Results 171 to 180 of about 27,882 (229)

Application research of convolutional neural network and its optimization in lightning electric field waveform recognition. [PDF]

Sci Rep
Wang C, Zhang X, Yang H, Guo J, Xu J, Sun Z.   +5 more
europepmc   +1 more source

Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models. [PDF]

Sci Rep
Shmuel A, Lazebnik T, Glickman O, Heifetz E, Price C.   +4 more
europepmc   +1 more source

An intelligent IoT-machine learning framework for wildfire detection and prediction using a hybrid RF-XGB model. [PDF]

Sci Rep
Radhi AA, Ibrahim AA.
europepmc   +1 more source

Transcribing historical Canadian weather data. [PDF]

Sci Data
Slonosky V, Black R, Podolsky L, Wang X, Cheng V.   +4 more
europepmc   +1 more source

Storms Are an Important Driver of Change in Tropical Forests. [PDF]

Ecol Lett
Gora EM, McGregor IR, Muller-Landau HC, Burchfield JC, Cushman KC, Rubio VE, Mori GB, Sullivan MJP, Chmielewski MW, Esquivel-Muelbert A.   +9 more
europepmc   +1 more source

Thunderstorm charge structures favouring cloud-to-ground lightning [PDF]

Atmospheric Research, 2021
Thunderstorm electrical structures favouring cloud-to-ground lightning were investigated through a Lightning Mapping Array (LMA), an accurate three-dimensional lightning location system that allows inferring the heights of the regions of charge.
Nicolau Pineda, Jesus Alberto López Trujillo, Joan Montanya   +2 more
exaly   +3 more sources

In‐Cloud Discharge of Positive Cloud‐To‐Ground Lightning and Its Influence on the Initiation of Tower‐Initiated Upward Lightning [PDF]

Journal of Geophysical Research D: Atmospheres, 2021
The data supports the manuscript entitled “In-cloud discharge of positive cloud-to-ground lightning and its influence on the initiation of tower-initiated upward lightning,” and MATLAB can open these *.fig files.
Rubin Jiang, Abhay Srivastava, Shanfeng Yuan   +2 more
exaly   +2 more sources

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Lightning warnings with NLDN cloud and cloud-to-ground lightning data

2014 International Conference on Lightning Protection (ICLP), 2014
Previous studies (Holle and Demetriades 2010; Murphy and Holle 2008) have evaluated the performance of the U.S. National Lightning Detection Network (NLDN) with respect to warnings of cloud-to-ground lightning at specific locations such as airports. The statistics used to evaluate warning performance have included probability of detection (POD), false ...
Holle, Ronald L, Demetriades, Nicholas W S, Nag, Amitabh   +2 more
openaire   +1 more source