Results 41 to 50 of about 1,454 (169)
PERSIANN-MSA: A Precipitation Estimation Method from Satellite-Based Multispectral Analysis [PDF]
Journal of Hydrometeorology, 2009 Abstract Visible and infrared data obtained from instruments onboard geostationary satellites have been extensively used for monitoring clouds and their evolution. The Advanced Baseline Imager (ABI) that will be launched onboard the Geostationary Operational Environmental Satellite-R (GOES-R) series in the near future will offer a larger
Behrangi, Ali +5 more
openaire +3 more sources
Assessment of 13 Gridded Precipitation Datasets for Hydrological Modeling in a Mountainous Basin
Atmosphere, 2022 Precipitation measurement with high spatial and temporal resolution over highly elevated and complex terrain in the eastern part of Turkey is an essential task to manage the water structures in an optimum manner.
Hamed Hafizi, Ali Arda Sorman
doaj +1 more source
Satellite-Based Precipitation Measurement Using PERSIANN System [PDF]
, 2008 PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) is a satellite-based rainfall estimation algorithm. It uses local cloud textures from longwave infrared images of the geostationary environmental satellites to estimate surface rainfall rates based on an artificial neural network algorithm.
Hsu, Kuo-Lin, Sorooshian, Soroosh
openaire +2 more sources
European Journal of Remote Sensing, 2020 Small watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study.
Kepeng Feng +5 more
doaj +1 more source
Journal of Hydrology and Hydromechanics, 2017 The precise rainfall estimate with appropriate spatial and temporal resolutions is a key input to distributed hydrological models. However, networks of rain gauges are often sparsely distributed in developing countries. To overcome such limitations, this
Thom Vu Thi +2 more
doaj +1 more source
Deep Neural Network Cloud-Type Classification (DeepCTC) Model and Its Application in Evaluating PERSIANN-CCS [PDF]
Remote Sensing, 2020 Satellite remote sensing plays a pivotal role in characterizing hydrometeorological components including cloud types and their associated precipitation. The Cloud Profiling Radar (CPR) on the Polar Orbiting CloudSat satellite has provided a unique dataset to characterize cloud types. However, data from this nadir-looking radar offers limited capability
Vesta Afzali Gorooh +6 more
openaire +4 more sources
Validation of PERSIANN Precipitation Product Using TAWN Rain Gauge Network Over Different Agro-climatic Zones in Tamil Nadu [PDF]
Madras Agricultural Journal, 2021 Currently, several satellite-precipitation products were developed usingmultiple algorithms to estimate rainfall. This study carried out usingPrecipitation Estimation from Remotely Sensed Information using ArtificialNeural Networks (PERSIANN) product ...
Venkadesh Samykannu, Pazhanivelan, S
doaj +1 more source
Journal of Hydrology: Regional Studies, 2020 Study region: The Upper Nan River Basin, Northern Thailand Study focus: Precipitation is a major component of the hydrological cycle. A large number of remotely sensed precipitation products are used in hydro-meteorological studies. The accuracy of these
Miyuru B. Gunathilake +5 more
doaj +1 more source
Assessment of the PERSIANN-CDR Products Bias-corrected with the GPCP Datasets Versions 2.2 & 2.3 [PDF]
, 2018 Accurate precipitation estimation at fine spatial and temporal scale is crucial for climatological studies. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) is a well-known ...
Sadeghi, Mojtaba
core +1 more source
Remote Sensing, 2020 In this study, the performances of four satellite-based precipitation products (IMERG-V06 Final-Run, TRMM-3B42V7, SM2Rain-ASCAT, and PERSIANN-CDR) were assessed with reference to the measurements of in-situ gauges at daily, monthly, seasonal, and annual ...
Ali Hamza +7 more
doaj +1 more source