2024. december 14. szombat
IDŐJÁRÁS - angol nyelvű folyóirat

Vol. 128, No. 2 * Pages 143–286 * April - June 2024


Journal of HungaroMet Hungarian Meteorological Service

Special issue:
11th Seminar for Homogenization and Quality Control in Climatological Databases and 6th Interpolation Conference jointly organized with the 14th EUMETNET Data Management Workshop

Guest Editor: Mónika Lakatos

letöltés [pdf: 22872 KB]
Analysis of daily and hourly precipitation interpolation supplemented with radar background: Insights from case studies
Kinga Bokros, Beatrix Izsák, and Zita Bihari
DOI:10.28974/idojaras.2024.2.8 (pp. 267–286)
 PDF (5425 KB)   |   Abstract

This study concerns the interpolation of daily and hourly precipitation data in regions where small but intense thunderstorms, such as supercells, have occurred, and which, due to their size, often evade conventional meteorological stations. Consequently, relying solely on these measurements for interpolation can introduce errors and yield incomplete representations. To mitigate these issues, this research incorporates radar background information. The study selects days marked by significant precipitation during summer season and employs the Meteorological Interpolation based on Surface Homogenized Data (MISH) method for interpolation, both with and without radar-derived background data. Furthermore, our research also investigates the adaptability of the MISH method in handling radar anomalies, which encompass errors, missing data, and spurious measurements resulting from unintended radar reflections. Additionally, it examines whether the precipitation measured by radar can be used for climatic purposes on its own (without traditional measurements). Statistical techniques are employed to assess the improvement in interpolation quality with the inclusion of radar data and to quantify the relationship between interpolations with and without supplementary radar information. The study underscores the critical role of combining measurement data and radar products in the interpolation framework. This approach has implications for societal and agricultural sectors and offers potential benefits for hazard forecasting accuracy.


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