中国农业气象 ›› 2022, Vol. 43 ›› Issue (09): 681-691.doi: 10.3969/j.issn.1000-6362.2022.09.001

• 农业气候资源与气候变化栏目 •    下一篇

2001-2100年中国区域季节平均温度变化的时空格局

付大容,陈笑蝶,刘亦婷,刘力,彭守璋   

  1. 1.西北农林科技大学资源环境学院,杨凌 712100;2.浙江树人学院,绍兴 310015;3. 西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室,杨凌 712100
  • 收稿日期:2021-11-25 出版日期:2022-09-20 发布日期:2022-09-19
  • 通讯作者: 彭守璋,研究员,博士,主要从事遥感与GIS应用研究. E-mail:szp@nwafu.edu.cn
  • 作者简介:付大容,E-mail:fdr2955776701@163.com
  • 基金资助:
    国家自然科学基金(42077451);陕西省自然科学基金项目(2020JQ-418);内陆河流域中科院重点实验室开放基金(KLEIRB-ZS-20-04);2021浙江软科学计划研究项目“生态文明视域下浙江典型湾区绿色发展评价研究-以三门湾为例”(2021C35083)

Spatiotemporal Patterns of Seasonal Mean Temperature Variations in China During 2001−2100

FU Da-rong, CHEN Xiao-die, LIU Yi-ting, LIU Li, PENG Shou-zhang   

  1. 1. College of Resources and Environment, Northwest A&F University, Yangling 712100, China; 2.Zhejiang Shuren University, Shaoxing 310015; 3. State Key Laboratory of Soil Erosion and Dryland Agriculture on the Loess Plateau, Northwest A&F University, Yangling 712100
  • Received:2021-11-25 Online:2022-09-20 Published:2022-09-19

摘要: 基于1km分辨率长时间序列温度数据集,采用距平法、Mann-Kendall趋势检验法和Sen’s斜率估计法,分析四季平均气温在历史时期(2001−2020年)与未来时期(2021−2100年)低强迫情景(SSP119)、中等强迫情景(SSP245)和高强迫情景(SSP585)下的变化幅度和变化趋势的时空格局,以期为气候变暖背景下制定详细的区域适应性策略提供依据。结果表明:(1)相比历史时期,未来时期在3个情景下的四季均温总体上升,且夏季增温区域面积最大,其中SSP119情景下增温1~2℃的区域占66.70%,SSP245和SSP585情景下增加2℃以上的区域分别占37.37%和99.06%;同时,3个SSP情景下的季节均温的整体变化幅度具有显著差异,SSP119情景下较缓和,SSP245情景次之,SSP585情景增温幅度最大。(2)在历史时期,相比其他季节,春季均温的显著上升速率最快(0.68±0.24℃∙10a−1),且面积占比最大(14.44%),主要分布于华北、云贵川和江浙局部区域。(3)在未来时期,中国区域季节均温呈总体上升趋势,且具有显著的空间差异;其中,在SSP119情景下,春季和冬季均温显著上升的区域主要集中于中国南部和青藏高原局部区域,面积占比分别为29.03%和25.58%,在SSP245和SSP585情景下,中国所有区域的季节均温呈显著上升趋势;在SSP585情景下,北方的季节均温显著上升速率比南方快,全国区域在冬季的显著上升速率最快(0.66±0.09℃∙10a−1)。

关键词: 季节均温, 时空格局, 变化趋势, SSP情景, 中国区域

Abstract: Based on the 1-km resolution long time series temperature data set, the spatial and temporal patterns of the magnitude and trend of the four-season mean temperature changes in the historical period (2001−2020), and in the future period (2021−2100) under the low forcing scenario (SSP119), medium forcing scenario (SSP245) and high forcing scenario (SSP585) are analyzed using the distance level method, Mann-Kendall trend test method and Sen's slope estimation method, with a view to providing a basis for developing detailed regional adaptation strategies in the context of climate warming. The results show that: (1) compared with the historical period, the average temperature of the four seasons in the future will increase in general under the three scenarios, and the area with the largest increase in summer is 66.70% under SSP119, 37.37% and 99.06% under SSP245 and SSP585, respectively. At the same time, the overall variation range of seasonal mean temperature under the three SSP scenarios is significantly different, which is moderated under SSP119, followed by SSP245, and the largest increase range under SSP585. (2) In the historical period, compared with other seasons, the significant rise in mean temperature in spring had the fastest rate (0.68±0.24℃∙10y−1) and the largest area share (14.44%), mainly distributed in North China, Yunnan, Guizhou, Jiangsu and Zhejiang provinces. (3) In the future period, the regional seasonal mean temperature in China shows an overall rising trend with significant spatial differences; among them, under the SSP119 scenario, the regions with significantly rising mean temperature in spring and winter are mainly concentrated in southern China and the local area of the Qinghai-Tibet Plateau, accounting for 29.03% and 25.58% of the area, respectively; under the SSP245 and SSP585 scenarios, the seasonal mean temperature in all regions of China shows a significant upward trend; under the SSP585 scenario, the seasonal mean temperature in the north increases at a faster rate than that in the south, and the national region has the fastest significant rate of increase in winter (0.66±0.09℃∙10y−1).

Key words: Seasonal mean temperature, Spatio-temporal pattern, Change trend, SSP scenarios, China