Thin-cirrus detection from Artificial Neural Network and IASI-NG-Reference-Cited by-同舟云学术

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Thin-cirrus detection from Artificial Neural Network and IASI-NG

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Ricciardelli Elisabetta¹,Paola Francesco Di¹,Cimini Domenico¹,Larosa Salvatore¹,Masiello Guido²,Mastro Pietro²,Serio Carmine²,Hultberg Tim³,August Thomas³,Romano Filomena¹

Affiliation:

1. Institute of Methodologies for Environmental Analysis,National Research Council of Italy,Tito (Potenza),Italy,85050

2. University of Basilicata,School of Engineering,Potenza,Italy,85100

3. European Organization for the Exploitation of Meteorological Satellites (EUMETSAT),Darmstadt,Germany,64297

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281635.pdf?arnumber=10281635

Reference21 articles.

1. Combined IASI-NG and MWS Observations for the Retrieval of Cloud Liquid and Ice Water Path: A Deep Learning Artificial Intelligence Approach

2. The σ-IASI code for the calculation of infrared atmospheric radiance and its derivatives

3. Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements

4. The ERA5 global reanalysis

5. A retrieval method for atmospheric composition from limb emission measurements

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