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基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响

刘瑞金 廖宏 常文渊 张天航 靳少非

刘瑞金, 廖宏, 常文渊, 张天航, 靳少非. 基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响[J]. 大气科学, 2017, 41(4): 739-751. doi: 10.3878/j.issn.1006-9895.1612.16218
引用本文: 刘瑞金, 廖宏, 常文渊, 张天航, 靳少非. 基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响[J]. 大气科学, 2017, 41(4): 739-751. doi: 10.3878/j.issn.1006-9895.1612.16218
Ruijin LIU, Hong LIAO, Wenyuan CHANG, Tianhang ZHANG, Shaofei JIN. Impact of Climate Change on Aerosol Concentrations in Eastern China Based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) Datasets[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(4): 739-751. doi: 10.3878/j.issn.1006-9895.1612.16218
Citation: Ruijin LIU, Hong LIAO, Wenyuan CHANG, Tianhang ZHANG, Shaofei JIN. Impact of Climate Change on Aerosol Concentrations in Eastern China Based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) Datasets[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(4): 739-751. doi: 10.3878/j.issn.1006-9895.1612.16218

基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响

doi: 10.3878/j.issn.1006-9895.1612.16218
基金项目: 

国家重点基础研究发展计划(973计划) 2014CB441202

国家自然科学基金项目 41475137

国家自然科学基金项目 91544219

详细信息
    作者简介:

    刘瑞金, 男, 1984年出生, 博士研究生, 主要从事气溶胶气候效应及气候变化的模拟研究。E-mail:liurj@mail.iap.ac.cn

    通讯作者:

    廖宏, E-mail:hongliao@mail.iap.ac.cn

  • 中图分类号: P401

Impact of Climate Change on Aerosol Concentrations in Eastern China Based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) Datasets

Funds: 

National Basic Research Program of China (973 Program) 2014CB441202

National Natural Science Foundation of China 41475137

National Natural Science Foundation of China 91544219

  • 摘要: 气候变化引起的地面气溶胶浓度变化与区域空气质量密切相关。本文利用“国际大气化学—气候模式比较计划”(Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP)中4个模式的试验数据分析了RCP8.5情景下2000~2100年气候变化对中国气溶胶浓度的影响。结果显示,在人为气溶胶排放固定在2000年、仅考虑气候变化的影响时,2000~2100年气候变化导致中国北部地区(31°N~45°N, 105°E~122°E)硫酸盐、有机碳和黑碳气溶胶分别增加28%、21%和9%,硝酸盐气溶胶在中国东部地区减少30%。气候变化对细颗粒物(PM2.5)浓度的影响有显著的季节变化特征,冬季PM2.5浓度在中国东部减少15%,这主要是由硝酸盐气溶胶在冬季的显著减少造成的;夏季PM2.5浓度在中国北部地区增加16%,而长江以南地区减少为9%,这可能与模式模拟的未来东亚夏季风环流的增强有关。
  • 图  1  中国气象局大气成分观测网站点分布和本文研究区域。三角形代表观测站点位置,研究区域包括中国北部(31°N~45°N, 105°E~122°E)、南部(20°N~31°N, 105°E~122°E)和东部地区(北部+南部,20°N~45°N, 105°E~122°E)

    Figure  1.  Geographic locations of observational sites (triangles) in China Meteorological Administration Atmosphere Watch Network (CAWNET) and the study domains of northern China (31°N-45°N, 105°E-122°E), southern China (20°N-31°N, 105°E-122°E), and eastern China (20°N-45°N, 105°E-122°E)

    图  2  多模式平均的当前气候态下不同季节气溶胶地表浓度(单位:μg m-3)的空间分布:(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5

    Figure  2.  The present-day multi-model and seasonal mean surface-layer concentrations (units: μg m-3) of aerosols over East Asia: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5 (fine particulate matter)

    图  3  (a)模式模拟和(b)MODIS观测的550 nm波长年平均气溶胶光学厚度空间分布。图b中灰色部分表示缺少观测数据

    Figure  3.  The annual mean aerosol optical thickness at 550 nm wavelength over China from MODIS (Moderate Resolution Imaging Spectroradiometer) and ACCMIP models. The gray areas in Fig. b represent the observation data are missing

    图  4  模式模拟的(左列)和NCEP再分析资料的(右列)中国地区年平均(a)温度(单位:℃)、(b)绝对湿度(单位:g kg-1)、(c)降水(单位:mm d-1)和(d)850 hPa风场(单位:m s-1)的分布

    Figure  4.  Distributions of annual mean (a) surface temperature (units: ℃), (b) specific humidity (units: g kg-1), (c) precipitation (units: mm d-1), and (d) 850-hPa wind (units: m s-1) over China from ACCMIP models (left column) and NCEP data (right column)

    图  5  ACCMIP模式模拟的RCP8.5情景下2000~2100年中国季节平均的(a)温度(单位:℃)、(b)绝对湿度(单位:g kg-1)、(c)降水(单位:mm d-1)和(d)850 hPa风场(单位:m s-1)的变化特征。(a)温度和(b)绝对湿度的变化全部通过了95%信度水平检验(t检验),(c)降水变化图中打点区域表示通过了95%信度水平检验

    Figure  5.  ACCMIP models-simulated changes in seasonal mean (a) surface temperature (units: ℃), (b) specific humidity (units: g kg-1), (c) precipitation (units: mm d-1), and (d) 850-hPa wind (units: m s-1) over China during 2000-2100 under the RCP8.5 scenario. Projected changes in surface temperature in Fig. a and specific humidity in Fig. b are all statistically significant at the 95% confidence level based on the Student's t test. The dotted areas in Fig. c represent statistically significant changes at the 95% confidence level based on the Student's t test

    图  6  ACCMIP模式模拟的RCP8.5情景下2000~2100年气候变化导致的中国地区人为气溶胶各季节地表浓度的变化(单位:μg m-3):(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5。打点区域表示偏差通过了95%信度水平检验(t检验)

    Figure  6.  ACCMIP models-simulated changes in seasonal mean surface-layer concentrations (units: μg m-3) of aerosols over China during 2000-2100 induced by the projected climate change under the RCP8.5 scenario: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5. The dotted areas represent statistically significant values at the 95% confidence level based on the Student's t test

    图  7  ACCMIP模式模拟的2000~2100年气候变化导致的中国地区人为气溶胶年平均地表浓度的变化(单位:μg m-3):(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5。打点区域表示偏差通过了95%信度水平检验(t检验)

    Figure  7.  ACCMIP models-simulated changes in annual mean surface-layer concentrations (units: μg m-3) of aerosols over China during 2000-2100 induced by the projected climate change under the RCP8.5 scenario: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5. The dotted areas represent statistically significant values at the 95% confidence level based on the Student's t test

    表  1  所选ACCMIP模式的基本信息

    Table  1.   Description of the ACCMIP (Atmospheric Chemistry and Climate Model Intercomparison Project) models used in this study

    研究中心模式名称气溶胶成分分辨率(经度×纬度)参考文献
    GFDLGFDL-AM3SO4, NO3, BC, POM, SOA, Dust2°×2.5°Donner et al.(2011)
    GISSGISS-E2-RSO4, NO3, BC, POM, SOA, Dust2°×2.5°Koch et al.(2006)
    UKMOHadGEM2SO4, BC, POM, SOA, Dust1.24°×1.87°Collins et al.(2011)
    NIESMIROC-CHEMSO4, BC, POM, SOA, Dust2.8°×2.8°Watanabe et al.(2011)
    注:SO4、NO3、NH4、BC、POM、SOA、Dust分别代表硫酸盐、硝酸盐、铵盐、黑碳、一次有机气溶胶、二次有机气溶胶和沙尘。GFDL,GISS,UKMO,NIES分别表示美国Geophysical Fluid Dynamics Laboratory,美国Goddard Institute for Space Studies,英国Met Office,日本National Institute for Environmental Studies。
    下载: 导出CSV

    表  2  ACCMIP模式模拟的各成分气溶胶地表浓度以及与观测的相对偏差

    Table  2.   Surface-layer aerosol concentrations from the models and normalized mean biases relative to observations

    模式硫酸盐浓度硝酸盐浓度铵盐浓度有机碳浓度黑碳浓度
    模拟/μg m−3归一化平均偏差 模拟/μg m−3归一化平均偏差模拟/μg m−3归一化平均偏差模拟/μg m−3归一化平均偏差模拟/μg m−3归一化平均偏差
    GFDL-AM38.07−67.67%0.95−91.49%4.64−45.70%5.94−75.59%1.32−77.87%
    GISS-E2-R5.33−78.64%3.09−72.45%1.88−77.99%7.01−71.19%1.53−74.46%
    HadGEM25.70−77.18%4.78−80.34%2.46−58.88%
    MIROC-CHEM3.69−85.22%4.69−80.74%1.23−79.39%
    平均5.70−77.18%2.02−81.97%3.26−61.85%5.60−76.96%1.63−72.65%
    注:归一化平均偏差定义为: $\sum\nolimits_{i = 1}^n {\left( {{x_i} - {y_i}} \right)} /\sum\nolimits_{i = 1}^n {{y_i} \times 100\% } $ ,xiyi分别代表不同站点的模拟值和观测值。
    下载: 导出CSV
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  • 收稿日期:  2016-08-19
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