{"title":"Preferable weather patterns to brown planthopper advection to Kyushu and its effect of climate change","authors":"Keito OISHI, Masaru INATSU, Sho KAWAZOE","doi":"10.2480/agrmet.d-23-00022","DOIUrl":null,"url":null,"abstract":"</p><p> The brown planthopper, <i>Nilaparvata lugens</i> (Stål), a type of rice pest, immigrates from southern China to western Japan by drifting in the southwesterly environment during the Baiu/Meiyu rainy season. This study aims to investigate the preferable weather patterns for the immigration of brown planthoppers across the East China Sea. We conducted immigration runs using an advection diffusion model for brown planthoppers and projected the possibility of them landing in Kyushu in the model run onto 64 weather map patterns typically observed in June and July, identified by the self-organizing map analysis. The results showed that the immigration occurred under two specific weather map patterns: flow stagnation around western Japan and a low-level jet blowing over the East China Sea. Consistency between landing cases in model runs and the occurrence of the two weather patterns was found in the intraseasonal and interannual variability. We also estimated the change in the frequency of brown planthopper arrival in Kyushu based on the climate change dataset, the database for Policy Decision Making for Future climate change (d4PDF). It was found that the flow stagnation patterns increased in response to global change, at least in the d4PDF dataset. Finally, risk assessment for temperature change and a comparison with trap observations were discussed.</p>\n<p></p>","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Agricultural Meteorology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.2480/agrmet.d-23-00022","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The brown planthopper, Nilaparvata lugens (Stål), a type of rice pest, immigrates from southern China to western Japan by drifting in the southwesterly environment during the Baiu/Meiyu rainy season. This study aims to investigate the preferable weather patterns for the immigration of brown planthoppers across the East China Sea. We conducted immigration runs using an advection diffusion model for brown planthoppers and projected the possibility of them landing in Kyushu in the model run onto 64 weather map patterns typically observed in June and July, identified by the self-organizing map analysis. The results showed that the immigration occurred under two specific weather map patterns: flow stagnation around western Japan and a low-level jet blowing over the East China Sea. Consistency between landing cases in model runs and the occurrence of the two weather patterns was found in the intraseasonal and interannual variability. We also estimated the change in the frequency of brown planthopper arrival in Kyushu based on the climate change dataset, the database for Policy Decision Making for Future climate change (d4PDF). It was found that the flow stagnation patterns increased in response to global change, at least in the d4PDF dataset. Finally, risk assessment for temperature change and a comparison with trap observations were discussed.
期刊介绍:
For over 70 years, the Journal of Agricultural Meteorology has published original papers and review articles on the science of physical and biological processes in natural and managed ecosystems. Published topics include, but are not limited to, weather disasters, local climate, micrometeorology, climate change, soil environment, plant phenology, plant response to environmental change, crop growth and yield prediction, instrumentation, and environmental control across a wide range of managed ecosystems, from open fields to greenhouses and plant factories.