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基于CMIP6模式优化集合平均预估21世纪全球陆地生态系统总初级生产力变化
引用本文:黄禄丰,朱再春,黄萌田,赵茜,马伟蕊,曾辉. 基于CMIP6模式优化集合平均预估21世纪全球陆地生态系统总初级生产力变化[J]. 气候变化研究进展, 2021, 17(5): 514-524. DOI: 10.12006/j.issn.1673-1719.2020.221
作者姓名:黄禄丰  朱再春  黄萌田  赵茜  马伟蕊  曾辉
作者单位:北京大学深圳研究生院城市规划与设计学院,深圳 518055;中国气象科学研究院灾害天气国家重点实验室,北京 100081
基金项目:国家自然科学基金项目(41901122);中国气象科学研究院基本业务费专项资金“气候变化对中国旱地生态系统变化的影响研究”(2020Y004)
摘    要:利用国际耦合模式比较计划第六阶段(CMIP6)中18个地球系统模式总初级生产力(GPP)模拟数据,基于传统的多模式集合平均(MME)和可靠集合平均方法(REA),在4个未来情景(SSP1-2.6,SSP2-4.5,SSP3-7.0和SSP5-8.5)下预估了21世纪全球陆地生态系统GPP的变化量,并分析了GPP变化的驱动因子。研究结果表明:在4个未来情景下,基于REA方法预估的全球陆地生态系统年GPP在未来时期(2068—2100年)比历史时期(1982—2014年)分别增长了(14.85±3.32)、(28.43±4.97)、(37.66±7.61)和(45.89±9.21)Pg C,其增量大小和不确定性都明显低于MME方法。在4个情景下,大气CO2浓度增长对GPP变化的贡献最大,基于REA方法计算的贡献占比分别为140%、137%、115%和75%;除SSP5-8.5(24%)外,其他情景下升温均导致全球陆地生态系统GPP降低(-42%、-37%、-16%),部分抵消了CO2施肥效应的正面贡献。温度的影响存在纬度差异:升温在低纬度地区对GPP有负向贡献,在中高纬度地区为正向贡献。降水和辐射变化对GPP变化的贡献相对较小。

关 键 词:总初级生产力(GPP)  地球系统模式  国际耦合模式比较计划第六阶段(CMIP6)  可靠集合平均(REA)
收稿时间:2020-09-21
修稿时间:2020-12-10

Projection of gross primary productivity change of global terrestrial ecosystem in the 21st century based on optimal ensemble averaging of CMIP6 models
HUANG Lu-Feng,ZHU Zai-Chun,HUANG Meng-Tian,ZHAO Qian,MA Wei-Rui,ZENG Hui. Projection of gross primary productivity change of global terrestrial ecosystem in the 21st century based on optimal ensemble averaging of CMIP6 models[J]. Progressus Inquisitiones DE, 2021, 17(5): 514-524. DOI: 10.12006/j.issn.1673-1719.2020.221
Authors:HUANG Lu-Feng  ZHU Zai-Chun  HUANG Meng-Tian  ZHAO Qian  MA Wei-Rui  ZENG Hui
Affiliation:1.School of Urban Planning and Design, Shenzhen Graduate School of Peking University, Shenzhen 518055, China2 State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Abstract:Using data set of 18 Earth system models in CMIP6, the global terrestrial annual gross primary productivity (GPP) changes in the 21st century were projected, and its driving factors were analyzed under four future scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) based on traditional Multi-Model Ensemble Mean (MME) and Reliability Ensemble Averaging (REA) methods. The results show that under the four scenarios, the global terrestrial GPP predicted by the REA method in the future period (2068-2100) would increase by (14.85±3.32), (28.43±4.97), (37.66±7.61), and (45.89±9.21) Pg C compared with that in historical period (1982-2014), where the increment magnitude and uncertainty are significantly lower than those based on MME method. Attribution analysis shows that under the four scenarios, atmospheric CO2 concentration increasing contributes the most to the changes of GPP, whose proportion calculated based on REA method are 140%, 137%, 115% and 75%. With the exception of SSP5-8.5 (24%), warming would lead to global GPP decreasing under other scenarios (-42%, -37%, -16%), which partially offsets the positive contribution of CO2 fertilization effects. There are different latitudinal patterns of the effect of temperature: warming in low latitudes contributes negatively to GPP changes, while it has positive contribution in middle and high latitudes. Precipitation and radiation changes contribute relatively little to GPP changes.
Keywords:Gross primary productivity (GPP)  Earth system models  CMIP6  Reliability ensemble averaging (REA)  
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