Abstract
Ground based rainfall information is hardly available in most high mountain areas of the world due to the remoteness and complex topography. Thus, proper understanding of spatio-temporal rainfall dynamics still remains a challenge in those areas. Satellite-based rainfall products may help if their rainfall assessment are of high quality. In this paper, microwave-based integrated multi-satellite retrieval for the Global Precipitation Measurement (GPM) (IMERG) (MW-based IMERG) was assessed along with the random-forest-based rainfall (RF-based rainfall) and infrared-only IMERG (IR-only IMERG) products against the quality-controlled rain radar network and meteorological stations of high temporal resolution over the Pacific coast and the Andes of Ecuador. The rain area delineation and rain estimation of each product were evaluated at a spatial resolution of 11 km2 and at the time of MW overpass from IMERG. The regionally calibrated RF-based rainfall at 2 km2 and 30 min was also investigated. The validation results indicate different essential aspects: (i) the best performance is provided by MW-based IMERG in the region at the time of MW overpass; (ii) RF-based rainfall shows better accuracy rather than the IR-only IMERG rainfall product. This confirms that applying multispectral IR data in retrieval can improve the estimation of rainfall compared with single-spectrum IR retrieval algorithms. (iii) All of the products are prone to low-intensity false alarms. (iv) The downscaling of higher-resolution products leads to lower product performance, despite regional calibration. The results show that more caution is needed when developing new algorithms for satellite-based, high-spatiotemporal-resolution rainfall products. The radar data validation shows better performance than meteorological stations because gauge data cannot correctly represent spatial rainfall in complex topography under convective rainfall environments.
Highlights
Understanding precipitation amounts and patterns is essential for sustainable water management and monitoring the hydrological cycle [1]
We evaluated and compared the performance of different satellitebased rainfall products over the Pacific coast and Andes of Ecuador
A mesoscale qualitycontrolled rain radar network was used as the rainfall reference
Summary
Understanding precipitation amounts and patterns is essential for sustainable water management and monitoring the hydrological cycle [1]. In complex mountainous regions characterized by high spatiotemporal variability, coarse networks of operational precipitation gauge stations are often lacking. The spatiotemporal variability, combined with lack of gauge data, makes the time series and area-averaged rainfall analysis more complicated in these regions [2]. This applies to the complex topography of the Andes in Ecuador. Satellite-based rainfall retrieval efforts estimated rainfall from geostationary infrared (IR) data, using the indirect relationship between precipitation rate and the temperature of cloud on top [3]. Unlike IR, microwave (MW) sensors measure thermal radiance from actual precipitation particles in the clouds; MW retrieval generally provides superior precipitation information [4]
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