Modelling deep convective activity using lightning clusters and machine learning-Reference-Cited by-同舟云学术

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Modelling deep convective activity using lightning clusters and machine learning

Published:2021-07-13 Issue:2 Volume:42 Page:952-973
ISSN:0899-8418
Container-title:International Journal of Climatology
language:en
Short-container-title:Intl Journal of Climatology

Author:

Shi Manxing¹^ORCID,Zhang Wei¹^ORCID,Fan Peng²³^ORCID,Chen Qihao¹^ORCID,Liu Zhipeng¹^ORCID,Li Qin¹^ORCID,Liu Xiuguo¹^ORCID

Affiliation:

1. School of Geography and Information Engineering China University of Geosciences Wuhan China

2. NARI Group (State Grid Electric Power Research Institute) Co., Ltd. Nanjing China

3. Wuhan NARI Limited Liability Company, State Grid Electric Power Research Institute Wuhan China

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7282

Reference106 articles.

1. Probabilistic Forecasts of Mesoscale Convective System Initiation Using the Random Forest Data Mining Technique

2. An empirical model relating U.S. monthly hail occurrence to large-scale meteorological environment

3. A review of severe thunderstorms in Australia

4. A climatology of Australian severe thunderstorm environments 1979-2011: inter-annual variability and ENSO influence

5. Lightning Prediction for Australia Using Multivariate Analyses of Large-Scale Atmospheric Variables

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1. Improved tropical deep convective cloud detection using MODIS observations with an active sensor trained machine learning algorithm;Remote Sensing of Environment;2023-11

2. Evaluation and application analysis of kilometer-scale convective parameters derived from a statistical downscaling method over Central China;Climate Dynamics;2023-05-15

3. Thunderstorm Activity over the Qinghai–Tibet Plateau Indicated by the Combined Data of the FY-2E Geostationary Satellite and WWLLN;Remote Sensing;2022-06-15

4. Using DBSCAN-RF Algorithm and Multi-source Features to Model Deep Convection in Hubei, China;Spatial Data and Intelligence;2022

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