.2020.1714776
- An Overview of Neural Network Methods for Predicting Uncertainty in Atmospheric Remote Sensing A. Doicu et al. 10.3390/rs13245061
Latest update: 08 Aug 2022