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First 1335 results for ” Martin de Graaf”

1. Sensitivity study of the residue method for the detection of aerosols from space-borne sensors

   In this study the residue method for the detection of absorbing aerosols from space-borne sensors...

   M de Graaf | Year: 2002 | Pages: 24

   Publication

2. First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates

   Constraint of the vertical distribution of aerosol particles is crucial for the study of aerosol ...

   Xi Chen, Jun Wang, Xiaoguang Xu, Meng Zhou, Huanxin Zhang, Lorena Castro Garcia, Peter R. Colarco, Scott J. Janz, John Yorks, Matthew McGill, Jeffrey S. Reid, Martin de Graaf, Shobha Kondragunta | Journal: Remote Sensing of Environment | Volume: 265 | Year: 2021 | First page: 1 | Last page: 18 | doi: 10.1016/j.rse.2021.112674

   Publication

3. Weather, seasonal and decadal forecasting: initial requirements

   This document contains the initial requirements from the Weather, seasonal and decadal forecastin...

   M Martin, A Sterl | Year: 2013

   Publication

4. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison

   This paper is the second part of companion papers describing the development of GRASP approach fo...

   Cheng Chen, Pavel Litvinov, Oleg Dubovik, Lukas Bindreiter, Christian Matar, David Fuertes, Anton Lopatin, Tatyana Lapyonok, Verena Lanzinger, Andreas Hangler, Michael Aspetsberger, Martin de Graaf, Lieuwe Gijsbert Tilstra, Piet Stammes, Alexandru Dandocsi, Daniele Gasbarra, Elody Fluck, Claus Zehner, Christian Retscher | Journal: Remote Sensing of Environment | Volume: 313 | Year: 2024 | First page: 114374 | doi: https://doi.org/10.1016/j.rse.2024.114374

   Publication

5. Weather, seasonal and decadal forecasting: synthesis of past OSE/OSSE activities and OSE/OSSE plans

   The planned experiments for the work package on seasonal to decadal forecasting within E-AIMS are...

   RR King, M Martin, A Sterl | Year: 2013

   Publication