Performance Assessment of IMERG V07 Versus V06 for Precipitation Estimation in the Parnaíba River Basin

Abstract

What are the main findings?

IMERG V07 reduced systematic errors compared to V06, with lower bias and random errors across most of the basin, while high Rbias values (>70%) persisted in the northeastern highlands due to orographic–convective interactions. Detection capacity also improved, with false alarms reduced by ~5% and KGE increasing by ~11%.

Cluster-based analysis revealed that V07 better represented seasonal precipitation variability, correcting overestimation in wet periods and underestimation in semi-arid regions.

What is the implication of the main finding?

These improvements enhance the reliability of IMERG V07 for hydrological and climate applications in tropical basins with strong seasonal variability.

Persistent errors in mountainous and transitional areas highlight the need for regionalized bias corrections tailored to local climatic and topographic conditions.

Accurate satellite-based precipitation estimates are crucial for climate studies and water resource management, particularly in regions with sparse meteorological station coverage. This study evaluates the improvements of the Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run version 07 (V07) relative to the previous version (V06). The evaluation employed gridded data from the Brazilian Daily Weather Gridded Data (BR-DWGD) product and ground observations from 58 rain gauges distributed across the Parnaíba River Basin in Northeast Brazil. The analysis comprised three main stages: (i) an intercomparison between BR-DWGD gridded data and rain gauge records using correlation, bias, and Root Mean Square Error (RMSE) metrics; (ii) a comparative assessment of the IMERG Final V06 and V07 products, evaluated with statistical metrics (correlation, bias, and RMSE) and complemented by performance indicators including the Kling-Gupta Efficiency (KGE), Probability of Detection (POD), and False Alarm Ratio (FAR); and (iii) the application of cluster analysis to identify homogeneous regions and characterize seasonal rainfall variations across the basin. The results show that the IMERG Final V07 product provides notable improvements, with lower bias, reduced RMSE, and greater accuracy in representing the spatial distribution of precipitation, particularly in the central and southern regions of the basin, which feature complex topography. IMERG V07 also demonstrated higher consistency, with reduced random errors and improved seasonal performance, reflected in higher POD and lower FAR values during the rainy season. The cluster analysis identified four homogeneous regions, within which V07 more effectively captured seasonal rainfall patterns influenced by systems such as the Intertropical Convergence Zone (ITCZ) and Amazonian moisture advection. These findings highlight the potential of the IMERG Final V07 product to enhance precipitation estimation across diverse climatic and topographic settings, supporting applications in hydrological modeling and extreme-event monitoring.