Time-independent bias correction methods compared with gauge adjustment methods in improving radar-based precipitation estimates


Yousefi K. P., YILMAZ M. T., Öztürk K., YÜCEL İ., YILMAZ K. K.

Hydrological Sciences Journal, cilt.68, sa.14, ss.1963-1983, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 68 Sayı: 14
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/02626667.2023.2248108
  • Dergi Adı: Hydrological Sciences Journal
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, IBZ Online, PASCAL, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Compendex, Geobase, INSPEC, Pollution Abstracts, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1963-1983
  • Anahtar Kelimeler: bias correction, meteorological weather radar, quantitative precipitation estimation (QPE), radar-based precipitation, radar–gauge merging
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Quantitative precipitation estimates obtained by weather radars are prone to errors. Gauge-based observations are known to be complementary data for mitigating radar-based estimation. This study investigates, implements, and validates four gauge adjustment and four time-independent bias correction methods over all the operating radars of Turkey during the years 2014–2019. The objective is to investigate the performance of methods over large regions using long time series, where such implementations are rarely done. The results provide detailed information regarding the performance of these methods in different spatiotemporal scenarios. Gauge adjustment methods can mitigate the mean error and/or the dispersion of the error in the original radar data. On average, gauge adjustment methods reduce the mean error from −0.81 to −0.05 mm/h, the root mean squared error from 2.63 to 1.50 mm/h, and the correlation coefficient from 0.53 to 0.83. Time-independent methods can improve the mean error from −0.81 to −0.08 mm/h.