Characterizing the errors in satellite-based precipitation estimation products is crucial for understanding their effects in hydrological applications. Six precipitation products derived from three algorithms are comprehensively evaluated against gauge data over mainland China from December 2006 to November 2010. These products include three satellite-only estimates: the Global Satellite Mappin...

Deficiency and inappropriate distribution of reengage station is one of challenges faced by researchers in hydrology and climate science. In this research, evaluate the applicability of four gridded precipitation data products ERA-Interim, PERSIANN-CDR, PERSIANN-CCS and CRU as a supplement or substitute for ground data in a monthly time scales. This assessment was done by comparison with observ...

Recent progress in satellite remote-sensing techniques for precipitation estimation, along with more accurate tropical rainfall measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) instruments, have made it possible to monitor tropical rainfall diurnal patterns and their intensities from satellite information. One year (August 1998...

This study evaluates rainfall estimates from the Next Generation Weather Radar (NEXRAD), operational rain gauges, Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) in the context as inputs to a calibrated, distributed hy...

Gridded climate products (GCPs) provide a potential source for representing weather in remote, poor quality or short-term observation regions. The accuracy of three long-term GCPs (Asian Precipitation—Highly-Resolved Observational Data Integration towards Evaluation of Water Resources: APHRODITE, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate D...

Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies four (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, PERSIANN) using data in situ weather stations installed over Himalayan Mountains Pakistan. All SPPs were evaluated on annual, seasonal, monthly, daily bases from 2010 to 2017, whole spatial d...

By employing wavelet and selected features (WSF), median merging (MM), and selected curve-fitting (SCF) techniques, the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) has been improved. The PERSIANN-CCS methodology includes the following four main steps: 1) segmentation of satellite cloud images into cloud pat...