In this paper, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) is analyzed for the assessment of meteorological drought. The evaluation is conducted over China at 0.5 ̋ spatial resolution against a ground-based gridded China monthly Precipitation Analysis Product (CPAP) from 1983 to 2014 (32 years). The Standardized Pr...

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...

The skill of the diverse-based precipitation products is investigated in comparison with observed-derived HYBAM and GoAmazon TRMM-LBA field campaigns data. performance eight remote sensing-based datasets (CHIRPS, MSWEP, TRMM, CMORPH, IMERG, PERSIANN-CDR, PERSIANN-CCS-CDR, PERSIANN-CCS) evaluated from 1998 to 2009 considering different timescales (diurnal, intraseasonal, seasonal) for Amazon Bas...

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...

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...

Satellite precipitation products (SPPs) are critical data sources for hydrological prediction and extreme event monitoring, especially for ungauged basins. This study conducted a comprehensive hydrological evaluation of six mainstream SPPs (i.e., TMPA 3B42RT, CMORPH-RT, PERSIANN-RT, TMPA 3B42V7, CMORPH-CRT, and PERSIANN-CDR) over humid Xixian basin in central eastern China for a period of 14 ye...

Evaluating satellite-based products is vital for precipitation estimation sustainable water resources management. The current study evaluates the accuracy of predicting using four remotely sensed rainfall datasets—Tropical Rainfall Measuring Mission (TRMM-3B42V7), Precipitation Estimation from Remotely Sensed Information Artificial Neural Networks Climate Data Records (PERSIANN-CDR), Cloud Clas...