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First 1958 results for ” Chabrillat”

  1. Generalization of Ku-Band False-Alarm Reduction Method and Application to Cscat

    Space-borne scatterometer observations are well-known ocean surface wind remote sensing instrumen...

    Xingou Xu, Ad Stoffelen, Wenming Lin, Xiaolong Dong | Journal: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium | Year: 2020 | doi: https://doi.org/10.1109/IGARSS39084.2020.9323921

    Publication

  2. Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers

    Retrievals of cloud properties from geostationary satellite sensors offer extensive spatial and t...

    Benas, N., Meirink, J. F., Stengel, M., and Stammes, P | Journal: Atmospheric Measurement Techniques | Year: 2019 | doi: https://doi.org/10.5194/amt-12-2863-2019

    Publication

  3. The MSG-SEVIRI-based cloud property data record CLAAS-2

    Clouds play a central role in the Earth's atmosphere, and satellite observations are crucial for ...

    Benas, N., Finkensieper, S., Stengel, M., van Zadelhoff, G.-J., Hanschmann, T., Hollmann, R., and Meirink, J. F | Journal: Earth System Science Data | Year: 2017 | doi: https://doi.org/10.5194/essd-9-415-2017

    Publication

  4. Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2

    Quantification and control of NOx and CO2 emissions are essential across the world to limit adver...

    Zhang, Q., Boersma, K. F., Zhao, B., Eskes, H., Chen, C., Zheng, H., and Zhang, X. | Journal: Atmos Chem Phys | Volume: 23 | Year: 2023 | First page: 551 | Last page: 563 | doi: https://doi.org/10.5194/acp-23-551-2023

    Publication

  5. Bayesian Algorithm for Rain Detection in Ku-Band Scatterometer Data

    Ku-band scatterometers are sensitive to rain effects due to their centimeter-scale radar waveleng...

    Zhao, K., A. Stoffelen, J. Verspeek, A. Verhoef and C. Zhao | Journal: IEEE Transactions on Geoscience and Remote Sensing | Volume: 61 | Year: 2023 | doi: 10.1109/TGRS.2023.3264245

    Publication