Articles | Volume 16, issue 17
https://doi.org/10.5194/amt-16-4067-2023
https://doi.org/10.5194/amt-16-4067-2023
Research article
 | 
11 Sep 2023
Research article |  | 11 Sep 2023

Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)

Anna Jurczyk, Katarzyna Ośródka, Jan Szturc, Magdalena Pasierb, and Agnieszka Kurcz

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Cited articles

Bonaccorso, B., Brigandì, G., and Aronica, G. T.: Regional sub-hourly extreme rainfall estimates in Sicily under a scale invariance framework, Water Resour. Manage., 34, 4363–4380, https://doi.org/10.1007/s11269-020-02667-5, 2020. 
Burcea, S., Cică, R., and Bojariu, R.: Radar-derived convective storms' climatology for the Prut River basin: 2003–2017, Nat. Hazards Earth Syst. Sci., 19, 1305–1318, https://doi.org/10.5194/nhess-19-1305-2019, 2019. 
Chan, S. C., Kendon, E. J., Roberts, N. M., Fowler, H. J., and Blenkinsop, S.: The characteristics of summer sub-hourly rainfall over the southern UK in a high-resolution convective permitting model, Environ. Res. Lett., 11, 094024, https://doi.org/10.1088/1748-9326/11/9/094024, 2016. 
Fabry, F., Meunier, V., Treserras, B. P., Cournoyer, A., and Nelson, B.: On the Climatological Use of Radar Data Mosaics: Possibilities and Challenges, B. Am. Meteorol. Soc., 98, 2135–2148, https://doi.org/10.1175/BAMS-D-15-00256.1, 2017. 
Hamidi, A., Devineni, N., Booth, J. F., Hosten, A., Ferraro, R. R., and Khanbilvardi, R.: Classifying urban rainfall extremes using weather radar data: An application to the greater New York area, J. Hydrometeorol., 18, 611–623, https://doi.org/10.1175/JHM-D-16-0193.1, 2017. 
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Short summary
A data-processing algorithm, RainGRS Clim, has been developed to work on precipitation accumulations such as daily or monthly totals. The algorithm makes the most of additional opportunities: access to high-quality data that are not operationally available and greater efficiency of the algorithms for data quality control and merging for longer accumulations. Monthly accumulations estimated by RainGRS Clim were found to be significantly more reliable than accumulations generated operationally.
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