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The weather radar is one of the most effective remote sensing devices for the monitoring and early warning of tornadoes. The existing tornado detection algorithms based on radar data are unsupervised and have strict multi-altitude constraints, such as the tornado detection algorithm based on tornado vortex signatures (TDA-TVS), which may lead to high false alarm rates, and the performance of the detection algorithm is greatly affected by the radar data quality control algorithm. A novel TDA-RF algorithm based on the random forest (RF) classification algorithm is proposed for real-time tornado identification of the S-band China new generation of Doppler weather radar (CINRAD-SA). The TDA-RF algorithm uses velocity features to identify tornadoes and adds features related to reflectivity and velocity spectrum width in radar level-II data. Historical CINRAD-SA tornado data from 2006\u20132015 are used to construct the tornado dataset and train the TDA-RF model. The performance of TDA-RF is evaluated using CINRAD-SA data from five tornadoes of 2016\u20132020 with enhanced Fujita(EF) scale ratings ranging from EF0 to EF4 and distances from 10 to 130 km to the radar. TDA-RF performs well overall with the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of 71%, 29%, and 55%, respectively. Moreover, the TDA-RF improves POD and CSI, and reduces FAR compared to the TDA-TVS. The maximum tornado early-warning time of TDA-RF is 17 min, and the average is 6 min; TDA-RF can provide classification probability according to the tornado generation and development process to facilitate tracking ability.<\/jats:p>","DOI":"10.3390\/rs14194909","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"4909","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Application of Random Forest Algorithm on Tornado Detection"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1123-2790","authenticated-orcid":false,"given":"Qiangyu","family":"Zeng","sequence":"first","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8295-506X","authenticated-orcid":false,"given":"Zhipeng","family":"Qing","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Zhu","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fugui","family":"Zhang","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0090-2840","authenticated-orcid":false,"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6361-0429","authenticated-orcid":false,"given":"Yin","family":"Liu","sequence":"additional","affiliation":[{"name":"Jiangsu Meteorological Observation Center, Nanjing 210041, China"},{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhao","family":"Shi","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiu","family":"Yu","sequence":"additional","affiliation":[{"name":"CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China"},{"name":"College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-021-81143-5","article-title":"Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices","volume":"11","author":"Nouri","year":"2021","journal-title":"Sci. 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