{"title":"中国南方春季气温快速变率:特征、年代际趋势及气候对作物产量的影响","authors":"Xianke Yang, Yixuan Zhang, Haosu Tang, Ping Huang, Xiaoxia Ling, Shaobing Peng, Dongliang Xiong","doi":"10.1002/joc.8880","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Climate-related risks are shaped not only by changes in mean temperatures, but also by temperature variability, which raises the likelihood of extreme weather events with profound impacts on society and ecosystems. Previous studies have documented contrasting seasonal trend differences in summer and winter temperature variability across most land areas. However, spring—a phenologically sensitive season for agricultural systems—has received limited attention for its temperature variability. Focusing on the major rice-growing regions in southern China, this study employs three indices—daily temperature standard deviation (STD), day-to-day temperature variability (DTD) and rapid cooling events (RCE)—to analyse the decadal trends and causes of spring temperature variability and assess its climate effects on rice yield anomalies. Our results reveal decadal trends in the spatial distribution of temperature variability, with increasing frequency and intensity in the Yangtze River Basin and Yunnan Province, and a decreasing trend across much of South China, closely following regional climatological patterns. Overall, the frequency and intensity of RCE trend exhibit a “strong gets weaker, weak gets stronger” pattern, likely linked to increased STD trends caused by spatial non-uniformity of warming. Through a multiple regression statistical model employing dominance analysis, we find that climate factors, including both mean climate and climate variability, explained 19%–45% of the variance in provincial rice yield anomalies, with up to 13% of the explained variance attributable to spring climate factors related to temperature variability. This study underscores the critical role of spring temperature variability in climate resilience, highlights the urgent need to enhance the adaptability of agricultural systems to extreme climate events.</p>\n </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 9","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spring Rapid Temperature Variability in Southern China: Characteristics, Decadal Trend and Associated Climate Impacts on Crop Yield\",\"authors\":\"Xianke Yang, Yixuan Zhang, Haosu Tang, Ping Huang, Xiaoxia Ling, Shaobing Peng, Dongliang Xiong\",\"doi\":\"10.1002/joc.8880\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Climate-related risks are shaped not only by changes in mean temperatures, but also by temperature variability, which raises the likelihood of extreme weather events with profound impacts on society and ecosystems. Previous studies have documented contrasting seasonal trend differences in summer and winter temperature variability across most land areas. However, spring—a phenologically sensitive season for agricultural systems—has received limited attention for its temperature variability. Focusing on the major rice-growing regions in southern China, this study employs three indices—daily temperature standard deviation (STD), day-to-day temperature variability (DTD) and rapid cooling events (RCE)—to analyse the decadal trends and causes of spring temperature variability and assess its climate effects on rice yield anomalies. Our results reveal decadal trends in the spatial distribution of temperature variability, with increasing frequency and intensity in the Yangtze River Basin and Yunnan Province, and a decreasing trend across much of South China, closely following regional climatological patterns. Overall, the frequency and intensity of RCE trend exhibit a “strong gets weaker, weak gets stronger” pattern, likely linked to increased STD trends caused by spatial non-uniformity of warming. Through a multiple regression statistical model employing dominance analysis, we find that climate factors, including both mean climate and climate variability, explained 19%–45% of the variance in provincial rice yield anomalies, with up to 13% of the explained variance attributable to spring climate factors related to temperature variability. This study underscores the critical role of spring temperature variability in climate resilience, highlights the urgent need to enhance the adaptability of agricultural systems to extreme climate events.</p>\\n </div>\",\"PeriodicalId\":13779,\"journal\":{\"name\":\"International Journal of Climatology\",\"volume\":\"45 9\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/joc.8880\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Climatology","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joc.8880","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Spring Rapid Temperature Variability in Southern China: Characteristics, Decadal Trend and Associated Climate Impacts on Crop Yield
Climate-related risks are shaped not only by changes in mean temperatures, but also by temperature variability, which raises the likelihood of extreme weather events with profound impacts on society and ecosystems. Previous studies have documented contrasting seasonal trend differences in summer and winter temperature variability across most land areas. However, spring—a phenologically sensitive season for agricultural systems—has received limited attention for its temperature variability. Focusing on the major rice-growing regions in southern China, this study employs three indices—daily temperature standard deviation (STD), day-to-day temperature variability (DTD) and rapid cooling events (RCE)—to analyse the decadal trends and causes of spring temperature variability and assess its climate effects on rice yield anomalies. Our results reveal decadal trends in the spatial distribution of temperature variability, with increasing frequency and intensity in the Yangtze River Basin and Yunnan Province, and a decreasing trend across much of South China, closely following regional climatological patterns. Overall, the frequency and intensity of RCE trend exhibit a “strong gets weaker, weak gets stronger” pattern, likely linked to increased STD trends caused by spatial non-uniformity of warming. Through a multiple regression statistical model employing dominance analysis, we find that climate factors, including both mean climate and climate variability, explained 19%–45% of the variance in provincial rice yield anomalies, with up to 13% of the explained variance attributable to spring climate factors related to temperature variability. This study underscores the critical role of spring temperature variability in climate resilience, highlights the urgent need to enhance the adaptability of agricultural systems to extreme climate events.
期刊介绍:
The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions