Results 181 to 190 of about 1,203 (197)

Monitoring Rainfall Patterns in the Southern Amazon with PERSIANN-CDR Data: Long-Term Characteristics and Trends [PDF]

Remote Sensing, 2017
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 ...
Damien Arvor, Beatriz Funatsu, Véronique Michot   +2 more
exaly   +5 more sources

Assessing the Efficacy of High-Resolution Satellite-Based PERSIANN-CDR Precipitation Product in Simulating Streamflow

Journal of Hydrometeorology, 2016
AbstractThis study aims to investigate the performance of Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) in a rainfall–runoff modeling application over the past three decades.
Hamed Ashouri, Phú Nguyễn, Soroosh Sorooshian   +2 more
exaly   +2 more sources

Assessment of PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0 Rainfall Products over a Semi-Arid Subtropical Climatic Region [PDF]

Water (Switzerland), 2022
This study compares the performance of four satellite-based rainfall products (SRPs) (PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0) in a semi-arid subtropical region. As a case study, Punjab Province of Pakistan was considered for this assessment.
Muhammad Naveed Anjum, Muhammed Irfan, Muhammad Waseem   +2 more
exaly   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies

Bulletin of the American Meteorological Society, 2015
Abstract A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band
Hamed Ashouri, Soroosh Sorooshian, Kenneth R Knapp   +2 more
exaly   +2 more sources

PERSIANN-CDR for Hydrology and Hydro-climatic Applications

2020
Satellite-retrieved precipitation datasets represent a promising input data source to be utilized in hydroclimatic and hydrologic applications. Due to their characteristics of high spatiotemporal resolution, near real-time availability and quasi global coverage, satellite-retrieved precipitation datasets promise to provide a remedy for the long ...
Phu Nguyen, Hamed Ashouri, Mohammed Ombadi, Negin Hayatbini, Kuo-Lin Hsu, Soroosh Sorooshian   +5 more
openaire   +1 more source

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset [PDF]

Remote Sensing, 2020
Spatiotemporal precipitation trend analysis provides valuable information for water management decision-making. Satellite-based precipitation products with high spatial and temporal resolution and long records, as opposed to temporally and spatially sparse rain gauge networks, are a suitable alternative to analyze precipitation trends over Iran.
Hamidreza Mosaffa, Mojtaba Sadeghi, Negin Hayatbini   +2 more
exaly   +3 more sources

Probabilistic drought forecasting using copula and satellite rainfall based PERSIANN‐CDR and MSWEP datasets

International Journal of Climatology, 2022
AbstractIn situ rainfall data plays a vital role in drought assessment. However, adequate in situ data are not available in many parts of the world, and they do not provide the proper spatial coverage for drought assessment. With the advacements in satellite rainfall estimates (SREs), it is possible to monitor droughts in ungauged basins.
Mohammadali Alijanian, Gholam Reza Rakhshandehroo, Maryam Dehghani, Ashok Mishra   +3 more
openaire   +1 more source

PERSIANN-CDR based characterization and trend analysis of annual rainfall in Rio De Janeiro State, Brazil

Atmospheric Research, 2020
Abstract Climate Data analysis has become a fundamental tool for scientists who seek to better evaluate changes in climatic variables worldwide. When it comes to rainfall there are many datasets publicly available, and orbital products have been gradually sharpening its results.
Bruno Serafini Sobral, José Francisco de Oliveira-Júnior, Fabiano Alecrim, Givanildo Gois, João Gualberto Muniz-Júnior, Paulo Miguel de Bodas Terassi, Edson Rodrigues Pereira-Júnior, Gustavo Bastos Lyra, Marcelo Zeri   +8 more
openaire   +1 more source

Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China

Journal of Hydrometeorology, 2015
AbstractThis study evaluates the performance of a newly developed daily precipitation climate data record, called Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), in capturing the behavior of daily extreme precipitation events in China during the period of 1983–2006 ...
Chiyuan Miao, Hamed Ashouri, Soroosh Sorooshian   +2 more
exaly   +2 more sources

Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran

Journal of Hydrology, 2019
Abstract Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a ...
Mohammadali Alijanian, Gholam Reza Rakhshandehroo, Ashok Mishra, Maryam Dehghani   +3 more
openaire   +1 more source