中国农业气象 ›› 2026, Vol. 47 ›› Issue (8): 1321-1335.doi: 10.3969/j.issn.1000-6362.2026.08.013

• 农业气象灾害栏目 • 上一篇    下一篇

1971−2022年浙江寒冷事件时空变异特征及其对农业影响

肖晶晶,马浩,郭芬芬,李正泉,张育慧,王治海,刘赞,马尚谦   

  1. 1. 浙江省气候中心,杭州 310052;2. 龙游国家一级农业气象试验站,龙游 324400;3. 自然资源部第二海洋研究所/自然资源部海洋空间资源管理技术重点实验室,杭州 310012
  • 收稿日期:2025-07-01 出版日期:2026-08-20 发布日期:2026-08-19
  • 作者简介:肖晶晶,E-mail:xiaojingjing2005@163.com
  • 基金资助:
    浙江省自然科学基金项目(LMS26D050003);浙江省自然科学基金联合重大项目(LZJMD24D050002);浙江省基础公益研究计划项目(LZJMZ23D050001;LGF22D050007);上海市自然科学基金项目(24ZR1492500);浙江省气象科技计划项目(2022ZD07)

Spatiotemporal Characteristics of Cold Events and Their Impacts on Agriculture in Zhejiang Province from 1971 to 2022

XIAO Jing-jing, MA Hao, GUO Fen-fen, LI Zheng-quan, ZHANG Yu-hui, WANG Zhi-hai, LIU Zan, MA Shang-qian   

  1. 1. Zhejiang Climate Centre, Hangzhou 310052, China; 2. Longyou National First-Class Agrometeorological Experimental Station, Longyou 324400; 3. Second Institute of Oceanography, Ministry of Natural Resources/Key Laboratory of Ocean Space Resource Management Technology, Ministry of Natural Resources, Hangzhou 310012
  • Received:2025-07-01 Online:2026-08-20 Published:2026-08-19

摘要:

基于19712022年浙江省66个气象站逐日最低气温和BCCCSM2MR模式预估数据,采用绝对阈值法和一倍标准差法构建浙江寒冷事件序列,利用气候统计方法,揭示浙江寒冷事件时空变异特征,定量评估未来(20232100年)SSP245SSP585情景下农业冷冻害受灾风险,以期为区域气候适应和灾害风险管理提供决策支持。结果表明:19712022年浙江年平均寒冷日数、寒冷事件发生频次、极端寒冷事件频次均呈显著下降趋势(P<0.01),气候倾向率分别为6.1d·10a10.6·10a10.2·10a1寒冷日数、寒冷事件发生频次和极端寒冷事件频次空间差异显著,分别呈北多南少、西多东少”“东北多西南少”“中北多西南少的分布特征。19712022年春季和秋季寒冷事件发生频次的气候倾向率分别为0.4·10a10.3·10a1P<0.01,冬季无显著变化趋势。极端寒冷事件EOF分析表明,第一模态为全省一致型,方差贡献达79.7%第二第四模态依次为西北东南反相型、近三极子型、南北反相型BCCCSM2MR模式SSP245SSP585情景下,20232100年浙江极端寒冷事件年平均发生频次分别为0.9次和1.0次,气候倾向率为0.1·10a10.2·10a1P<0.01,空间分布呈“南高北低、内陆高沿海低”的特征,高值区分布在浙西南地区。20232100SSP245情景下,未来78a寒冷事件可能导致浙江19a农业冷冻害受灾率≥5%、2a的农业冷冻害成灾率>5%,其中2030年和2066年农业冷冻害受灾率分别为18.1%25.9%,成灾率分别为6.7%11.0%SSP585情景下,未来78a中寒冷事件可能导致17a农业冷冻害受灾率≥5%3a农业冷冻害成灾率>5%,其中2079年农业冷冻害受灾率24.9%、成灾率11.9%

关键词: 寒冷日, 寒冷事件, 气候变化, 农业, CMIP6

Abstract:

Based on daily minimum temperature of 66 meteorological stations in Zhejiang province from 1971 to 2022 and projected results stem the BCCCSM2MR model, a series of cold events for Zhejiang was constructed using the absolute threshold values and standard deviations. Furthermore, spatiotemporal variability of cold events was investigated by diagnostic and statistical methods, and agricultural freezing risk under the SSP245 and SSP585 scenarios during 20232100 was quantitatively assessed in order to effectively support regional climate adaptation and disaster risk management. It was found that during 19712022, the annual mean number of cold days, frequency of cold events, and frequency of extreme cold events in Zhejiang all exhibited significant decreasing trends (P<0.01), with decreasing rates of 6.1d·10y1, 0.6times·10y1 and 0.2times·10y1, respectively. There displayed distinct spatial differences for cold days, cold events, and extreme cold events, with showing patterns of "more in the north and less in the south, more in the west and less in the east" "more in the northeast and less in the southwest" and "more in the centralnorth and less in the southwest", respectively. As for the long-term trends, climatic tendency rates of cold events' frequency in spring and autumn were 0.4times·10y1 and 0.3times·10y1 (P<0.01) respectively, while no significant trend was observed in winter. Empirical orthogonal function (EOF) analysis of extreme cold events indicated that the first mode was a province-wide consistent pattern with a variance contribution of 79.7%, and the second, third and fourth modes exhibited the northwestsoutheast dipole patterns, neartripl and northsouth dipole, respectively. In the projection results of the BCCCSM2MR model, under the SSP245 and SSP585 scenario, the annual average frequency of extreme cold events in Zhejiang during 2023−2100 would be 0.9times and 1.0times with climatic tendency rates of 0.1times·10y1 and 0.2times·10y1 (P<0.01), respectively. During the same period, spatial distribution of the cumulative frequency of extreme cold events under SSP245 and SSP585 scenario indicated that a south-north gradient (higher in the south and lower in the north) and an inlandcoastal gradient (higher inland and lower along the coast), and the highvalues would be located in southwestern Zhejiang. Under the SSP245 scenario, cold events could result in an agricultural freezingaffected rate ≥5% in 19y and a freezing-suffering rate >5% in 2y over Zhejiang in the future 78 years. Especially, the agricultural freezingaffected rate would reach 18.1% and 25.9%, and the freezingsuffering rate would be 6.7% and 11.0% in 2030 and 2066, respectively. Under the scenario of SSP585, there might be 17y with an agricultural freezingaffected >5% and 3y with a freezingsuffering rate >5%. In particular, the agricultural freezingaffected rate would be 24.9% and the freezingsuffering rate would be 11.9% in 2079.

Key words: Cold day, Cold event, Climate Change, Agriculture, CMIP6