single-dr.php

JDR Vol.16 No.4 pp. 786-793
(2021)
doi: 10.20965/jdr.2021.p0786

Paper:

A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan

Yoshiaki Hayashi*,†, Taichi Tebakari**, and Akihiro Hashimoto*

*Department of Civil Engineering, Fukuoka University
8-19-1 Nanakuma, Jonan-ku, Fukuoka 814-0180, Japan

Corresponding author

**Department of Environment and Civil Engineering, Graduate School of Engineering, Toyama Prefectural University, Toyama, Japan

Received:
October 23, 2020
Accepted:
March 24, 2021
Published:
June 1, 2021
Keywords:
observation characteristics, C-band radar, X-band MP radar, GPM/GMI, GSMaP
Abstract

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.

Cite this article as:
Y. Hayashi, T. Tebakari, and A. Hashimoto, “A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan,” J. Disaster Res., Vol.16 No.4, pp. 786-793, 2021.
Data files:
References
  1. [1] T. Kubota, S. Shige, H. Hashizume, K. Aonashi, N. Takahashi, S. Seto, M. Hirose, Y. N. Takayabu, T. Ushio, K. Nakagawa, K. Iwanami, M. Kachi, and K. Okamoto, “Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: production and validation,” IEEE Trans. on Geoscience and Remote Sensing, Vol.45, No.7, pp. 2259-2275, 2007.
  2. [2] T. Ushio, K. Sasashige, T. Kubota, S. Shige, K. Okamoto, K. Aonashi, T. Inoue, N. Takahashi, T. Iguchi, M. Kachi, R. Oki, T. Morimoto, and Z. Kawasaki, “A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data,” J. of the Meteorological Society of Japan. Ser. II, Vol.87A, pp. 137-151, 2009.
  3. [3] T. Kubota, T. Ushio, S. Shige, S. Kida, M. Kachi, and K. Okamoto, “Verification of high-resolution satellite-based rainfall estimates around Japan using a gauge-calibrated ground-radar dataset,” J. of the Meteorological Society of Japan. Ser. II, Vol.87A, pp. 203-222, 2009.
  4. [4] K. Aonashi, J. Awaka, M. Hirose, T. Kozu, T. Kubota, G. Liu, S. Shige, S. Kida, S. Seto, N. Takahashi, and Y. N. Takayabu, “GSMaP passive microwave precipitation retrieval algorithm: algorithm description and validation,” J. of the Meteorological Society of Japan. Ser. II, Vol.87A, pp. 119-136, 2009.
  5. [5] K. P. N. Sakolnakhon, “Comparison the estimation rainfall from Global Satellite Mapping of Precipitation (GSMaP) to ground-based precipitation data over Thailand,” 1st Joint Project Team Meeting for Sentinel Asia STEP3 (JPTM2013), 2013.
  6. [6] S. Seto, T. Iguchi, N. Utsumi, M. Kiguchi, and T. Oki, “Evaluation of extreme rain estimates in the TRMM/PR standard product version 7 using high-temporal-resolution rain gauge datasets over Japan,” Scientific Online Letters on the Atmosphere, Vol.9, pp. 98-101, 2013.
  7. [7] M. K. Yamamoto and S. Shige, “Implementation of an orographic/nonorographic rainfall classification scheme in the GSMaP algorithm for microwave radiometers,” Atmospheric Research, Vol.163, pp. 36-47, 2013.
  8. [8] T. Mega, T. Ushio, T. Kubota, M. Kachi, K. Aonashi, and S. Shige, “Gauge adjusted global satellite mapping of precipitation (GSMaP_Gauge),” 2014 31th URSI General Assembly and Scientific Symp. (USRI GASS), pp.1-4, 2014.
  9. [9] K. Takido, O. C. Saavedra, M. Ryo, K. Tanuma, T. Ushio, and T. Kubota, “Spatiotemporal evaluation of the gauge-adjusted Global Satellite Mapping of Precipitation at the basin scale,” J. of the Meteorological Society of Japan. Ser. II, Vol.94, No.2, pp. 185-195, 2016.
  10. [10] M. Yamaji, T. Kubota, and R. Oki, “Observing system simulation experiment on the accuracy of Global Mapping of Precipitation (GSMaP) by future small precipitation radar constellation,” 2019 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS2019), pp. 7594-7597, 2019.
  11. [11] H. Chen, B. Yong, Y. Shen, J. Liu, Y. Hong, and J. Zhang, “Comparison analysis of six purely satellite-derived global precipitation estimates,” J. of Hydrology, Vol.581, 124356, 2020.
  12. [12] F. Satgé, D. Defrance, B. Sultan, M.-P. Bonnet, F. Seyler, N. Rouché, F. Pierron, and J.-E. Paturel, “Evaluation of 23 gridded precipitation datasets across West Africa,” J. of Hydrology, Vol.581, 124412, 2020.
  13. [13] Y. Tian, C. D. Peters-Lidard, R. F. Adler, T. Kubota, and T. Ushio, “Evaluation of GSMaP precipitation estimates over the Contiguous United States,” J. of Hydrometeorology, Vol.11, No.2, pp. 556-574, 2010.
  14. [14] M. Shrestha, K. Takara, T. Kubota, and S. Bajracharya, “Verification of GSMaP rainfall estimates over the Central Himalayas,” Annual J. of Hydraulic Engineering, Vol.67, No.4, pp. I_37-I_42, 2011 (in Japanese with English abstract).
  15. [15] G. Ozawa, H. Inomata, Y. Shiraishi, and K. Fukami, “Applicability of GSMaP correction method to typhoon “Morakot” in Taiwan,” Annual J. of Hydraulic Engineering, Vol.67, No.4, pp. I_445-I_450, 2011 (in Japanese with English abstract).
  16. [16] S. Seto, T. Tsunekawa, and T. Oki, “A new rain detection method to complement high-resolution globe precipitation products,” Hydrological Research Letters, Vol.6, pp. 82-86, 2012.
  17. [17] T. Ngo-Duc, J. Matsumoto, H. Kamimera, and H.-H. Bui, “Monthly adjustment of Global Satellite Mapping of Precipitation (GSMaP) data over the VuGia-ThuBon River basin in Central Vietnam using an artificial neural network,” Hydrological Research Letters, Vol.7, No.4, pp. 85-90, 2013.
  18. [18] W. Veerakachen, M. Raksapatcharawong, and S. Seto, “Performance evaluation of Global Satellite of Precipitation products over the Chaophraya River basin, Thailand,” Hydrological Research Letters, Vol.8, No.1, pp. 39-44, 2014.
  19. [19] K. Tsujimoto, T. Koike, S. I. Monichoto, K. Aida, K. Tamagawa, T. Nukui, and S. Sobue, “Validation of satellite precipitation products over Cambodia,” Trans. of the Japan Society for Aeronautical and Space Sciences, Aerospace Technology Japan, Vol.12, No.ists29, pp. Tn.41-Tn.46, 2014.
  20. [20] Marzuki, R. Oktaviani, L. Meylani, H. Hashiguchi, M. Vonnisa, and Harmadi, “One-Minute rain gauge distribution in Indonesia derived from TRMM, GPM and GSMaP data,” 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama), Vol.2018, pp. 2134-2138, 2018.
  21. [21] P. Deng, M. Zhang, H. Guo, C. Xu, J. Bing, and J. Jia, “Error analysis and correction of the daily GSMaP products over Hanjiang and River basin of China,” Atmospheric Research, Vol.214, pp. 121-134, 2018.
  22. [22] S. Prakash, A. K. Mitra, A. AghaKouchak, Z. Liu, H. Norouzi, and D. S. Pai, “A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region,” J. of Hydrology, Vol.556, pp. 865-876, 2018.
  23. [23] M. Saber and K. K. Yilmaz, “Evaluation and bias correction of satellite-based rainfall estimates for modelling flash floods over the Mediterranean region: Application to Karpuz River basin, Turkey,” Water, Vol.10, No.5, p. 657, 2018.
  24. [24] D. Lu, B. Yong, “Evaluation and hydrological utility of the latest GPM IMERG V5 and GSMaP V7 precipitation products over the Tibetan Plateau,” Remote Sensing, Vol.10, No.12, p. 2022, 2018.
  25. [25] I. Rashid, A. A. Parray, and S. A. Romshoo, “Evaluating the performance of remotely sensed precipitation estimates against In-Situ observations during the September 2014 mega-flood in the Kashmir Valley,” Asia-Pacific J. of Atmospheric Science, Vol.55, pp. 209-219, 2019.
  26. [26] M. Nashwan, S. Shahid, X. Wang, “Assessment of satellite-based precipitation measurement products over the hot desert climate of Egypt,” Remote Sensing, Vol.11, No.5, p. 555, 2019.
  27. [27] P. Deng, M. Zhang, J. Bing, J. Jia, and D. Zhang, “Evaluation of the GSMaP_Gauge products using rain gauge observations and SWAT model in the upper Hanjiang River basin,” Atmospheric Research, Vol.219, pp. 153-165, 2019.
  28. [28] T. H. Bui and H. Ishidaira, “Evaluation of satellite-gauge merging precipitation methods for rainfall runoff simulation,” Annual J. of Hydraulic Engineering, Vol.71, No.4, pp. I_79-I_84, 2017 (in Japanese with English abstract).
  29. [29] S. Seto and R. Taguchi, “Judgement of heavy rainfall corresponding to emergency warning by Global Satellite Mapping of Precipitation,” Annual J. of Hydraulic Engineering, Vol.72, No.4, pp. I_223-I_228, 2016 (in Japanese with English abstract).
  30. [30] T. Tebakari, S. Wongsa, and Y. Hayashi, “Flood in southern Thailand in December 2016 and January 2017,” J. Disaster Res., Vol.13, pp. 793-803, 2018.
  31. [31] D. D. Admojo, T. Tebakari, and M. Miyamoto, “Evaluation of a satellite-based rainfall product for a flood event: a case study,” Annual J. of Hydraulic Engineering, Vol.74, No.4, pp. I_73-I_78, 2018 (in Japanese with English abstract).
  32. [32] R. A. Acierto, A. Kawasaki, W. W. Zin, A. T. Oo, K. Ra, and D. Komori, “Development of a hydrological telemetry system in Bago River,” J. Disaster Res., Vol.13, No.1, pp. 116-124, 2018.
  33. [33] H. Chen, B. Yong, J. J. Gourley, J. Liu, L. Ren, W. Wang, Y. Hong, and J. Zhang, “Impact of the crucial geographic and climatic factors on the input source errors of GPM-based global satellite precipitation estimates,” J. of Hydrology, Vol.575, pp. 1-16, 2019.
  34. [34] S. Otsuka, S. Kotsuki, M. Ohhigashi, and T. Miyoshi, “GSMaP RIKEN Nowcast: Global precipitation nowcasting with data assimilation,” J. of the Meteorological Society of Japan, Vol.97, pp. 1099-1117, 2019.
  35. [35] T. Tashima, T. Kubota, and R. Oki, “Precipitation extremes monitoring using Global Satellite Mapping of Precipitation (GSMaP) products,” IEEE Conference Proceedings, Vol.2019, pp. 4463-4466, https://doi.org/10.1109/IGARSS.2019.8898435, 2019.
  36. [36] Japan Meteorological Agency, “Meteorological rainfall events that caused disasters from 1989–2020,” http://www.data.jma.go.jp/obd/stats/data/bosai/report/index_1989.html (in Japanese) [accessed August 21, 2020]
  37. [37] T. Kubota, K. Aonashi, T. Ushio, S. Shige, Y. N. Takayabu, M. Kachi, Y. Arai, T. Tashima, T. Masaki, N. Kawamoto, T. Mega, M. K. Yamamoto, A. Hamada, M. Yamaji, G. Liu, and R. Oki, “Global Satellite Mapping of Precipitation (GSMaP) products in the GPM era,” Satellite precipitation measurement, Vol.67, pp. 355-373, 2020.
  38. [38] D.S. Kim and M. Maki, “Validation of composite polarimetric parameters and rainfall rates from an X-band dual-polarization radar network in the Tokyo metropolitan area,” Hydrological Research Letters, Vol.6, pp. 76-81, 2012.
  39. [39] Y. Hayashi, T. Tebakari, and K. Yamasaki, “Accuracy of quantitative precipitation estimation by X-band Multi-Parameter Radar using rain-gauge data over Hokuriku region,” J. of Hydrology and Water Resources, Vol.27, No.2, pp. 67-76, 2014 (in Japanese with English abstract).
  40. [40] S. Tsuchiya, M. Kawasaki, and H. Godo, “Improvement of the radar rainfall accuracy of XRAIN by modifying of rainfall attenuation correction and compositing radar rainfall,” Annual J. of Hydraulic Engineering, Vol.71, No.4, pp. I_457-I_462, 2015 (in Japanese with English abstract).
  41. [41] E. Nakakita, K. Morimoto, and Y. Touge, “Estimation of future changes in the occurrence frequency of the guerrilla-heavy rainfall events using a 5-km-mesh reginal climate model,” Annual J. of Hydraulic Engineering, Vol.73, No.4, pp. I_133-I_138, 2017 (in Japanese with English abstract).
  42. [42] Y. Shiraishi, K. Fukami, and H. Inomata, “A proposal of correction method using the movement of rainfall area on satellite-based rainfall information by analysis in the Yoshino River basin,” Annual J. of Hydraulic Engineering, Vol.53, pp. 385-390, 2009 (in Japanese with English abstract).

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 05, 2024