Estimation of Rainfall via IMERG-FR and Its Relationship with the Records of a Rain Gauge Network with Spatio-Temporal Variation, Case of Study: Mexican Semi-Arid Region

Abstract

In the last few years, Satellite Precipitation Estimates (SPE) have been increasingly used for rainfall estimation applications. Their validity and accuracy are influenced by several factors related to the location where the SPEs are applied. The objective of this study is to evaluate the performance of the Integrated Multisatellite Retrievals for Global Precipitation Measurement Version 06 Half-Hour Temporal Resolution (IMERG-FR V06 HH) for rainfall estimation, as well as to determine its relationships with the hourly and daily rain gauge network data in a semiarid region during 2019–2021. The methodology contemplates the temporality, elevation, rainfall intensity, and rain gauge density variables, carrying out a point-to-pixel analysis using continuous, (Bias, r, ME, and RMSE), categorical (POD, FAR, and CSI), and volumetric (VHI, VFAR, and VCSI) statistical metrics to understand the different behaviors between the rain gauge and IMERG-FR V06 HH data. IMERG-FR greatly underestimated the heavy rainfall events in values of −63.54 to −23.58 mm/day and −25.29 to −11.74 mm/30 min; however, it overestimates the frequency of moderate rain events (1 to 25 mm/day). At making the correlation (r) between the temporal scales, the monthly temporal resolution was the one that better relates the measured and estimated data, as well as reported r values of 0.83 and 0.85, where records at shorter durations in IMERG-FR do not detect them. The weakness of this system, according to the literature and confirmed by the research findings, in the case of hydrological phenomena, is that recording or estimating short durations is essential for the water project, and therefore, the placement of rain gauges. The 1902–2101 m.a.s.l. range elevation has the best behavior between the data with the lowest error and best detection ability, of which IMERG-FR tended to overestimate the rain at higher altitudes. Considering that the r for two automated rain gauges per IMERG-FR pixel density was 0.74, this indicates that the automated rain gauges versus IMERG-FR have a better data fit than the rain gauges versus IMERG-FR. The distance to centroid and climatic evaluations did not show distinctive differences in the performance of IMERG. These findings are useful to improve the IMERG-FR algorithms, guide users about its performance at semiarid plateau regions, and assist in the recording of data for hydrological projects.

Keywords

• IMERG-FR
• rainfall
• rain gauge
• satellite image
• statistical evaluation