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First 530 results for ”M Optis”

1. Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products

   The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is the first mission that will provid...

   Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther | Journal: Atmospheric Measurement Techniques | Volume: 17 | Year: 2024 | First page: 261 | Last page: 276 | doi: 10.5194/amt-17-261-2024

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2. Validation of ash optical depth and layer height retrieved from passive satellite sensors using EARLINET and airborne lidar data: the case of the Eyjafjallajökull eruption

   The vulnerability of the European airspace to volcanic eruptions was brought to the attention of ...

   D Balis, ME Koukouli, N Siomos, S Dimopoulos, L Mona, G Pappalardo, F Marenco, L Clarisse, LJ Ventress, E Carboni, RG Grainger, P Wang, G Tilstra, RJ van der A, N Theys | Status: published | Journal: Atm. Chem. Phys. | Volume: 16 | Year: 2016 | First page: 5705 | Last page: 5720 | doi: 10.5194/acp-16-5705-2016

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3. Optimisation of Rotating, Range-Gated Fanbeam Scatterometer for Wind Retrieval, task 2a report, GMF and wind field definition, and wind retrieval

   This document describes some components that have been developed as part of the Rotating Fanbeam...

   J de Kloe | Year: 2003

   Publication

4. Observations and projections of visibility and aerosol optical thickness (1956-2100) in the Netherlands: impacts of time-varying aerosol composition and hygroscopicity

   Time series of visibility and aerosol optical thickness for the Netherlands have been constructed...

   Boers, Van Weele, Van Meijgaard, Savenije, Siebesma, Bosveld, Stammes | Status: published | Journal: Environmental Research Letters | Volume: 10 | Year: 2015 | doi: 10.1088/1748-9326/10/1/015003

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5. Joint retrieval of the aerosol fine mode fraction and optical depth using MODIS spectral reflectance over northern and eastern China: Artificial neural network method

   The Fine Mode Fraction (FMF) of atmospheric aerosol is very important for environment and climate...

   X Chen, G de Leeuw, A Arola, S Liu, Y Liu, K Zhang | Status: published | Journal: Remote Sens. Environ. | Volume: 247 | Year: 2020 | First page: 1 | Last page: 16 | doi: https://doi.org/10.1016/j.rse.2020.112006

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