Please wait a minute...
img

官方微信

遥感技术与应用  2023, Vol. 38 Issue (4): 880-891    DOI: 10.11873/j.issn.1004-0323.2023.4.0880
面向双碳的观测与模拟专栏     
基于通用地球系统模式的不同类型气溶胶直接辐射效应的数值模拟
刘甲1,2,3(),王壬1,2,3,李龙辉1,2,3()
1.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023
2.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023
3.南京师范大学地理科学学院,江苏 南京 210023
Numerical Simulation of Different Types of Aerosols Direct Radiation Effect based on Community Earth System Model
Jia LIU1,2,3(),Ren WANG1,2,3,Longhui LI1,2,3()
1.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China
2.Key Laboratory of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University,Nanjing 210023,China
3.School of Geography,Nanjing Normal University,Nanjing 210023,China
 全文: PDF(10567 KB)   HTML
摘要:

气溶胶可以通过直接效应来影响地气系统的辐射平衡,然而目前气溶胶直接辐射效应的研究主要集中于总气溶胶,缺乏不同类型气溶胶直接辐射效应研究。利用通用地球系统模式(Community Earth System Model, CESM)模拟研究了晴空和有云条件下总气溶胶、硫酸盐气溶胶和含碳气溶胶在大气层顶和地表的直接辐射强迫,并利用多源数据对模拟结果进行验证。结果表明,CESM模拟总气溶胶光学厚度与气溶胶自动观测网(Aerosol Robotic Network, AERONET)有较好的相关性(R2 =0.44),但模拟数值整体偏小;与MERRA-2(Modern-Era Retrospective Analysis for Research and Applications Version 2)对比发现,高估了含碳气溶胶光学厚度,低估了硫酸盐气溶胶光学厚度;CESM模拟的辐射通量与基线地表辐射观测网(Baseline Surface Radiation Network, BSRN)的模拟效果良好(R2 =0.93)。在晴空条件下,CESM模拟的总气溶胶以及硫酸盐气溶胶、含碳气溶胶在大气层顶的直接辐射强迫分别为-1.37、-0.46、-0.45 W/m2;有云条件下分别为-0.30、-0.25、+0.04 W/m2,云削弱了气溶胶在大气层顶负的辐射效应,但加强了含碳气溶胶的吸热作用从而呈现出正效应;晴空条件下地表的直接辐射强迫分别为-5.60、-0.53、-2.21 W/m2,有云条件下分别为-4.38、-0.32、-1.64 W/m2,气溶胶的直接辐射效应在地表均为负效应,云对沙尘气溶胶的辐射效应影响不大,但却能削弱硫酸盐气溶胶和含碳气溶胶的直接辐射效应强度。研究结果有利于进一步理解不同类型气溶胶的直接辐射效应,并为未来改进CESM提供依据。

关键词: 气溶胶CESM模式评估直接辐射强迫    
Abstract:

Aerosols can affect the radiation balance of the earth atmosphere system through direct effects. However the research on aerosol direct radiation effect mainly focuses on total aerosol, and there is a lack of research on different types of aerosol direct radiation effect. In this study, the Community Earth System Model (CESM) is used to simulate the direct radiative forcing of total aerosols, sulfate aerosols and carbonaceous aerosols on the top of the atmosphere and the surface, and the simulation results are verified by multi-source data. The results show that there is a good correlation between the total Aerosol Optical Depth (AOD) simulated by CESM and the AERONET (R2 = 0.44), but the simulation value is relatively small. Compared with MERRA-2, it is found that the optical depth of carbonaceous aerosol is overestimated and the optical depth of sulfate aerosol is underestimated; The radiation flux simulated by CESM and the simulation effect of BSRN are good (R2 = 0.93).The simulation results show that the direct radiative forcing of total aerosol, sulfate aerosol and carbon aerosol at the top of the atmosphere under clear sky conditions are -1.37、-0.46 and -0.45 W/m2, and -0.30、-0.25 and +0.04 W/m2 under cloudy conditions, respectively. Therefore, the existence of clouds weakens the negative radiation effect of aerosols at the top of the atmosphere and strengthens the endothermic effect of carbonaceous aerosols, showing a positive effect; Under clear sky conditions, the direct radiation forcing on the surface is -5.60、-0.53、-2.21 W/m2, and it is -4.38、-0.32、-1.64 W/m2 under cloudy conditions, respectively. Thus, the direct radiation effect of aerosols presents a negative effect on the surface, and the presence of clouds has little effect on the radiation effect of dust aerosols, but it can weaken the direct radiation effect intensity of sulfate aerosol and carbon aerosol. The results of this study are helpful to further understand the direct radiation effects of different types of aerosols and provide a basis for improving CESM in the future.

Key words: Aerosol    CESM    Model evaluation    Direct radiation forcing
收稿日期: 2021-12-06 出版日期: 2023-09-11
ZTFLH:  P407  
基金资助: 国家重点研发计划“全球变化及应对”专项项目(2017YFA0603603)
通讯作者: 李龙辉     E-mail: 13182875966lj@gmail.com;Longhui.Li@njnu.edu.cn
作者简介: 刘 甲(1996-),女,江西九江人,硕士研究生,主要从事气溶胶辐射效应研究。E?mail:13182875966lj@gmail.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
刘甲
王壬
李龙辉

引用本文:

刘甲,王壬,李龙辉. 基于通用地球系统模式的不同类型气溶胶直接辐射效应的数值模拟[J]. 遥感技术与应用, 2023, 38(4): 880-891.

Jia LIU,Ren WANG,Longhui LI. Numerical Simulation of Different Types of Aerosols Direct Radiation Effect based on Community Earth System Model. Remote Sensing Technology and Application, 2023, 38(4): 880-891.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2023.4.0880        http://www.rsta.ac.cn/CN/Y2023/V38/I4/880

试验名称外强迫条件
S1所有外强迫条件随时间变化
S2去掉所有气溶胶的直接辐射效应
S3去掉硫酸盐气溶胶的直接辐射效应
S4去掉含碳气溶胶的直接辐射效应
表1  气溶胶的直接辐射强迫试验设计
序号国家站点观测时段样本数
1中国Beijing-CAMS201208~20180663
2中国XiangHe200103~201705148
3中国Taihu200509~20160888
4中国SACOL200608~20130579
5中国Hong_Kong_PolyU200511~201703103
6中国Xinglong200602~20140868
7印度Gandhi_College200604~20170692
8印度Bhola201304~20170539
9印度Kanpur200301~201803170
10巴基斯坦Karachi200609~20140989
11巴基斯坦Lahore200701~20150481
12日本Osaka200301~201902165
13越南Bac_Lieu200303~20170994
14泰国Silpakorn_Univ200711~201802111
15赞比亚Mongu200101~201001109
16巴西Alta_Floresta200101~201903207
17尼日尔Zinder_Airport200905~201810102
18尼日尔Banizoumbou200101~201812213
19阿根廷CEILAP-BA200301~201701156
20墨西哥Mexico_City200101~201807183
21巴西CUIABA-MIRANDA200103~201903177
22印度尼西亚Bandung200905~20180786
表2  AERONET选取的站点样本数和观测时段
地表类型站点数量样本数
城市7852
草地111 779
森林4594
表3  BSRN选取的站点信息
图1  CESM模拟结果与AERONET AOD观测数据对比验证
图2  CESM模拟结果和MERRA-2数据的对比验证
图3  CESM模拟结果(a)和CERES(SYN)(b) 与BSRN观测数据对比验证
图4  CESM模拟结果和CERES(SYN)的气溶胶直接辐射强迫对比验证(第一列:CESM模拟结果;第二列:CERES计算的辐射强迫(右上角为全球平均值, 打点区域表示通过0.05显著性检验)
图5  总气溶胶、硫酸盐气溶胶、含碳气溶胶在晴空和有云条件下大气层顶的直接辐射强迫(单位:W/m2)(右上角为全球平均值, 打点区域表示通过0.05显著性检验)
图6  总气溶胶、硫酸盐气溶胶、含碳气溶胶在晴空和有云条件下地表的直接辐射强迫(单位:W/m2)(右上角为全球平均值, 打点区域表示通过0.05显著性检验)
1 ENGLING G, GELENCSER A. Atmospheric brown clouds: from local air pollution to climate change[J]. Elements (Quebec), 2010, 6(4): 223-228. DOI: 10.2113/gselements.6.4.223
doi: 10.2113/gselements.6.4.223
2 CHEN L J, FEI Y, WANG R, et al. Retrieval of high temporal resolution aerosol optical depth using the GOCI remote sensing data[J]. Remote Sensing,2021,13(12):2376. DOI: 10.3390/rs13122376
doi: 10.3390/rs13122376
3 FU B, GASSER T, LI B G, et al. Short-lived climate forcers have long-term climate impacts via the carbon-climate feedback[J]. Nature Climate Change,2020,10(9): 851-855. DOI: 10.1038/s41558-020-0841-x
doi: 10.1038/s41558-020-0841-x
4 HUANG J P, WANG T H, WANG W C, et al. Climate effects of dust aerosols over East Asian arid and semiarid regions[J]. Journal of Geophysical Research:Atmos-pheres,2014,119(19):11398-11416. DOI:10.1002/2014JD 021796
doi: 10.1002/2014JD 021796
5 ZHANG H, MA J H, ZHANG Y F. Modeling study of the global distribution of radiative forcing by dust aerosol[J]. Acta Meteorologica Sinica, 2010, 24(5): 558-570.
6 LIU Z Y, HUANG J B, SHI G Y, et al. Aerosol optical properties and radiative effect determined from sky-radiometer over Loess Plateau of Northwest China[J]. Atmospheric Che-mistry and Physics,2011,11(22):11455-11463. DOI:10.5194/acp-11-11455-2011
doi: 10.5194/acp-11-11455-2011
7 HAYWOOD J M, RAMASWAMY V. Global sensitivity studies of the direct radiative forcing due to anthropogenic sulfate and black carbon aerosols[J]. Journal of Geophysical Research Atmospheres, 1998, 103(D6): 6043-6058. DOI: 10.1029/97JD03426
doi: 10.1029/97JD03426
8 ACKERMANA S, TONN O B, STEVENS D E, et al. Reduction of tropical cloudiness by soot[J]. Science,2000,288(5468): 1042-1047. DOI: 10.1126/science.288.5468.1042
doi: 10.1126/science.288.5468.1042
9 SHI G Y, WANG B, ZHANG H, et al. The radiative and climatic effects of atmospheric aerosols[J]. Chinese Journal of Atmospheric Sciences,2008,32(4):826-840. DOI:10.3878/j.issn.1006-9895.2008.04.11
doi: 10.3878/j.issn.1006-9895.2008.04.11
10 LUO Yunfeng, ZHOU Xiuji, LI Weiliang. Advances in the study of atmospheric aerosol radiative forcing and climate change[J]. Advances in Earth Science, 1998, 13(6): 63-72.
10 罗云峰, 周秀骥, 李维亮. 大气气溶胶辐射强迫及气候效应的研究现状[J]. 地球科学进展, 1998, 13(6): 63-72.
11 SHI G M. Radiative forcing and greenhouse effect due to the atmospheric trace gases[J]. Science China-chemistry, 1992, 35(2): 217-229. DOI: 10.1360/YB1992-35-2-217
doi: 10.1360/YB1992-35-2-217
12 SHAO Y P. A model for mineral dust emission[J]. Journal of Geophysical Research Atmospheres, 2001, 106(D17): 20239-20254. DOI: 10.1029/2001JD900171
doi: 10.1029/2001JD900171
13 HAN Tian, PAN Xiaoduo, WANG Xufeng,et al. Application of remote sensing data in WRF-Chem model simulating sandstorm[J]. Remote Sensing Technology and Application, 2020, 35(4): 808-819.
13 韩天,潘小多,王旭峰,等. 遥感资料在WRF-Chem沙尘模拟中的应用[J]. 遥感技术与应用,2020,35(4):808-819.
14 ALVIM D S, PENDHARKAR J, CAPISTRANO V B, et al. Aerosol distribution over Brazil with ECHAM-HAM and CAM5-MAM3 simulations and its comparison with ground-based and satellite data[J]. Atmospheric Pollution Research, 2017, 8(4): 718-728. DOI: 10.1016/j.apr.2017.01.008
doi: 10.1016/j.apr.2017.01.008
15 HU Zhiyuan. Numerical simulation of aerosol in atmosphere an snow[D]. Lanzhou: Lanzhou University, 2016.
15 胡志远.大气和积雪中气溶胶的数值模拟研究[D]. 兰州:兰州大学,2016.
16 YU H, KAUFMAN Y J, CHIN M, et al. A review of measurement-based assessment of aerosol direct radiative effect and forcing[J]. Atmospheric Chemistry and Physics, 2006, 27(6): 613-666. DOI: 10.5194/acp-6-613-2006
doi: 10.5194/acp-6-613-2006
17 PARK S U, JEONG J I. Direct radiative forcing due to aerosols in Asia during March 2002[J]. Science of the Total Environment,2008,407(1):394-404. DOI:10.1016/j.scitotenv. 2008.07.041
doi: 10.1016/j.scitotenv. 2008.07.041
18 ZHANG L, LIAO H, LI J P. Impacts of Asian summer monsoon on seasonal and interannual variations of aerosols over eastern China[J]. Journal of Geophysical Research: Atmospheres, 2010, 115(D7). DOI: 10.1029/2009JD012299
doi: 10.1029/2009JD012299
19 RAJI K B, OGUNJOBI K O, AKINSANOLA A A. Radiative effects of dust aerosol on West African climate using simulations from RegCM4[J]. Modeling Earth Systems & Environment,2017,3(1):34. DOI:10.1007/s40808-017-0295-y
doi: 10.1007/s40808-017-0295-y
20 HE Xin, LU Chunsong, ZHU Jun. A study of the spatiotemporal variation in aerosol types and their radiation effect in China[J]. Acta Scientiae Circumstantiae, 2020, 40(11): 4070-4080.
20 贺欣、陆春松、朱君. 中国地区气溶胶类型变化及其辐射效应研究[J]. 环境科学学报, 2020, 40(11): 4070-4080.
21 WANG H, TAN S C, WANG Y, et al. A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013[J]. Atmospheric Environment,2014,89:807-815. DOI:10.1016/j.atmosenv. 2014.03.004
doi: 10.1016/j.atmosenv. 2014.03.004
22 ZHOU C, ZHANG H, ZHAO S Y, et al. On effective radiative forcing of partial internally and externally mixed aerosols and their effects on global climate[J]. Journal of Geophysical Research: Atmospheres,2018,123(1):401-423. DOI:10.1002/2017JD027603
doi: 10.1002/2017JD027603
23 WANG Dongdong, ZHU Bing, JIANG Zhihong, et al. A modeling study of effects of anthropogenic aerosol on East Asian winter monsoon over eastern China[J]. Transactions of Atmospheric Sciences, 2017, 40(4): 541-552.
23 王东东, 朱彬, 江志红, 等. 人为气溶胶对中国东部冬季风影响的模拟研究[J]. 大气科学学报, 2017, 40(4): 541-552.
24 LI Xin, LIU Yu. Assessment of two aerosol modules of CAM5[J]. Chinese Academy of Meteorological Sciences, 2013, 24(1):75-86.
24 李鑫,刘煜. CAM5模式中两气溶胶模块的评估[J].应用气象学报, 2013, 24(1):75-86.
25 FARQUHAR G D, CAEMMERER S V, BERRY J A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species[J]. Planta, 1980, 149(1): 78-90. DOI: 10.1007/BF00386231
doi: 10.1007/BF00386231
26 COLLATZ G J, BALL J T, GRIVET C, et al. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: A model that includes a laminar boundary layer[J]. Agricultural and Forest Meteorology, 1991, 54(2-4): 107-136. DOI: 10.1016/0168-1923(91)90002-8
doi: 10.1016/0168-1923(91)90002-8
27 OLESON K W, LAWRENCE D M, BONAN G B, et al. Technical description of version 4.0 of the Community Land Model (CLM)[Z]. National Center for Atmospheric Research, Boulder, USA, 2010. DOI: 10.5065/D6FB50WZ
28 HOLBEN B N, ECK T F, SLUTSKER I, et al. AERONET-A federated instrument network and data archive for aerosol characterization[J]. Remote Sensing of Environment, 1998, 66(1): 1-16. DOI: 10.1016/S0034-4257(98)00031-5
doi: 10.1016/S0034-4257(98)00031-5
29 LU Tianwei, ZHANG Jing, QIAO Yan, et al. Effects of aerosols on radiation and precipitation in the Yangtze River Delta[J]. Journal of Beijing Normal University(Natural Science), 2019, 55(1): 135-144.
29 陆天蔚, 张晶, 乔岩, 等. 长三角地区气溶胶对辐射和降水影响的分析[J]. 北京师范大学学报(自然科学版), 2019, 55(1): 135-144.
30 DOELLING D R, LOEB N G, KEYES D F, et al. Geostationary enhanced temporal interpolation for CERES Flux products[J].Journal of Atmospheric and Oceanic Technology,2013,30(6):1072-1090. DOI:10.1175/JTECH-D-12-00136.1
doi: 10.1175/JTECH-D-12-00136.1
31 Rui Lü. Aerosol optical properties and direct radiative forcing over eastern China[D]. Nanjing: Nanjing University of Information Science and Technology, 2018.
31 吕睿. 中国东部大气气溶胶光学特性及直接辐射强迫研究[D]. 南京:南京信息工程大学, 2018.
32 MA Jinghui. The optical properties and global radiative forcing simulation of black carbon and dust aerosols[D]. Nanjing: Nanjing University of Information Science and Technology, 2007.
32 马井会. 黑碳和沙尘气溶胶光学特性及全球辐射强迫的模拟研究[D]. 南京:南京信息工程大学, 2007.
33 ZHANG H, WANG Z L, WANG Z Z, et al. Simulation of direct radiative forcing of aerosols and their effects on east Asian climate using an interactive AGCM-aerosol coupled System[J]. Climate Dynamics, 2012, 38(7-8): 1675-1693. DOI: 10.1007/s00382-011-1131-0
doi: 10.1007/s00382-011-1131-0
34 LI Jiandong, MAO Jiangyu, WANG Weijiang. Anthropogenic Eastern Asian radiative forcing due to sulfate and black carbon aerosols and their time evolution estimated by an AGCM[J]. Chinese Journal of Geophysics, 2015, 58(4): 1103-1120.
34 李剑东, 毛江玉, 王维强. 大气模式估算的东亚区域人为硫酸盐和黑碳气溶胶辐射强迫及其时间变化特征[J]. 地球物理学报, 2015, 58(4): 1103-1120.
35 KOCH D, BOND T C, STREETS D, et al. Global impacts of aerosols from particular source regions and sectors [J]. Journal of Geophysical Research Atmospheres, 2007, 112(D2). DOI: 10.1029/2005JD007024
doi: 10.1029/2005JD007024
36 REDDY M S, BOUCHER O, BALKANSKI Y, et al. Aerosol optical depths and direct radiative perturbations by species and source type[J]. Geophysical Research Letters, 2005, 32(12): 21743-21746. DOI: 10.1029/2004GL021743
doi: 10.1029/2004GL021743
37 DENMAN K, BRASSEUR G. The physical science basis, contribution of working group I to the fourth assessment report of the Intergovernmental panel on climate change[J]. Computational Geometry, 2007, 18(2): 95-123.
38 ZHANG H, WANG Z L, GUO P W,et al. A modeling study of the effects of direct radiative forcing due to carbonaceous aerosol on the climate in East Asia[J]. Advances in Atmospheric Sciences,2009,26(1):57-66. DOI: 10.1007/s00376-009-0057-5
doi: 10.1007/s00376-009-0057-5
39 ABDUL R H. Atmospheric aerosols regional characteristics chemistry and physics[J]. 2012, 10.5772/2695 (Chapter 6).
40 SU Xingtao, WANG Hanjie, SONG Shuai, et al. Radiative force and temperature response of dust aerosol over East Asia in recent decade[J]. Plateau Meteorology,2011,30(5):1300-1307.
40 宿兴涛,王汉杰,宋帅,等. 近10年东亚沙尘气溶胶辐射强迫与温度响应[J]. 高原气象,2011,30(5):1300-1307.
41 ZHANG Tianhang, LIAO Hong, CHANG Wenyuan, et al. Direct radiative forcing by dust in China based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) Datasets[J]. Chinese Journal of Atmospheric Sciences, 2016,40(6):1242-1260.
41 张天航,廖宏,常文渊,等. 基于国际大气化学—气候模式比较计划模式数据评估中国沙尘气溶胶直接辐射强迫[J]. 大气科学,2016,40(6):1242-1260.
42 LI Xin. Aeesesment of CAM5 and climate effect of primary organic aerosol[D]. Beijing: Chinese Academy of Meteorological Sciences, 2012.
42 李鑫. CAM5模式的评估与一次有机碳气溶胶的气候效应[D]. 北京:中国气象科学研究院, 2012.
[1] 崔嘉文,陈健,成高淼,石满,刘佳琪,祝善友. 协同地基和空基激光雷达的沙尘天气观测研究[J]. 遥感技术与应用, 2022, 37(2): 416-423.
[2] 王永前,何孟琦,张洋,杨世琦,高阳华. 基于高分五号DPC数据的细模态气溶胶光学厚度反演[J]. 遥感技术与应用, 2022, 37(2): 451-459.
[3] 王浩天,汪源,袁强强. 2008~2016年MODIS多角度大气校正气溶胶产品在中国的时空分布及变化趋势[J]. 遥感技术与应用, 2021, 36(1): 217-228.
[4] 王明,刘正佳,陈元琰. 基于Sentinel-2波段/产品的图像云检测效果对比研究[J]. 遥感技术与应用, 2020, 35(5): 1167-1177.
[5] 韦海宁,王维真,黄广辉,徐菲楠,冯姣姣,董磊磊. 基于Himawari-8的气溶胶反演研究[J]. 遥感技术与应用, 2020, 35(4): 797-807.
[6] 徐玉雯,张浩,陈正超,景海涛. 基于深蓝算法的Sentinel-2数据气溶胶光学厚度反演[J]. 遥感技术与应用, 2020, 35(2): 372-380.
[7] 李志鹏,陈健. 基于GOCI卫星的大气细颗粒物PM2.5的遥感反演及其时空分布规律研究[J]. 遥感技术与应用, 2020, 35(1): 163-173.
[8] 韦海宁,王维真,徐菲楠,冯姣姣. Himawari-8气溶胶产品的验证及应用[J]. 遥感技术与应用, 2019, 34(5): 1005-1015.
[9] 向嘉敏, 祝善友, 张桂欣, 刘祎, 周洋. 灰霾遥感监测研究进展[J]. 遥感技术与应用, 2019, 34(1): 12-20.
[10] 冯姣姣, 王维真, 李净, 刘雯雯. 基于BP神经网络的华东地区太阳辐射模拟及时空变化分析[J]. 遥感技术与应用, 2018, 33(5): 881-889.
[11] 汤玉明,邓孺孺,刘永明,熊龙海. 大气气溶胶遥感反演研究综述[J]. 遥感技术与应用, 2018, 33(1): 25-34.
[12] 陈健,周杰,李雅雯. 基于静止卫星GOCI数据的陆地上空气溶胶光学厚度遥感反演[J]. 遥感技术与应用, 2017, 32(6): 1040-1047.
[13] 黎微微,胡斯勒图,陈洪滨,尚华哲. 利用MODIS资料计算不同云天条件下的地表太阳辐射[J]. 遥感技术与应用, 2017, 32(4): 643-650.
[14] 张婕,张文煜,冯建东,王宏义,于泽,宋玮. 基于亮温—植被指数—气溶胶光学厚度的MODIS火点监测算法研究[J]. 遥感技术与应用, 2016, 31(5): 886-892.
[15] 张胜敏,周美玲,司一丹,王中挺. 深蓝算法应用于GF-1 16 m相机反演陆地气溶胶[J]. 遥感技术与应用, 2016, 31(4): 709-713.