中国农业气象 ›› 2025, Vol. 46 ›› Issue (12): 1683-1696.doi: 10.3969/j.issn.1000-6362.2025.12.001

• 农业气候资源与气候变化栏目 •    下一篇

基于CMIP6气候模式的中国农业水热资源评估

侯伟,黄明霞,张柳红,陈小敏,李伟光,邹海平   

  1. 1.海南省气候中心/海南省南海气象防灾减灾重点实验室,海口 570203;2.国家气候中心,北京 100081;3.广东省气候中心,广州 510030
  • 收稿日期:2025-02-27 出版日期:2025-12-20 发布日期:2025-12-16
  • 作者简介:侯伟,高级工程师,研究方向为农业生态气象和气候变化,E-mail:houwei89@outlook.com
  • 基金资助:
    海南省“南海新星”科技创新人才平台项目(NHXXRCXM202355);海南省气象局科研项目(HNQXJS202404);国家自然科学基金气象联合基金项目(U2142205);中国气象局气候变化专项项目(QBZ202401)

Assessment of Agricultural Precipitation and Heat Resources in China Based on CMIP6 Climate Models

HOU Wei, HUANG Ming-xia, ZHANG Liu-hong, CHEN Xiao-min, LI Wei-guang, ZOU Hai-ping   

  1. 1.Hainan Climate Center/Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570203, China; 2.National Climate Center, Beijing 100081; 3.Climate Center of Guangdong Province, Guangzhou 510030
  • Received:2025-02-27 Online:2025-12-20 Published:2025-12-16

摘要:

基于CMIP65种气候模式,选用SSP126SSP245气候情景,以1970-2014年(历史期)中国区域高分辨率气象格点数据CN05.1基本数据集,采用Delta偏差校正、泰勒图及贝叶斯模型平均(BMA)评估2015-2050(未来期)中国农业水热资源时空变化规律,以期为优化种植制度、调整农业布局以及应对气候变化提供参考。结果表明:(1CMIP65气候模式及BMA对气温和降水量的模拟效果较好,能有效捕捉区域气候特征,BMA能有效平衡多模式在模拟气温和降水量的表现。(2SSP126SSP245情景下,1970-2050平均气温增速分别为0.37·10a−10.40·10a−1,青藏高原、西北、华北和东北地区气温升幅明显普遍超过0.4℃·10a1;年降水量呈微弱增加趋势,两种情景下分别增加5.6mm·10a14.8mm·10a1,华南、华东及东北地区增加明显(10mm·10a1,西南地区则不同程度减少。(3)与历史期相比,未来平均气温0的区域逐渐缩小,5101520等温线分别向北移动2.1°2.9°4.2°2.2°,华南地区年降水量1500mm的范围略有扩大419702050SSP245未来气候情境下0℃≥5℃≥10℃≥15℃有效积温倾向率分别为10.4℃·d·a19.3℃·d·a17.6℃·d·a15.9℃·d·a1呈温度阈值越高、有效积温升幅越小的变化特征。(5未来高海拔地区和中纬度地区有效积温低值区范围缩小,华北以南的高值区呈不同程度北扩19702050≥0℃≥5℃≥10℃≥15℃有效积温升幅10℃·d·a1的区域面积随温度阈值增加而逐渐缩小,升幅在010℃·d·a1区域的面积不断扩大。气候变化使作物生长季延长,种植界限北扩并提高复种指数,但也对冬小麦等喜凉作物生育、病虫害防控等提出新的要求,加强农业应对策略以适应未来气候变化不确定性至关重要

关键词: CMIP6, 气温, 降水量, 有效积温, 评估

Abstract:

Based on five CMIP6 climate models and using the SSP126 and SSP245 scenarios, this study employed the highresolution meteorological grid data for China (CN05.1) from 1970 to 2014 (historical period) as the baseline dataset. Delta bias correction, Taylor diagram and Bayesian model averaging (BMA) were used to assess the spatiotemporal changes in agricultural precipitation and heat resources in China from 2015 to 2050. The aim was to provide scientific evidence for optimizing planting systems, adjusting agricultural layout and adapting to climate change. The results showed that: (1) the five CMIP6 climate models and BMA ensemble demonstrate good performance in simulating temperature and precipitation, effectively capturing regional climate characteristics, with better accuracy in temperature simulations. BMA could effectively balance the performance of multiple models in simulating temperature and precipitation. (2) Under the SSP126 and SSP245 scenarios, the average temperature increase rate from 1970 to 2050 was 0.37°C·10y1 and 0.40°C·10y1, respectively. With the most significant temperature increasing in the Tibetan plateau, northwest, north and northeast regions, generally exceeding 0.4°C·10y1. Annual precipitation showed a slight increasing trend, with rates of 5.6mm·10y1 and 4.8mm·10y1. Significant increases (≥10mm·10y1) were observed in south, east and northeast regions, while the southwest region showed a varying degrees of decrease. (3) Compared with the historical period (19702014), the regions with an average temperature ≤0°C during 20152050 showed significant warming, with the area gradually shrinking. The isotherms for 5°C, 10°C, 15°C and 20°C moved northward by 2.1°, 2.9°, 4.2° and 2.2°, respectively. The region in south China with annual precipitation ≥1500mm slightly expands. (4) Under the SSP245 scenario during From 1970 to 2050, the trend rates of effective accumulated temperature for thresholds ≥0°C, ≥5°C, ≥10°C, and ≥15°C were 10.4°C·d·y1, 9.3°C·d·y1, 7.6°C·d·y1 and 5.9°C·d·y1, respectively, showing a pattern in which higher temperature thresholds correspond to smaller increases in effective accumulated temperatures. (5) From the distribution of effective accumulated temperature at different thresholds, the low value areas in highaltitude and midlatitude regions shrinked in the future, while the high value areas in south China expanded to varying degrees.  From 1970 to 2050, the area with an increase in effective accumulated temperature ≥10·d·y1 for thresholds of ≥0, 5, 10 and ≥15 gradually decreased as the temperature threshold rises, while the area with an increase in the range of 010·d·y1 continued to expand. Climate change has led to an extended growing season, a northward expansion of planting boundaries and an increase in the cropping index. However, it also presented new challenges for the growth of coolseason crops such as winter wheat, pest control and disease prevention. Strengthening agricultural adaptation strategies to cope with the uncertainties of future climate change is crucial.

Key words: CMIP6, Temperature, Precipitation, Effective accumulated temperature, Assessment