Results 141 to 150 of about 576 (159)
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 ...
Véronique Michot +2 more
exaly +6 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
PERSIANN-CDR for Hydrology and Hydro-climatic Applications
2020Satellite-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 +5 more
openaire +1 more source
Atmospheric Environment, 2021
Abstract The availability of continuous long-term precipitation time series with uniform spatial distribution has a significant role in hydrological studies and applications from simple water budget calculation to infrastructure design. However, in numerous parts of the world precipitation observations are sparse, patchy and uneven and hence ...
Narjes Salmani-Dehaghi, Nozar Samani
openaire +1 more source
Abstract The availability of continuous long-term precipitation time series with uniform spatial distribution has a significant role in hydrological studies and applications from simple water budget calculation to infrastructure design. However, in numerous parts of the world precipitation observations are sparse, patchy and uneven and hence ...
Narjes Salmani-Dehaghi, Nozar Samani
openaire +1 more source
Evaluation of PERSIANN System Satellite–Based Estimates of Tropical Rainfall
Bulletin of the American Meteorological Society, 2000Abstract PERSIANN, an automated system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, has been developed for the estimation of rainfall from geosynchronous satellite longwave infared imagery (GOES–IR) at a resolution of 0.25° × 0.25° every half–hour.
Soroosh Sorooshian +5 more
openaire +1 more source
Improving PERSIANN-CCS Using Passive Microwave Rainfall Estimation
2020Re-calibrated PERSIANN-CCS is one of the algorithms used in “Integrated Multi-satellitE Retrievals for GPM” (IMERG) to provide high-resolution precipitation estimations from the NASA Global Precipitation Measurement (GPM) program and retrospective data generation for the period covered by the Tropical Rainfall Measurement Mission (TRMM).
Kuo-Lin Hsu +2 more
openaire +1 more source
International Journal of Climatology, 2017
ABSTRACTIn situ rainfall data observed by gauges is the most important data in water resources management. However, these data have some limitations both spatially and temporally. With the advancements in satellite rainfall products, it is now possible to evaluate whether these products can capture the climatology of known rainfall characteristics.
Mohammadali Alijanian +3 more
openaire +1 more source
ABSTRACTIn situ rainfall data observed by gauges is the most important data in water resources management. However, these data have some limitations both spatially and temporally. With the advancements in satellite rainfall products, it is now possible to evaluate whether these products can capture the climatology of known rainfall characteristics.
Mohammadali Alijanian +3 more
openaire +1 more source
Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks [PDF]
Journal of Geophysical Research D: Atmospheres, 2018 AbstractShort‐term Quantitative Precipitation Forecasting is important for flood forecasting, early flood warning, and natural hazard management. This study proposes a precipitation forecast model by extrapolating Cloud‐Top Brightness Temperature (CTBT) using advanced Deep Neural Networks, and applying the forecasted CTBT into an effective rainfall ...
Soroosh Sorooshian +2 more
exaly +4 more sources
Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm
2009The need for frequent observations of precipitation is critical to many hydrological applications. The recently developed high resolution satellite-based precipitation algorithms that generate precipitation estimates at sub-daily scale provide a great potential for such purpose.
Kuo-Lin Hsu +3 more
openaire +1 more source
Error Analysis on PERSIANN Precipitation Estimations: Case Study of Urmia Lake Basin, Iran
Journal of Hydrologic Engineering, 2018AbstractIn-depth evaluation and analysis of the error properties associated with satellite-based precipitation estimation algorithms can play an important role in the future development and improve...
N. Ghajarnia +3 more
openaire +1 more source
Theoretical and Applied Climatology, 2019
High resolution and global coverage of the satellite-based precipitation data have been found useful in many climate and hydrological studies, particularly in limited and nongauged areas. Due to systematic and nonsystematic factors, there are always deviations between ground-based and satellite-based precipitation.
Narjes Salmani-Dehaghi, Nozar Samani
openaire +1 more source
High resolution and global coverage of the satellite-based precipitation data have been found useful in many climate and hydrological studies, particularly in limited and nongauged areas. Due to systematic and nonsystematic factors, there are always deviations between ground-based and satellite-based precipitation.
Narjes Salmani-Dehaghi, Nozar Samani
openaire +1 more source