Volume 42 Issue 2
Feb.  2023
Turn off MathJax
Article Contents
Zenghong Liu, Xiaogang Xing, Zhaohui Chen, Shaolei Lu, Xiaofen Wu, Hong Li, Chunling Zhang, Lijing Cheng, Zhaoqin Li, Chaohui Sun, Jianping Xu, Dake Chen, Fei Chai. Twenty years of ocean observations with China Argo[J]. Acta Oceanologica Sinica, 2023, 42(2): 1-16. doi: 10.1007/s13131-022-2076-3
Citation: Zenghong Liu, Xiaogang Xing, Zhaohui Chen, Shaolei Lu, Xiaofen Wu, Hong Li, Chunling Zhang, Lijing Cheng, Zhaoqin Li, Chaohui Sun, Jianping Xu, Dake Chen, Fei Chai. Twenty years of ocean observations with China Argo[J]. Acta Oceanologica Sinica, 2023, 42(2): 1-16. doi: 10.1007/s13131-022-2076-3

Twenty years of ocean observations with China Argo

doi: 10.1007/s13131-022-2076-3
Funds:  The National Natural Science Foundation of China under contract Nos 42122046, 42076202, U1811464 and 4210060098; the Project Supported by Laoshan Laboratory under contract No. LSKJ202201500; the Project Supported by Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) under contract No. SML2021SP102.
More Information
  • Corresponding author: E-mail: fchai@sio.org.cn
  • Received Date: 2022-04-12
  • Accepted Date: 2022-06-14
  • Available Online: 2022-11-07
  • Publish Date: 2023-02-25
  • The international Argo program, a global observational array of nearly 4 000 autonomous profiling floats initiated in the late 1990s, which measures the water temperature and salinity of the upper 2 000 m of the global ocean, has revolutionized oceanography. It has been recognized one of the most successful ocean observation systems in the world. Today, the proposed decade action “OneArgo” for building an integrated global, full-depth, and multidisciplinary ocean observing array for beyond 2020 has been endorsed. In the past two decades since 2002, with more than 500 Argo deployments and 80 operational floats currently, China has become an important partner of the Argo program. Two DACs have been established to process the data reported from all Chinese floats and deliver these data to the GDACs in real time, adhering to the unified quality control procedures proposed by the Argo Data Management Team. Several Argo products have been developed and released, allowing accurate estimations of global ocean warming, sea level change and the hydrological cycle, at interannual to decadal scales. In addition, Deep and BGC-Argo floats have been deployed, and time series observations from these floats have proven to be extremely useful, particularly in the analysis of synoptic-scale to decadal-scale dynamics. The future aim of China Argo is to build and maintain a regional Argo fleet comprising approximately 400 floats in the northwestern Pacific, South China Sea, and Indian Ocean, accounting for 9% of the global fleet, in addition to maintaining 300 Deep Argo floats in the global ocean (25% of the global Deep Argo fleet). A regional BGC-Argo array in the western Pacific also needs to be established and maintained.
  • loading
  • Amin H, Bagherbandi M, Sjöberg L E. 2020. Quantifying barystatic sea-level change from satellite altimetry, GRACE and Argo observations over 2005–2016. Advances in Space Research, 65(8): 1922–1940. doi: 10.1016/j.asr.2020.01.029
    Argo Science Team. 1998. On the design and implementation of Argo: an initial plan for a global array of profiling floats. ICPO Report No. 21. Melbourne, Victoria: GODAE International Project Office, Bureau of Meteorology
    Bao Senliang, Wang Huizan, Zhang Ren, et al. 2019. Comparison of satellite-derived sea surface salinity products from SMOS, Aquarius, and SMAP. Journal of Geophysical Research: Oceans, 124(3): 1932–1944. doi: 10.1029/2019JC014937
    Bao Senliang, Wang Huizan, Zhang Ren, et al. 2021. Application of phenomena-resolving assessment methods to satellite sea surface salinity products. Earth and Space Science, 8(8): e2020EA001410
    Bindoff N L, Cheung W W L, Kairo J G, et al. 2019. Changing ocean, marine ecosystems, and dependent communities. In: Pörtner H O, Roberts D C, Masson-Delmotte V, et al. , eds. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. Cambridge, UK and New York, NY, USA: Cambridge University Press, 447–587
    Biogeochemical-Argo Planning Group. 2016. The scientific rationale, design and implementation plan for a biogeochemical-Argo float array. https://biogeochemical-argo.org/cloud/document/relevant-reports/BGC-Argo_Science_Implementation_Plan.pdf[2016-04-12/2020-12-03]
    Böhme L, Send U. 2005. Objective analyses of hydrographic data for referencing profiling float salinities in highly variable environments. Deep-Sea Research Part II: Topical Studies in Oceanography, 52(3–4): 651–664
    Camargo C M L, Riva R E M, Hermans T H J, et al. 2020. Exploring sources of uncertainty in steric sea-level change estimates. Journal of Geophysical Research: Oceans, 125(10): e2020JC016551
    Chai Fei, Johnson K S, Claustre H, et al. 2020. Monitoring ocean biogeochemistry with autonomous platforms. Nature Reviews Earth & Environment, 1(6): 315–326
    Chai Fei, Wang Yuntao, Xing Xiaogang, et al. 2021. A limited effect of sub-tropical typhoons on phytoplankton dynamics. Biogeosciences, 18(3): 849–859. doi: 10.5194/bg-18-849-2021
    Chen Jianqiang, Gong Xun, Guo Xinyu, et al. 2022. Improved perceptron of subsurface chlorophyll maxima by a deep neural network: A case study with BGC-Argo float data in the northwestern Pacific Ocean. Remote Sensing, 14(3): 632. doi: 10.3390/rs14030632
    Cheng Lijing, Abraham J, Hausfather Z, et al. 2019. How fast are the oceans warming?. Science, 363(6423): 128–129. doi: 10.1126/science.aav7619
    Cheng Lijing, Abraham J, Trenberth K E, et al. 2021. Upper ocean temperatures hit record high in 2020. Advances in Atmospheric Sciences, 38(4): 523–530. doi: 10.1007/s00376-021-0447-x
    Cheng Lijing, Trenberth K E, Fasullo J, et al. 2017. Improved estimates of ocean heat content from 1960 to 2015. Science Advances, 3(3): e1601545. doi: 10.1126/sciadv.1601545
    Cheng Lijing, Trenberth K E, Gruber N, et al. 2020. Improved estimates of changes in upper ocean salinity and the hydrological cycle. Journal of Climate, 33(23): 10357–10381. doi: 10.1175/JCLI-D-20-0366.1
    Cheng Lijing, Zhu Jiang. 2016. Benefits of CMIP5 multimodel ensemble in reconstructing historical ocean subsurface temperature variations. Journal of Climate, 29(15): 5393–5416. doi: 10.1175/JCLI-D-15-0730.1
    Cheng Lijing, Zhu Jiang, Cowley R, et al. 2014. Time, probe type, and temperature variable bias corrections to historical expendable bathythermograph observations. Journal of Atmospheric and Oceanic Technology, 31(8): 1793–1825. doi: 10.1175/JTECH-D-13-00197.1
    Claustre H, Bishop J, Boss E, et al. 2010. Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies: Potential synergies with ocean color remote sensing. In: Hall J, Harrison D E, Stammer D, eds. Proceedings of the “OceanObs’09: Sustained Ocean Observations and Information for Society”. Venice, Italy: ESA Publication
    Claustre H, Johnson K S, Takeshita Y. 2020. Observing the global ocean with biogeochemical-Argo. Annual Review of Marine Science, 12(1): 23–48. doi: 10.1146/annurev-marine-010419-010956
    Dangendorf S, Frederikse T, Chafik L, et al. 2021. Data-driven reconstruction reveals large-scale ocean circulation control on coastal sea level. Nature Climate Change, 11(6): 514–520. doi: 10.1038/s41558-021-01046-1
    Dilmahamod A F, Penven P, Aguiar-González B, et al. 2019. A new definition of the South-East Madagascar Bloom and analysis of its variability. Journal of Geophysical Research: Oceans, 124(3): 1717–1735. doi: 10.1029/2018JC014582
    Ding Ya’nan, Yu Fei, Ren Qiang, et al. 2022. The physical-biogeochemical responses to a subsurface anticyclonic eddy in the Northwest Pacific. Frontiers in Marine Science, 8: 766544. doi: 10.3389/fmars.2021.766544
    Duan Wei, Cheng Xuhua, Zhu Xiuhua, et al. 2021. Variability in upper-ocean salinity stratification in the tropical Pacific Ocean. Acta Oceanologica Sinica, 40(1): 113–125. doi: 10.1007/s13131-020-1597-x
    Frederikse T, Landerer F, Caron L, et al. 2020. The causes of sea-level rise since 1900. Nature, 584(7821): 393–397. doi: 10.1038/s41586-020-2591-3
    Gaillard F. 2012. ISAS-Tool Version 6: Method and configuration. Brest: via Ifremer
    Gaillard F, Autret E, Thierry V, et al. 2009. Quality control of large Argo datasets. Journal of Atmospheric and Oceanic Technology, 26(2): 337–351. doi: 10.1175/2008JTECHO552.1
    Gaillard F, Reynaud T, Thierry V, et al. 2016. In situ–based reanalysis of the global ocean temperature and salinity with ISAS: variability of the heat content and steric height. Journal of Climate, 29(4): 1305–1323. doi: 10.1175/JCLI-D-15-0028.1
    Gao Zhiyuan, Chen Zhaohui, Huang Xiaodong, et al. 2021. Internal wave imprints on temperature fluctuations as revealed by rapid-sampling deep profiling floats. Journal of Geophysical Research: Oceans, 126(12): e2021JC017878
    Garcia H E, Boyer T P, Baranova O K, et al. 2019. World Ocean Atlas 2018: Product Documentation. A. Mishonov, Technical Editor. https://www.ncei.noaa.gov/sites/default/files/2020-04/woa18documentation.pdf[2022-4-6]
    Gleckler P, Santer B, Domingues C, et al. 2012. Human-induced global ocean warming on multidecadal timescales. Nature Climate Change, 2: 524–529. doi: 10.1038/nclimate1553
    Gonaduwage L P, Chen Gengxin, Priyadarshana T, et al. 2021. Interannual variability of summertime eddy-induced heat transport in the western South China Sea and its formation mechanism. Climate Dynamics, 57(1): 451–468
    Good S A, Martin M J, Rayner N A. 2013. EN4: quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. Journal of Geophysical Research: Oceans, 118(12): 6704–6716. doi: 10.1002/2013JC009067
    Gourrion J, Szekely T, Killick R, et al. 2020. Improved statistical method for quality control of hydrographic observations. Journal of Atmospheric and Oceanic Technology, 37(5): 789–806. doi: 10.1175/JTECH-D-18-0244.1
    Guerreiro C V, Baumann K H, Brummer G J A, et al. 2019. Transatlantic gradients in calcifying phytoplankton (coccolithophore) fluxes. Progress in Oceanography, 176: 102140. doi: 10.1016/j.pocean.2019.102140
    Hakuba M Z, Frederikse T, Landerer F W. 2021. Earth’s energy imbalance from the ocean perspective (2005–2019). Geophysical Research Letters, 48(16): e2021GL093624
    Herr A E, Kiene R P, Dacey J W H, et al. 2019. Patterns and drivers of dimethylsulfide concentration in the northeast subarctic Pacific across multiple spatial and temporal scales. Biogeosciences, 16(8): 1729–1754. doi: 10.5194/bg-16-1729-2019
    Holte J, Talley L D, Gilson J, et al. 2017. An Argo mixed layer climatology and database. Geophysical Research Letters, 44(11): 5618–5626. doi: 10.1002/2017GL073426
    Hosoda S, Ohira T, Nakamura T. 2008. A monthly mean dataset of global oceanic temperature and salinity derived from Argo float observations. JAMSTEC Report of Research and Development, 8: 47–59. doi: 10.5918/jamstecr.8.47
    Johnson K S, Berelson W M, Boss E S, et al. 2009. Observing biogeochemical cycles at global scales with profiling floats and gliders: prospects for a global array. Oceanography, 22(3): 216–225. doi: 10.5670/oceanog.2009.81
    Johnson G C, Hosoda S, Jayne S R, et al. 2022. Argo-two decades: Global oceanography, revolutionized. Annual Review of Marine Science, 14(1): 379–403. doi: 10.1146/annurev-marine-022521-102008
    Johnson G C, Lyman J M, Purkey S G. 2015. Informing Deep Argo array design using Argo and full-depth hydrographic section data. Journal of Atmospheric and Oceanic Technology, 32(11): 2187–2198
    Kobayashi T, Watanabe K, Tachikawa M. 2013. Deep NINJA collects profiles down to 4, 000 meters. Sea Technology, 54(2): 41–44
    Le Reste S, Dutreuil V, André X, et al. 2016. “Deep-Arvor”: A new profiling float to extend the Argo observations down to 4000-m depth. Journal of Atmospheric and Oceanic Technology, 33(5): 1039–1055. doi: 10.1175/JTECH-D-15-0214.1
    Li Guancheng, Cheng Lijing, Zhu Jiang, et al. 2020a. Increasing ocean stratification over the past half-century. Nature Climate Change, 10(12): 1116–1123. doi: 10.1038/s41558-020-00918-2
    Li Zhaoqin, Liu Zenghong, Lu Shaolei. 2020b. Global Argo data fast receiving and post-quality-control system. IOP Conference Series: Earth and Environmental Science, 502(1): 012012. doi: 10.1088/1755-1315/502/1/012012
    Li Hong, Xu Jianping, Liu Zenghong, et al. 2013. Study on the global ocean Argo gridded dataset and its validation community in coastal waters of Yantai. Marine Science Bulletin (in Chinese), 32(6): 615–625
    Li Hong, Xu Fanghua, Zhou Wei, et al. 2017. Development of a global gridded Argo data set with Barnes successive corrections. Journal of Geophysical Research: Oceans, 122(2): 866–889. doi: 10.1002/2016JC012285
    Li Guancheng, Zhang Yuhong, Xiao Jingen, et al. 2019. Examining the salinity change in the upper Pacific Ocean during the Argo period. Climate Dynamics, 53(9): 6055–6074
    Liang Xinfeng, Liu Chao, Ponte R M, et al. 2021. A comparison of the variability and changes in global ocean heat content from multiple objective analysis products during the Argo period. Journal of Climate, 34(19): 7875–7895
    Liu Zenghong, Li Zhaoqin, Lu Shaolei, et al. 2021. Scattered dataset of global ocean temperature and salinity profiles from the international Argo Program. Journal of Global Change Data & Discovery (in Chinese), 5(3): 312–321
    Liu Chao, Liang Xinfeng, Chambers D P, et al. 2020. Global patterns of spatial and temporal variability in salinity from multiple gridded Argo products. Journal of Climate, 33(20): 8751–8766. doi: 10.1175/JCLI-D-20-0053.1
    Liu Hao, Lin Xiaopei, Lan Jian. 2019. Salt sinking in the upper South Pacific subtropical gyre from 2004 to 2016. Journal of Geophysical Research: Oceans, 124(10): 7011–7029. doi: 10.1029/2019JC015270
    Liu Hao, Wei Zexun. 2021. Intercomparison of global sea surface salinity from multiple datasets over 2011–2018. Remote Sensing, 13(4): 811. doi: 10.3390/rs13040811
    Liu Zenghong, Wu Xiaofen, Xu Jianping, et al. 2017. China Argo project: progress in China Argo ocean observations and data applications. Acta Oceanologica Sinica, 36(6): 1–11. doi: 10.1007/s13131-017-1035-x
    Lu Shaolei, Liu Zenghong, Li Hong, et al. 2020. Manual of Global Ocean Argo Gridded Data Set (BOA_Argo). Hangzhou: China Argo Real-Time Data Center
    Lu Shaolei, Sun Chaohui, Liu Zenghong, et al. 2016. Comparative testing and data quality evaluation for COPEX, HM2000 and APEX profiling buoys. Journal of Ocean Technology (in Chinese), 35(1): 84–92
    Lyu Kewei, Zhang Xuebin, Church J A. 2021. Projected ocean warming constrained by the ocean observational record. Nature Climate Change, 11(10): 834–839. doi: 10.1038/s41558-021-01151-1
    Owens W B, Wong A P S. 2009. An improved calibration method for the drift of the conductivity sensor on autonomous CTD profiling floats by θ-S climatology. Deep-Sea Research Part I: Oceanographic Research Papers, 56(3): 450–457. doi: 10.1016/j.dsr.2008.09.008
    Park J E, Park K A, Kang C K, et al. 2020. Satellite-observed chlorophyll-a concentration variability and its relation to physical environmental changes in the East Sea (Japan Sea) from 2003 to 2015. Estuaries and Coasts, 43(3): 630–645. doi: 10.1007/s12237-019-00671-6
    Petzrick E, Truman J, Fargher H. 2013. Profiling from 6, 000 meter with the APEX-Deep float. In: 2013 OCEANS. San Diego, CA, USA: IEEE, 1–3
    Ponte R M, Sun Qiang, Liu Chao, et al. 2021. How salty is the global ocean: Weighing it all or tasting it a sip at a time?. Geophysical Research Letters, 48(11): e2021GL092935
    Ridgway K R, Dunn J R, Wilkin J L. 2002. Ocean interpolation by four-dimensional weighted least squares—Application to the waters around Australasia. Journal of Atmospheric and Oceanic Technology, 19(9): 1357–1375. doi: 10.1175/1520-0426(2002)019<1357:OIBFDW>2.0.CO;2
    Riser S C, Freeland H J, Roemmich D, et al. 2016. Fifteen years of ocean observations with the global Argo array. Nature Climate Change, 6(2): 145–153. doi: 10.1038/nclimate2872
    Roemmich D, Alford M H, Claustre H, et al. 2019a. On the future of Argo: A global, full-depth, multi-disciplinary array. Frontiers in Marine Science, 6: 439. doi: 10.3389/fmars.2019.00439
    Roemmich D, Gilson J. 2009. The 2004–2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program. Progress in Oceanography, 82(2): 81–100. doi: 10.1016/j.pocean.2009.03.004
    Roemmich D, Johnson G C, Riser S, et al. 2009. The Argo Program: Observing the global oceans with profiling floats. Oceanography, 22(2): 34–43. doi: 10.5670/oceanog.2009.36
    Roemmich D, Owens W B. 2000. The Argo Project: Global ocean observations for understanding and prediction of climate variability. Oceanography, 13(2): 45–50. doi: 10.5670/oceanog.2000.33
    Roemmich D, Sherman J T, Davis R E, et al. 2019b. Deep SOLO: A full-depth profiling float for the Argo program. Journal of Atmospheric and Oceanic Technology, 36(10): 1967–1981. doi: 10.1175/JTECH-D-19-0066.1
    Tesdal J E, Abernathey R P, Goes J I, et al. 2018. Salinity trends within the upper layers of the subpolar North Atlantic. Journal of Climate, 31(7): 2675–2698. doi: 10.1175/JCLI-D-17-0532.1
    Tran A. 2019. Review of Argo data performance on the Global Telecommunication System (GTS). The 20th Argo Data Management Team Meeting, 16–18 October, 2019, Villefranche-sur-mer, France
    von Schuckmann K, Cheng L J, Palmer M D, et al. 2020. Heat stored in the Earth system: Where does the energy go?. Earth System Science Data, 12(3): 2013–2041. doi: 10.5194/essd-12-2013-2020
    Wang Tao, Chai Fei, Xing Xiaogang, et al. 2021a. Influence of multi-scale dynamics on the vertical nitrate distribution around the Kuroshio Extension: An investigation based on BGC-Argo and satellite data. Progress in Oceanography, 193: 102543. doi: 10.1016/j.pocean.2021.102543
    Wang Guihua, Liu Zenghong, Xu Jianping. 2006. Three dimensional Pacific temperature, salinity and circulation reconstructions with Argo data. In: Xu Jianping, ed. A Collection of Research Articles on Argo Application (in Chinese). Beijing: China Ocean Press, 16–26
    Wang Tao, Zhang Shuwen, Chen Fajin, et al. 2021b. Influence of sequential tropical cyclones on phytoplankton blooms in the northwestern South China Sea. Journal of Oceanology and Limnology, 39(1): 14–25. doi: 10.1007/s00343-020-9266-7
    Wong A P S, Johnson G C, Owens W B. 2003. Delayed-mode calibration of autonomous CTD profiling float salinity data by θ-S climatology. Journal of Atmospheric and Oceanic Technology, 20(2): 308–318. doi: 10.1175/1520-0426(2003)020<0308:DMCOAC>2.0.CO;2
    Wong A, Keeley R, Carval T, et al. 2022. Argo quality control manual for CTD and trajectory data. https://archimer.ifremer.fr/doc/00228/33951/[2021-8-3]
    Wong A P S, Riser S C. 2011. Profiling float observations of the upper ocean under sea ice off the Wilkes Land coast of Antarctica. Journal of Physical Oceanography, 41(6): 1102–1115. doi: 10.1175/2011JPO4516.1
    Wong A P S, Riser S C. 2013. Modified shelf water on the continental slope north of Mac Robertson Land, East Antarctica. Geophysical Research Letters, 40(23): 6186–6190. doi: 10.1002/2013GL058125
    Wong A P S, Wijffels S E, Riser S C, et al. 2020. Argo data 1999–2019: Two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7: 700. doi: 10.3389/fmars.2020.00700
    Wu Yue, Zheng Xiaotong, Sun Qiwei, et al. 2021. Decadal variability of the upper-ocean salinity in the southeast Indian Ocean: role of local ocean-atmosphere dynamics. Journal of Climate, 34(19): 7927–7942. doi: 10.1175/JCLI-D-21-0122.1
    Xie Chunhu, Xu Miaomiao, Cao Shasha, et al. 2019. Gridded Argo data set based on GDCSM analysis technique: establishment and preliminary applications. Journal of Marine Sciences (in Chinese), 37(4): 24–35
    Xing Xiaogang, Boss E, Chen Shuangling, et al. 2021. Seasonal and daily-scale photoacclimation modulating the phytoplankton chlorophyll-carbon coupling relationship in the mid-latitude northwest Pacific. Journal of Geophysical Research: Oceans, 126(10): e2021JC017717
    Xing Xiaogang, Wells M L, Chen Shuangling, et al. 2020. Enhanced winter carbon export observed by BGC-Argo in the Northwest Pacific Ocean. Geophysical Research Letters, 47(22): e2020GL089847
    Xu Jianping. 2002. A Exploration of Global Ocean Argo Observing (in Chinese). Beijing: China Ocean Press
    Xu Jianping, Liu Zenghong. 2007. The Experiment of China Argo Ocean Observing Array (in Chinese). Beijing: China Meteorological Press
    Yan Hengqian, Wang Huizan, Zhang Ren, et al. 2021. The inconsistent pairs between in situ observations of near surface salinity and multiple remotely sensed salinity data. Earth and Space Science, 8(5): e2020EA001355
    Yang Yuanyuan, Zhong Min, Feng Wei, et al. 2021. Detecting regional deep ocean warming below 2000 meter based on altimetry, GRACE, Argo, and CTD data. Advances in Atmospheric Sciences, 38(10): 1778–1790. doi: 10.1007/s00376-021-1049-3
    Zhang Chunling, Wang Zhenfeng, Liu Yu. 2021. An Argo-based experiment providing near-real-time subsurface oceanic environmental information for fishery data. Fisheries Oceanography, 30(1): 85–98. doi: 10.1111/fog.12504
    Zhang Chunling, Wang Danyang, Wang Zhenfeng. 2022. Fishery analysis using gradient-dependent optimal interpolation. Acta Oceanologica Sinica, 41(2): 116–126. doi: 10.1007/s13131-021-1895-y
    Zhang Chunling, Xu Jianping, Bao Xianwen. 2015. Gradient-dependent correlation scale method based on Argo. Journal of PLA University of Science and Technology (Natural Science Edition) (in Chinese), 16(5): 476–483
    Zhang Chunling, Xu Jianping, Bao Xianwen, et al. 2013. An effective method for improving the accuracy of Argo objective analysis. Acta Oceanologica Sinica, 32(7): 66–77. doi: 10.1007/s13131-013-0333-1
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(15)  / Tables(2)

    Article Metrics

    Article views (950) PDF downloads(70) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return