Articles | Volume 17, issue 1
https://doi.org/10.5194/amt-17-247-2024
https://doi.org/10.5194/amt-17-247-2024
Research article
 | 
15 Jan 2024
Research article |  | 15 Jan 2024

Assessing sampling and retrieval errors of GPROF precipitation estimates over the Netherlands

Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet

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Cited articles

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Beekhuis, H. and Holleman, I.: Highlights of the digital-IF upgrade of the Dutch national radar network, online report, https://cdn.knmi.nl/system/data_center_publications/files/000/068/061/original/erad2008drup_0120.pdf?1495621011 (last access: 19 December 2023), 2008. a
Bogerd, L., Overeem, A., Leijnse, H., and Uijlenhoet, R.: A comprehensive five-year evaluation of IMERG late run precipitation estimates over the Netherlands, J. Hydrometeorol., 22, 1855–1868, https://doi.org/10.1175/JHM-D-21-0002.1, 2021. a, b
Casella, D., Panegrossi, G., Sanò, P., Milani, L., Petracca, M., and Dietrich, S.: A novel algorithm for detection of precipitation in tropical regions using PMW radiometers, Atmos. Meas. Tech., 8, 1217–1232, https://doi.org/10.5194/amt-8-1217-2015, 2015. a
Chang, N.-B. and Hong, Y.: Multiscale hydrologic remote sensing: perspectives and applications, CRC Press, ISBN 978-1-00-068727-9, 2012. a
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Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
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