Evaluation of the IMERG Product Performance at Estimating the Rainfall Properties in a Semi-Arid Region of Mexico

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention, however, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem is the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement final run V06B SPP in a semi-arid region of Mexico, using four rain gauges sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing moderate overestimations and underestimations, respectively. The study zone presented 80 to 85% of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and rain gauges. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation.

References:

[1] Y. Wang, C. Miao, X. Zhao, Q. Zhang, and J. Su, “Evaluation of the GPM IMERG product at the hourly timescale over China,” Atmospheric Res., vol. 285, p. 106656, Apr. 2023, doi: 10.1016/j.atmosres.2023.106656.
[2] R. Li, C. Guilloteau, P.-E. Kirstetter, and E. Foufoula-Georgiou, “How well does the IMERG satellite precipitation product capture the timing of precipitation events?,” J. Hydrol., vol. 620, p. 129563, May 2023, doi: 10.1016/j.jhydrol.2023.129563.
[3] L. Yu, G. Leng, and A. Python, “A comprehensive validation for GPM IMERG precipitation products to detect extremes and drought over mainland China,” Weather Clim. Extrem., vol. 36, p. 100458, Jun. 2022, doi: 10.1016/j.wace.2022.100458.
[4] P. Weng, Y. Tian, Y. Jiang, D. Chen, and J. Kang, “Assessment of GPM IMERG and GSMaP daily precipitation products and their utility in droughts and floods monitoring across Xijiang River Basin,” Atmospheric Res., vol. 286, p. 106673, May 2023, doi: 10.1016/j.atmosres.2023.106673.
[5] M. Gentilucci, M. Barbieri, and G. Pambianchi, “Reliability of the IMERG product through reference rain gauges in Central Italy,” Atmospheric Res., vol. 278, p. 106340, Nov. 2022, doi: 10.1016/j.atmosres.2022.106340.
[6] S. Jiang, L. Wei, L. Ren, L. Zhang, M. Wang, and H. Cui, “Evaluation of IMERG, TMPA, ERA5, and CPC precipitation products over mainland China: Spatiotemporal patterns and extremes,” Water Sci. Eng., vol. 16, no. 1, pp. 45–56, Mar. 2023, doi: 10.1016/j.wse.2022.05.001.
[7] M. Yang, G. Liu, T. Chen, Y. Chen, and C. Xia, “Evaluation of GPM IMERG precipitation products with the point rain gauge records over Sichuan, China,” Atmospheric Res., vol. 246, p. 105101, Dec. 2020, doi: 10.1016/j.atmosres.2020.105101.
[8] E. da S. Freitas et al., “The performance of the IMERG satellite-based product in identifying sub-daily rainfall events and their properties,” J. Hydrol., vol. 589, p. 125128, Oct. 2020, doi: 10.1016/j.jhydrol.2020.125128.
[9] W. Wang et al., “Minimum Inter-Event Times for Rainfall in the Eastern Monsoon Region of China,” Trans. ASABE, vol. 62, no. 1, pp. 9–18, 2019, doi: 10.13031/trans.12878.
[10] INEGI, “Resumen de Zacatecas.” Accessed: Feb. 27, 2023. Online. Available: https://cuentame.inegi.org.mx/monografias/informacion/zac/
[11] G. Van Rossum and F. L. Drake, Python 3 Reference Manual. Scotts Valley, CA: CreateSpace, 2009.
[12] C.-Y. Liu, P. Aryastana, G.-R. Liu, and W.-R. Huang, “Assessment of satellite precipitation product estimates over Bali Island,” Atmospheric Res., vol. 244, p. 105032, Nov. 2020, doi: 10.1016/j.atmosres.2020.105032.