Probable Maximum Precipitation (PMP) is an essential prerequisite in designing dams, spillways, and reservoirs in order to minimize the risk of overtopping infrastructure collapse, especially under today’s changing climate. This study investigates conventional PMP estimation approach by using both scarce in-situ observations and mainstream satellite precipitation products in the Dadu River basi...

Precipitation data with fine quality plays vital roles in hydrological-related applications. In this study, we choose the high-quality China Merged Analysis (CMPA) as benchmark for evaluating four satellite-based precipitation products (PERSIANN-CCS, FY4A QPE, GSMap_Gauge, IMERG-Final) and one model-based product (ERA5-Land), respectively, at 0.1°, hourly scales over Zhejiang province, China, s...

[1] Water resources management, forecasting, and decision making require reliable estimates of precipitation. Extreme precipitation events are of particular importance because of their severe impact on the economy, the environment, and the society. In recent years, the emergence of various satellite‐retrieved precipitation products with high spatial resolutions and global coverage have resulted...

Abstract Because of the sparseness ground monitoring network, precipitation estimations based on satellite products (PESPs) are currently requisite tools for hydrological simulation research and applications. The evaluation six global high-resolution PESPs (TRMM 3B42V7, GPGP-1DD, TRMM 3B42RT, CMORPH-V1.0, PERSIANN, PERSIANN-CDR) is ultimate purpose this research. Additionally, distributed Hydro...

Over the past few decades, several high-resolution gridded precipitation products have been developed using multiple data sources and techniques, including measured precipitation, numerical modeling, remote sensing. Each has its own sets of uncertainties limitations. Therefore, evaluating these datasets is critical in assessing their applicability various climatic regions. We used ten datasets,...

An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Climate Prediction center MORPHing technique (CMORPH), and Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMP...

We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) Morphing Technique (CMORPH)—over the African contine...

Satellite-derived estimates of precipitation are essential to compensate for missing rainfall measurements in regions where the homogeneous and continuous monitoring of rainfall remains challenging due to low density rain gauge networks. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Climate Data Record (PERSIANN-CDR) is a relatively new product (...