Browse > Article
http://dx.doi.org/10.11108/kagis.2020.23.3.208

Comparison of Accuracy for GPM IMERG, GSMaP and CMORPH Satellite Precipitation Products over Korea  

KIM, Joo-Hun (Dept. of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology)
CHOI, Yun-Seok (Dept. of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology)
KIM, Kyung-Tak (Dept. of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.23, no.3, 2020 , pp. 208-219 More about this Journal
Abstract
This study aims to determine the applicability of satellite precipitation to the ungauged or inaccessible areas by comparing the accuracy of satellite precipitation. The accuracy assessment showed that the overall spatial distributions of ground-based rainfall and satellite precipitation were similar in all three events. For one-month precipitation with one-hour temporal resolution, the correlations between ground-based precipitation (ASOS) and satellite precipitation were analyzed to be between 0.42 and 0.46. In the evaluation during the period in which precipitation was concentrated, the correlation coefficients for one-hour temporal resolution data were analyzed as 0.55 to 0.66 for IMERG and 0.56 to 0.67 for GSMAP. According to the total rainfall analysis of each rainfall station for the three events, the correlation coefficients of IMERG and GSMaP were relatively better than CMORPH, and the bias of CMORPH data was relatively better than IMERG and GSMaP. However, all the three satellite precipitation were underestimated compared to the ground-based precipitation. In the future, a study will be carried out to estimate precipitation across the Korean Peninsula, including North Korea, reflecting the results from this study.
Keywords
Satellite Precipitation; IMERG; GSMaP; CMORPH; accuracy;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
1 Aonashi, K., J. Awaka, M. Hirose, T. Kozu, T. Kubota, G. Liu, S. Shige, S. Kida, S. Seto, N. Takahashi and Y.N. Takayabu. 2009. Gsmap passive microwave precipitation retrieval algorithm: Algorithm description and validation. Journal of the Meteorological Society of Japan 87:119-136. doi:10. 2151/jmsj.87A.119.   DOI
2 Choi Y.S., J.H. Kim and J.S. Kim. 2020. Inundation analysis on the flood plain in ungauged area using satellite rainfall and global geographic data: In the case of Tumen/Namyang area in Duman-gang (Riv.). Journal of the Korean Association of Geographic Information Studies 23(1):51-64.
3 Dandridge, C., V. Lakshmi, J. Bolten and R. Srinivasan. 2019. Evaluation of satellite based satellite based rainfall estimates in the Lower Mekong River Basin(Southeast Asia). Remote Sensing 11:2709.   DOI
4 Dembele, M. and S.J. Zwart. 2016. Evaluation and comparison of satellite-based rainfall products in Burkina Faso, West Africa. International Journal of Remote Sensing 37(17):3995-4014.   DOI
5 Hong Y, Zhang Y., Khan S. 2016. Hydrologic remote sensing: Capacity building for sustainability and resilience CRC Press(2016). 395pp.
6 Hong Y, G. Tang, Y. Ma, Q. Huang, Z. Han, Z. Zeng, Y. Yang, C. Wang and X. Guo. 2019. Remote sensing precipitation: sensors, retrievals, validations, and applications. In: Li X., Vereecken H.(eds) Observation and measurement of ecohydrological processes. Ecohydrology, vol.2. Springer, Berlin, Heidelberg p.107-128.
7 Hoscilo, A., H. Balzter, E. Bartholome, M. Boschetti, P.A. Brivio, A, Brink, M. Clericic and J.F. Pekelc. 2015. A conceptual model for assessing rainfall and vegetation trends in Sub-Saharan Africa from satellite data. International Journal of Climatology. 35:3582-3592.   DOI
8 Kim, J.H., K.T. Kim and Y.S. Choi 2013. Fitness evaluation of CMORPH satellite -derived precipitation data in Korea. Journal of Wetlands Research 15(3):339-346.   DOI
9 Kim, J.H., Y.S. Choi and K.T. Kim. 2017a. Evaluation for accuracy of IMERG at multiple temporal scales. Journal of the Korean Association of Geographic Information Studies 20(4):12-26.
10 Kim, J.H., Y.S. Choi and K.T. Kim. 2015. Flow estimation using rainfalls derived from multiple satellite images in North Korea. Journal of the Korean Association of Geographic Information Studies 18(4):31-42.   DOI
11 Kim, J.H., Y.S. Choi and K.T. Kim. 2017b. Estimation of flood discharge using satellite-derived rainfall in abroad watersheds-A case study of Sebou watershed, Morocco. Journal of the Korean Association of Geographic Information Studies 20(3):141-152.   DOI
12 Kim, I.W., J. Oh, S. Woo and R.H. Kripalani. 2019. Evaluation of precipitation extremes over the Asian domain: observation and modelling studies. Climate Dynamics. 52:1317-1342.   DOI
13 Ning, S.W., Wang, J., Jin, J.L., Ishidaira, H., 2016. Assessment of the latest GPMera high resolution satellite precipitation products by comparison with observation gauge data over the Chinese mainland. Water 8,(11), 481:1-7.
14 Tan, M.L., Ibrahim, A.L., Duan, Z., Cracknell, A.P. and Chaplot, V. 2015. Evaluation of six high-resolution satellite and ground-based precipitation products over Malaysia. Remote Sens 7:1504-1528.   DOI
15 NOAA Climate Prediction Center. 2011. Bias-corrected CMORPH: A 13-year analysis of high-resolution global precipitation. http://ftp.cpc.ncep.noaa.gov/precip/CMORPH_V1.0/REF/EGU_1104_Xie_bias-CMORPH.pdf (Accessed April 10, 2020)
16 Prakash, S. Mitra, A.K. Pai, D.S. and AghaKouchak, A. 2016. From TRMM to GPM: How well can heavy rainfall be detected from space? Adv. Water Resour 88:1-7.   DOI
17 Sharifi, E., Steinacker, R. and Saghafian, B., 2016. Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran: preliminary results. Remote Sens. 8, 24.   DOI
18 Sohn, B.J., H.J. Han, and E.K. Seo. 2010. Validation of satellite-based highresolution rainfall products over the Korean Peninsula using data from a dense rain gauge network. Journal of Applied Meteorology and Climatology 49(4):701-714.   DOI
19 Sun, R., Yuan, H., Liu, X. and Jiang, X., 2016. Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin. J.Hydrol 536:302-319.   DOI
20 Tong, K., Su, F., Yang, D. and Hao, Z. 2014. Evaluation of satellite precipitation retrievals and their potential utilities in hydrologic modeling over the Tibetan Plateau. J.Hydrol 519, 423-437.   DOI
21 Xu, R., Tian, F., Yang, L., Hu, H., Lu, H. and Hou, A. 2017. Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over Southern Tibetan Plateau based on a high density rain gauge network. J. Geophys. Res. -Atmos. 122:910-924.   DOI
22 Yuan, F., L. Zhang, K. Soe and Y. Liu. 2019. Applications of TRMM- and GPM -Era Multiple-satellite Precipitation Products for Flood Simulations at Subdaily Scales in a Sparsely Gauged Watershed in Myanmar. Remote Sensing.11(2):140.   DOI