Results 151 to 160 of about 1,454 (169)

Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks [PDF]

Journal of Geophysical Research D: Atmospheres, 2018
Short-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 ...
Soroosh Sorooshian, Tiantian Yang, Kuolin Hsu   +2 more
exaly   +6 more sources

Assessment of PERSIANN Satellite Products over the Tulijá River Basin, Mexico

Remote Sensing
Precipitation is a fundamental component of the Earth’s hydrological cycle. Therefore, monitoring precipitation is paramount, as accurate information is needed to prevent natural hydrological disasters, such as floods and droughts. However, measuring precipitation using rain gauges is complicated due to their sparse spatial distribution.
René Sebastián Mora Ortiz, FRANCISCO Magana Hernández, Gabriela Adina Moroșanu   +2 more
exaly   +4 more sources

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, Vincent Dubreuil, Damien Arvor   +2 more
exaly   +6 more sources

Evaluation of PERSIANN-CDR Constructed Using GPCP V2.2 and V2.3 and A Comparison with TRMM 3B42 V7 and CPC Unified Gauge-Based Analysis in Global Scale [PDF]

Remote Sensing, 2019
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 ...
Soroosh Sorooshian, Kuolin Hsu, Mohammad Faridzad   +2 more
exaly   +2 more sources

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On an Enhanced PERSIANN-CCS Algorithm for Precipitation Estimation

Journal of Atmospheric and Oceanic Technology, 2012
Abstract By employing wavelet and selected features (WSF), median merging (MM), and selected curve-fitting (SCF) techniques, the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) has been improved.
Kuo-Lin Hsu, James Aanstoos, Nicolas H. Younan, Valentine G. Anantharaj, Majid Mahrooghy   +4 more
openaire   +1 more source

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

Development of bias-correction PERSIANN-CDR models for the simulation and completion of precipitation time series

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

Evaluation of PERSIANN System Satellite–Based Estimates of Tropical Rainfall

Bulletin of the American Meteorological Society, 2000
Abstract 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, Kuo-Lin Hsu, Xiaogang Gao, Hoshin V. Gupta, Bisher Imam, Dan Braithwaite   +5 more
openaire   +1 more source

Improving PERSIANN-CCS Using Passive Microwave Rainfall Estimation

2020
Re-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, Negar Karbalee, Dan Braithwaite   +2 more
openaire   +1 more source

Evaluation of satellite rainfall climatology using CMORPH, PERSIANN‐CDR, PERSIANN, TRMM, MSWEP over Iran

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, Gholam Reza Rakhshandehroo, Ashok K. Mishra, Maryam Dehghani   +3 more
openaire   +1 more source