Optimization of Radar Rainfall Estimation in Yogyakarta using a Time Correction Approach and DEM-Based Height Selection

Section: Research Article
Issue
Vol. 35 No. 3 (2026): Volume 35, Issue 3
Pages
95-105

Keywords:

Weather Radar, QPE, Phase locking, Marshall-Palmer, Optimal AGL

Abstract

The accuracy of quantitative precipitation estimation (QPE) using radar is often hindered by uncertainties in the vertical reflectivity profile and time discrepancies with surface measurements. This study aims to determine the most appropriate sampling height above ground level (AGL) and align the time lag between weather radar data and tipping bucket rain gauges. The methods used include rigorous filtering of multi-volume raw data to reduce bias, followed by retrieving converted reflectivity using the Marshall-Palmer Z–R relationship. Phase locking analysis shows that a 10-minute backward time shift (Time Shift -1) yields the highest correlation, reflecting the rainfall duration and sensor delay. Vertical evaluation reveals a compromise between accuracy and stability at an altitude of 600 m, where the lowest average RMSE (0.779 mm) was obtained. This altitude is optimal for low-lying areas, despite a high level of instability (standard deviation of 0.493) due to interference in mountainous areas. Meanwhile, an altitude of 1400 m demonstrates the best data stability (standard deviation of 0.185). This study recommends applying a -10-minute time correction and using data at altitudes above 1200 m as the optimum zone to reduce topographic distortion in regions with dynamic contours.

References

  1. P. Jordan, A. Seed, and G. Austin, “Sampling errors in radar estimates of rainfall,” Journal of Geophysical Research Atmospheres, vol. 105, no. D2, pp. 2247–2257, 2000, doi: 10.1029/1999JD900130.
  2. T. Y. Ojebisi, J. S. Ojo, E. O. Olurotimi, and M. O. Ajewole, “Computational Analysis of Raindrop Radar Reflectivity and Radar Cross Section across Various Frequency Bands,” 2025, pp. 123–130. doi: 10.2991/978-94-6463-644-4_12.
  3. M. Lakkham, “Determining the appropriate altitude to improve accuracy in rainfall estimation from radar reflectivity data,” in Journal of Physics: Conference Series, Institute of Physics Publishing, Oct. 2017. doi: 10.1088/1742-6596/901/1/012045.
  4. E. Ghaemi, M. Gabella, U. Foelsche, I. Sideris, and D. Nerini, “The effect of altitude on the uncertainty of radar-based precipitation estimates over Switzerland,” Int J Remote Sens, vol. 44, no. 8, pp. 2495–2517, 2023, doi: 10.1080/01431161.2023.2203339.
  5. F. Simanjuntak, I. Jamaluddin, T. H. Lin, H. A. W. Siahaan, and Y. N. Chen, “Rainfall Forecast Using Machine Learning with High Spatiotemporal Satellite Imagery Every 10 Minutes,” Remote Sens (Basel), vol. 14, no. 23, Dec. 2022, doi: 10.3390/rs14235950.
  6. V. Louf et al., “An integrated approach to weather radar calibration and monitoring using ground clutter and satellite comparisons,” J Atmos Ocean Technol, vol. 36, no. 1, pp. 17–39, Jan. 2019, doi: 10.1175/JTECH-D-18-0007.1.
  7. M. De Biase et al., “Integrated Rainfall Estimation Using Rain Gauges and Weather Radar: Implications for Rainfall-Induced Landslides,” Remote Sens (Basel), vol. 17, no. 21, Nov. 2025, doi: 10.3390/rs17213629.
  8. J. Zhang, C. Langston, and K. Howard, “Brightband Identification Based on Vertical Profiles of Reflectivity from the WSR-88D,” Journal of Atmospheric and Oceanic Technology - J ATMOS OCEAN TECHNOL, vol. 25, Oct. 2008, doi: 10.1175/2008JTECHA1039.1.
  9. P. Chen, L. Chen, Q. Wu, G. Wang, and P. Zhang, “Analysis of Satellite-Ground Radar Reflectivity Consistency: First Evaluation Results of FY-3G and GPM Precipitation Radar,” Geophys Res Lett, vol. 52, no. 13, Jul. 2025, doi: 10.1029/2025GL115785.
  10. Y. Gou and H. Chen, “Combining radar attenuation and partial beam blockage corrections for improved quantitative application,” J Hydrometeorol, vol. 22, no. 1, pp. 139–153, 2020, doi: 10.1175/JHM-D-20-0121.1.
  11. A. D. Ochou, E.-P. Zahiri, B. Bamba, and M. Koffi, “Understanding the Variability of Z-R Relationships Caused by Natural Variations in Raindrop Size Distributions (DSD): Implication of Drop Size and Number,” Atmospheric and Climate Sciences, vol. 01, no. 03, pp. 147–164, 2011, doi: 10.4236/acs.2011.13017.
  12. J. I. Song, S. S. Yum, S. H. Park, K. H. Kim, K. J. Park, and S. W. Joo, “Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations,” Journal of Geophysical Research: Atmospheres, vol. 126, no. 17, Sep. 2021, doi: 10.1029/2021JD034816.
  13. Z. Tan et al., “Climatology of Cloud Base Height Retrieved from Long-Term Geostationary Satellite Observations,” Remote Sens (Basel), vol. 15, no. 13, Jul. 2023, doi: 10.3390/rs15133424.
  14. S. Chumchean, A. Seed, and A. Sharma, “Correcting of real-time radar rainfall bias using a Kalman filtering approach,” J Hydrol (Amst), vol. 317, no. 1–2, pp. 123–137, Feb. 2006, doi: 10.1016/j.jhydrol.2005.05.013.
  15. Y. A. Oh, H. L. Kim, and M. K. Suk, “Clutter elimination algorithm for non-precipitation echo of radar data considering meteorological and observational properties in polarimetric measurements,” Remote Sens (Basel), vol. 12, no. 22, pp. 1–18, Nov. 2020, doi: 10.3390/rs12223790.
  16. World Meteorological Organization, State of the Global Climate 2022, WMO-No. 1257. Geneva: World Meteorological Organization, 2023.
  17. Pramil, Prateek, and Parashuram, “Band Pass Semi Adaptive Digital Filters for Radar Applications,” Int J Eng Adv Technol, vol. 9, no. 3, pp. 4184–4186, Feb. 2020, doi: 10.35940/ijeat.C5017.029320.
  18. C. Yoo, J. Yoon, J. Kim, and Y. Ro, “Evaluation of the gap filler radar as an implementation of the 1.5 km CAPPI data in Korea,” Meteorological Applications, vol. 23, no. 1, pp. 76–88, Jan. 2016, doi: 10.1002/met.1531.
  19. D. S. Permana, T. D. F. Hutapea, A. S. Praja, F. Fatkhuroyan, and L. F. Muzayanah, “Pengolahan Dan Pemulihan Data Radar Cuaca Menggunakan Wradlib Berbasis Python,” Jurnal Meteorologi dan Geofisika, vol. 17, no. 3, 2018, doi: 10.31172/jmg.v17i3.350.
  20. A. Overeem, H. DE VRIES, H. Al Sakka, R. Uijlenhoet, and H. Leijnse, “Rainfall-induced attenuation correction for two operational dual-polarization c-band radars in the Netherlands,” J Atmos Ocean Technol, vol. 38, no. 6, pp. 1125–1142, Jun. 2021, doi: 10.1175/JTECH-D-20-0113.1.
  21. M. Heistermann, S. Jacobi, and T. Pfaff, “Technical Note: An open source library for processing weather radar data (wradlib),” Hydrol Earth Syst Sci, vol. 17, no. 2, pp. 863–871, 2013, doi: 10.5194/hess-17-863-2013.
  22. J. S. Marshall and W. McK. Palmer, “The distribution of raindrops with size,” Journal of Meteorology, vol. 5, no. 4, pp. 165–166, 1948, doi: 10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2..
  23. N. A. Jamal, N. Mohamed Noor, I. A. M. Jafri, and G. J. Wibowo, “Assessment of Moving Average (MA) Method for Rainfall Prediction in Yogyakarta, Indonesia,” MDPI AG, Mar. 2025, p. 5. doi: 10.3390/eesp2025033005.
  24. Q. Yan, B. Zhang, Y. Jiang, Y. Liu, B. Yang, and H. Wang, “Quality control of hourly rain gauge data based on radar and satellite multi-source data,” Journal of Hydroinformatics, vol. 26, no. 5, pp. 1042–1058, May 2024, doi: 10.2166/hydro.2024.272.
  25. R. Villalobos-Herrera, S. Blenkinsop, S. B. Guerreiro, T. O’Hara, and H. J. Fowler, “Sub-hourly resolution quality control of rain-gauge data significantly improves regional sub-daily return level estimates,” Quarterly Journal of the Royal Meteorological Society, vol. 148, no. 748, pp. 3252–3271, Oct. 2022, doi: 10.1002/qj.4357.
  26. M. Ding, Z. Shen, R. Huang, Y. Liu, and H. Wu, “Cross-Validation Methods for Multisource Precipitation Datasets over the Sparse-Gauge Region: Applicability and Uncertainty”, doi: 10.1175/JHM-D-23.
  27. S. Ryu, J. J. Song, and G. W. Lee, “Radar–Rain Gauge Merging for High-Spatiotemporal-Resolution Rainfall Estimation Using Radial Basis Function Interpolation,” Remote Sens (Basel), vol. 17, no. 3, Feb. 2025, doi: 10.3390/rs17030530.
  28. N. S. Osman and W. Tahir, “Radar Quantitative Precipitation Estimation (QPE) Calibration Methods: A Systematic Literature Review,” Engineering, Technology and Applied Science Research, vol. 14, no. 5, pp. 16185–16192, Oct. 2024, doi: 10.48084/etasr.7534.
  29. K. Dzwonkowski, I. Winnicki, S. Pietrek, and J. Siewert, “Analysis of Precipitation Totals Based on Radar and Rain Gauge Data,” Remote Sens (Basel), vol. 17, no. 13, Jul. 2025, doi: 10.3390/rs17132157.

Authors

Ferdinandus Edwin Penalun

Indonesian Agency for Meteorology Climatology and Geophysics

Alfin Syarifuddin Syahab

Climatology Station of Yogyakarta, Indonesian Agency for Meteorology Climatology and Geophysics, Indonesia

Identifiers

DOI: 10.33899/jes.v35i3.60402

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[1]
“Optimization of Radar Rainfall Estimation in Yogyakarta using a Time Correction Approach and DEM-Based Height Selection ”, JES, vol. 35, no. 3, pp. 95–105, Jul. 2026, doi: 10.33899/jes.v35i3.60402.
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How to Cite

[1]
“Optimization of Radar Rainfall Estimation in Yogyakarta using a Time Correction Approach and DEM-Based Height Selection ”, JES, vol. 35, no. 3, pp. 95–105, Jul. 2026, doi: 10.33899/jes.v35i3.60402.