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First 1530 results for ” Georg Engelhard”

  1. Support vector machine tropical wind speed retrieval in the presence of rain for Ku-band wind scatterometry

    Wind retrieval parameters, i.e. quality indicators and the two-dimensional variational ambiguity ...

    Xingou Xu, Ad Stoffelen | Journal: Atmospheric Measurement Techniques | Volume: 14 | Year: 2021 | doi: https://doi.org/10.5194/amt-14-7435-2021

    Publication

  2. Comparison of Ocean Surface Rain Rates From the Global Precipitation Mission and the Meteosat Second-Generation Satellite for Wind Scatterometer Quality Control

    Ocean surface rain rate information is crucial for quality control (QC) research in wind scattero...

    Xu, X., Stoffelen, A., and Meirink, J. F | Journal: IEEE Journal of Selected Topics in Applied Earth Observations, Remote Sensing | Volume: 13 | Year: 2020 | doi: https://doi.org/10.1109/JSTARS.2020.2995178

    Publication

  3. Validation of New Sea Surface Wind Products From Scatterometers Onboard the HY-2B and MetOp-C Satellites

    The new Ku-band scatterometer (HSCAT-B) onboard the HY-2B satellite was launched on October 25, 2...

    Zhixiong Wang, Ad Stoffelen, Juhong Zou, Wenming Lin, Anton Verhoef, Yi Zhang, Yijun He, Mingsen Lin | Journal: IEEE Transactions on Geoscience and Remote Sensing | Volume: 58 | Year: 2020 | doi: https://doi.org/10.1109/TGRS.2019.2963690

    Publication

  4. Improved Rain Screening for Ku-Band Wind Scatterometry

    Spaceborne scatterometers for ocean surface winds usually operate in Ku- or C-band. Rather strict...

    Xingou Xu, Ad Stoffelen | Journal: IEEE Transactions on Geoscience and Remote sensing | Volume: 58 | Year: 2019 | doi: https://doi.org/10.1109/TGRS.2019.2951726

    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