Providing reliable long-term global precipitation records at high spatial and temporal resolutions is crucial for climatological studies. Satellite-based precipitation estimations are a promising alternative to rain gauges for providing homogeneous precipitation information. Most satellite-based precipitation products suffer from short-term data records, which make them unsuitable for various climatological and hydrological applications. However, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) provides more than 35 years of precipitation records at 0.25° × 0.25° spatial and daily temporal resolutions. The PERSIANN-CDR algorithm uses monthly Global Precipitation Cl...
The number of global precipitation datasets (PPs) is on the rise and they are commonly used for hydr...
The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facili...
Characterizing the errors in satellite-based precipitation estimation products is crucial for unders...
Providing reliable long-term global precipitation records at high spatial and temporal resolutions i...
Accurate precipitation estimation at fine spatial and temporal scale is crucial for climatological s...
Accurate long-term global precipitation estimates, especially for heavy precipitation rates, at fine...
The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks for C...
Over the past 2 decades, a wide range of studies have incorporated Precipitation Estimation from Rem...
In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remot...
Over the past 2 decades, a wide range of studies have incorporated Precipitation Estimation from Re...
This paper examines the spatial error structures of eight precipitation estimates derived from four ...
In this study, satellite-based daily precipitation estimation data from precipitation estimation fro...
Accurate and continuous rainfall monitoring is essential for effective water resources management, e...
In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Net...
Satellite-based rainfall estimates (SREs) represent a promising alternative dataset for climate and ...
The number of global precipitation datasets (PPs) is on the rise and they are commonly used for hydr...
The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facili...
Characterizing the errors in satellite-based precipitation estimation products is crucial for unders...
Providing reliable long-term global precipitation records at high spatial and temporal resolutions i...
Accurate precipitation estimation at fine spatial and temporal scale is crucial for climatological s...
Accurate long-term global precipitation estimates, especially for heavy precipitation rates, at fine...
The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks for C...
Over the past 2 decades, a wide range of studies have incorporated Precipitation Estimation from Rem...
In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remot...
Over the past 2 decades, a wide range of studies have incorporated Precipitation Estimation from Re...
This paper examines the spatial error structures of eight precipitation estimates derived from four ...
In this study, satellite-based daily precipitation estimation data from precipitation estimation fro...
Accurate and continuous rainfall monitoring is essential for effective water resources management, e...
In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Net...
Satellite-based rainfall estimates (SREs) represent a promising alternative dataset for climate and ...
The number of global precipitation datasets (PPs) is on the rise and they are commonly used for hydr...
The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facili...
Characterizing the errors in satellite-based precipitation estimation products is crucial for unders...