[HTML][HTML] Robustness of gridded precipitation products for Vietnam basins using the comprehensive assessment framework of rainfall
The use of satellite–based precipitation products (SPPs) have become increasingly
prevalent as key inputs to provide regional rainfall for improving hydrological simulations in …
prevalent as key inputs to provide regional rainfall for improving hydrological simulations in …
[HTML][HTML] Comparison of bias-corrected multisatellite precipitation products by deep learning framework
Despite satellite-based precipitation products (SPPs) providing a worldwide span with a
high spatial and temporal resolution, their efficiency in disaster risk forecasting, hydrological …
high spatial and temporal resolution, their efficiency in disaster risk forecasting, hydrological …
Intercomparison of multiple high-resolution precipitation products over China: Climatology and extremes
An accurate and high spatiotemporal resolution precipitation observation dataset is crucial
to the studies of climate change and related impact assessments. Great efforts have been …
to the studies of climate change and related impact assessments. Great efforts have been …
[HTML][HTML] Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks
Accurate rainfall-runoff (RR) modeling is crucial for effective Mekong River Basin (MRB)
water resource management. Satellite precipitation products (SPPs) can offer valuable data …
water resource management. Satellite precipitation products (SPPs) can offer valuable data …
A preliminary assessment of the GSMaP Version 08 products over Indonesian maritime continent against gauge data
This study is a preliminary assessment of the latest version of the Global Satellite
Measurement of Precipitation (GSMaP version 08) data, which were released in December …
Measurement of Precipitation (GSMaP version 08) data, which were released in December …
Accuracy assessment and bias correction of remote sensing–based rainfall products over semiarid watersheds
In the context of water scarcity, the strong spatiotemporal fluctuation of rainfall combined with
the sparsity of the rain gauge (RG) measurement networks, particularly over the …
the sparsity of the rain gauge (RG) measurement networks, particularly over the …
Deep learning-based bias correction of ISMR simulated by GCM
Simulated data of atmospheric variables like precipitation is very important for climate
science research, especially for understanding future scenarios. Such data is generated by …
science research, especially for understanding future scenarios. Such data is generated by …
SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies
A reliable and accurate long-term rainfall dataset is an indispensable resource for
climatological studies and crucial for application in water resource management, agriculture …
climatological studies and crucial for application in water resource management, agriculture …
Bias correction of the hourly satellite precipitation product using machine learning methods enhanced with high-resolution WRF meteorological simulations
N Yao, J Ye, S Wang, S Yang, Y Lu, H Zhang… - Atmospheric …, 2024 - Elsevier
Accurate precipitation data are crucial in atmospheric and hydrological studies, especially
for water resource management and disaster early warning. Satellite precipitation product …
for water resource management and disaster early warning. Satellite precipitation product …
Distributed hydrological model based on machine learning algorithm: assessment of climate change impact on floods
Rapid population growth, economic development, land-use modifications, and climate
change are the major driving forces of growing hydrological disasters like floods and water …
change are the major driving forces of growing hydrological disasters like floods and water …