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First 1372 results for ”A. Denkema”

1. Estimating Single-Epoch Integrated Atmospheric Refractivity from InSAR for Assimilation in Numerical Weather Models

   Numerical weather prediction (NWP) models are used to predict the weather based on current observ...

   Gert Mulder, Freek J. van Leijen, Jan Barkmeijer, Siebren de Haan, and Ramon F. Hanssen | Journal: IEEE Transactions on Geoscience and Remote Sensing | Volume: 60 | Year: 2022 | doi: 10.1109/TGRS.2022.3177041

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2. Observations from Personal Weather Stations—EUMETNET Interests and Experience

   The number of people owning a private weather station (PWS) and sharing their meteorological meas...

   Claudia Hahn, Irene Garcia-Marti, Jacqueline Sugier, Fiona Emsley, Anne-Lise Beaulant, Louise Oram, Eva Strandberg, Elisa Lindgren, Martyn Sunter, Franziska Ziska | Journal: MDPI CLimate | Volume: 10 | Year: 2022 | doi: https://doi.org/10.3390/cli10120192

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3. Study of the strongest dust storm occurred in Uzbekistan in November 2021

   We studied and reconstructed a severe Central Asian dust storm of November 4, 2021, through high-...

   B. E. Nishonov, B. M. Kholmatjanov, L. D. Labzovskii, N. Rakhmatova, L. Shardakova, E. I. Abdulakhatov, D. U. Yarashev, T. Khujanazarov, D. A. Belikov | Journal: Scientific Reports | Year: 2023 | doi: https://doi.org/10.1038/s41598-023-42256-1

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4. Validation of Aura-OMI QA4ECV NO2 climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

   The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and trop...

   Compernolle, S., Verhoelst, T., Pinardi, G., Granville, J., Hubert, D., Keppens, A., Niemeijer, S., Rino, B., Bais, A., Beirle, S., Boersma, K.F., Burrows, J.P., De Smedt, I., Eskes, H., Goutail, F., Hendrick, F., Lorente, A., Pazmino, A., Piters, A., Peters, E., Pommereau, J.-P., Remmers, J., Richter, A., van Geffen, J., Van Roozendael, M., Wagner, T. and Lambert, J.-C | Journal: Atmospheric Chemistry and Physics | Volume: 20 | Year: 2020 | doi: https://doi.org/10.5194/acp-20-8017-2020

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5. Improvements in Ku-band scatterometer wind ambiguity removal using ASCAT-based empirical background error correlations

   Wind scatterometry is an established technique for accurately measuring wind vectors over the wor...

   Jur Vogelzang, Ad Stoffelen | Journal: Quarterly Journal of the Royal Meteorological Society | Volume: 144 | Year: 2018 | doi: https://doi.org/10.1002/qj.3349

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