Abstract
The CarbonTracker (CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model’s performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within −0.3 and 1.3 ppm, except for inland stations (7.7 ppm).
摘 要
在以往的研究中, CarbonTracker(CT)模型可用于理解和预测在不同空间和时间尺度范围内控制大气CO2分布的源, 汇和动力过程. 然而, 精确再现接近地表的CO2模型模拟浓度仍然存在挑战, 这通常与较高的空间异质性和土地覆盖相关. 在本研究中, 通过与2009-2013年期间东亚现场观测数据进行比较, 我们评估了基于CT2016版本的嵌套网格CT模型模拟CO2的性能. 我们选择了位于沿海, 偏远, 内陆和山区的站点, 并且将结果进行日变化和季节时间尺度的展示. 在各个目标站点, 在捕捉CO2日变化方面, 模式和观测的一致性是不同的. 总体而言, 全部24小时的平均偏差小于6.3 ppm, 当仅考虑白天时, 偏差进一步降低, 最大偏差为4.6 ppm. 例如, 在Anmyeondo站点, 冬季的模式与观测的偏差较小, 大约为0.2ppm. 该模型揭示了冬季在Gosan和Anmyeondo站点, CO2浓度几乎无日变化, 而在夏季与观测相比则被轻微高估. 该模型在再现CO2日变化方面的表现仍然是一项挑战, 需要改进. 该模型在模拟大多数站点处的白天的CO2季节变化时与观测数据符合的更好, 相关系数在0.70~0.99之间. 其中, 模型与观测的偏差在-0.3和1.3 ppm之间, 内陆站点除外(偏差为7.7 ppm).
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References
Ahmadov, R., C. Gerbig, R. Kretschmer, S. Körner, C. Rodenbeck, P. Bousquet, and M. Ramonet, 2009: Comparing high resolution WRF-VPRM simulations and two global CO2 transport models with coastal tower measurements of CO2. Biogeosciences, 6, 807–817, https://doi.org/10.5194/bg-6-807-2009.
Andrews, A. E., and Coauthors, 2014: CO2, CO, and CH4 measurements from tall towers in the NOAA Earth System Research Laboratory’s Global Greenhouse Gas Reference Network: Instrumentation, uncertainty analysis, and recommendations for future high-accuracy greenhouse gas monitoring efforts. Atmospheric Measurement Techniques, 7, 647–687, https://doi.org/10.5194/amt-7-647-2014.
Baker, D. F., and Coauthors, 2006: TransCom 3 inversion inter-comparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003. Global Biogeochemical Cycles, 20, GB1002, https://doi.org/10.1029/2004GB002439.
Bakwin, P. S., P. P. Tans, D. F. Hurst, and C. L. Zhao, 1998: Measurements of carbon dioxide on very tall towers: Results of the NOAA/CMDL program. Tellus, 50B, 401–415, https://doi.org/10.3402/tellusb.v50i5.16216.
Ballav, S., and Coauthors, 2012: Simulation of CO2 concentration over East Asia using the regional transport model WRF-CO2. J. Meteor. Soc. Japan, 90(6), 959–976, https://doi.org/10.2151/jmsj.2012-607.
Cheng, S. Y., L. X. Zhou, P. P. Tans, X. Q. An, and Y. S. Liu, 2018: Comparison of atmospheric CO2 mole fractions and source-sink characteristics at four WMO/GAW stations in China. Atmos. Environ., 180, 216–225, https://doi.org/10.1016/j.atmosenv.2018.03.010.
Cheng, Y. L., X. Q. An, F. H. Yun, S. X. Fang, L. Xu, L. X. Zhou, and L. X. Liu, 2013: Simulation of CO2 variations at Chinese background atmospheric monitoring stations between 2000 and 2009: Applying a CarbonTracker model. Chinese Science Bulletin, 2013, 58, 3986–3993, https://doi.org/10.1007/s11434-013-5895-y.
Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828.
Fang, S. X., L. X. Zhou, P. P. Tans, P. Ciais, M. Steinbacher, L. Xu, and T. Luan, 2014: In situ measurement of atmospheric CO2 at the four WMO/GAW stations in China. Atmospheric Chemistry and Physics, 14, 2541–2554, https://doi.org/10.5194/acp-14-2541-2014.
Fukuyama, Y., 2013: Atmospheric CO2 monthly concentration data, Yonagunijima, World Data Centre for Greenhouse Gases. Japan Meteorology Agency, Tokyo. [Available online at https://doi.org/ds.data.jma.go.jp/gmd/wdcgg/.]
Gerbig, C., S. Körner, and J. C. Lin, 2008: Vertical mixing in atmospheric tracer transport models: Error characterization and propagation. Atmospheric Chemistry and Physics, 8, 591–602, https://doi.org/10.5194/acp-8-591-2008.
Gurney, K. R., and Coauthors, 2002: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models. Nature, 415, 6872, 626–630, https://doi.org/10.1038/415626a.
Hansen, J., and Coauthors, 2007: Dangerous human-made interference with climate: A GISS modelE study. Atmospheric Chemistry and Physics, 7, 2287–2312, https://doi.org/10.5194/acp-7-2287-2007.
IPCC, 2013: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Report on Climate Change. Cambridge University Press, United Kingdom and New York, NY, USA, 1535 pp.
Keeling, C. D., R. B. Bacastow, A. F. Carter, S. C. Piper, T. P. Whorf, M. Heimann, M. W. G. Mook, and H. Roeloffzen, 1989: A Three Dimensional Model of Atmospheric CO2 Transport Based on Observed Winds. I: Analysis of Observed Data. American Geophysical Union, Washington D. C., 165–236.
Keppel-Aleks, G., and Coauthors, 2012: The imprint of surface fluxes and transport on variations in total column carbon dioxide. Biogeosciences, 9, 875–891, https://doi.org/10.5194/bg-9-875-2012.
Kretschmer, R., C. Gerbig, U. Karstens, and F.-T. Koch, 2012: Error characterization of CO2 vertical mixing in the atmospheric transport model WRF-VPRM. Atmospheric Chemistry and Physics, 12, 2441–2458, https://doi.org/10.5194/acp-12-2441-2012.
Kretschmer, R., C. Gerbig, U. Karstens, G. Biavati, A. Vermeulen, F. Vogel, S. Hammer, and K. U. Totsche, 2014: Impact of optimized mixing heights on simulated regional atmospheric transport of CO2. Atmospheric Chemistry and Physics, 14, 7149–7172, https://doi.org/10.5194/acp-14-7149-2014.
Krol, M., S., and Coauthors, 2005: The two-way nested global chemistry-transport zoom model TM5: Algorithm and applications. Atmospheric Chemistry and Physics, 5, 417–432, https://doi.org/10.5194/acp-5-417-2005.
Law, R. M., and Coauthors, 2008: TransCom model simulations of hourly atmospheric CO2: Experimental overview and diurnal cycle results for 2002. Global Biogeochemical Cycles, 22, GB3009, https://doi.org/10.1029/2007GB003050.
Lin, J. C., and C. Gerbig, 2005: Accounting for the effect of transport errors on tracer inversions. Geophys. Res. Lett., 32, L01802, https://doi.org/10.1029/2004GL021127.
Patra, P. K., and Coauthors, 2008: TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002–2003. Global Biogeochemical Cycles, 22, GB4013, https://doi.org/10.1029/2007GB003081.
Peters, W., and Coauthors, 2007: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker. Proceedings of the National Academy of Sciences of the United States of America, 104, 18 925–18 930, https://doi.org/10.1073/pnas.0708986104.
Peters, W., and Coauthors, 2010: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations. Global Change Biology, 16, 1317–1337, https://doi.org/10.1111/j.1365-2486.2009.02078.x.
Prather, M. J., X. Zhu, S. E. Strahan, S. D. Steenrod, and J. M. Rodriguez, 2008: Quantifying errors in trace species transport modeling. Proceedings of the National Academy of Sciences of the United States of America, 105, 19 617–19 621, https://doi.org/10.1073/pnas.0806541106.
Qu, Y., and Coauthors, 2013: Comparison of atmospheric CO2 observed by GOSAT and two ground stations in China. Int. J. Remote Sens., 34(11), 3938–3946, https://doi.org/10.1080/01431161.2013.768362.
Sasaki, H., 2006: Atmospheric CO2 hourly concentration data. Minamitorishima, Ryori and Yonagunijima, World Data Centre for Greenhouse Gases, Japan Meteorological Meteorological Agency. [Available online from https://doi.org/gqw.kishou.go.jp/wdcgg.html]
Shim, C., J. Lee, and Y. X. Wang, 2013: Effect of continental sources and sinks on the seasonal and latitudinal gradient of atmospheric carbon dioxide over East Asia. Atmos. Environ., 79, 853–860, https://doi.org/10.1016/j.atmosenv.2013.07.055.
Swathi, P. S., N. K. Indira, P. J. Rayner, M. Ramonet, D. Jagadheesha, B. C. Bhatt, and V. K. Gaur, 2013: Robust inversion of carbon dioxide fluxes over temperate Eurasia in 2006–2008. Current Science, 105, 201–208.
Takahashi, T., and Coauthors, 2009: Climatological mean and decadal change in surface ocean pCO2, and net sea-air CO2 flux over the global oceans. Deep Sea Research Part II: Topical Studies in Oceanography, 56(8–10), 554–577, https://doi.org/dx.doi.org/10.1016/j.dsr2.2008.12.009.
Tans, P. P., I. Y. Fung, and T. Takahashi, 1990: Observational constraints on the global atmospheric CO2 budget. Science, 247(4949), 1431–1438, https://doi.org/10.1126/science.247.4949.1431.
Tian, H. Q., and Coauthors, 2016: The terrestrial biosphere as a net source of greenhouse gases to the atmosphere. Nature, 531, 225–228, https://doi.org/10.1038/nature16946.
Tolk, L. F., A. G. C. A. Meesters, A. J. Dolman, and W. Peters, 2008: Modelling representation errors of atmospheric CO2 mixing ratios at a regional scale. Atmospheric Chemistry and Physics, 8, 6587–6596, https://doi.org/10.5194/acp-8-6587-2008.
Watson, A. J., N. Metzl, and U. Schuster, 2011: Monitoring and interpreting the ocean uptake ofatmospheric CO2. Philosophical Transactions of the Royal Society A, 369, 1997–2008, https://doi.org/10.1098/rsta.2011.0060.
Yang, Z., R. A. Washenfelder, G. Keppel-Aleks, N. Krakauer, J. T. Randerson, P. P. Tans, C. Sweeney, and P. O. Wennberg, 2007: New constraints on Northern Hemisphere growing season net flux. Geophys. Res. Lett., 34, L12807, https://doi.org/10.1029/2007GL029742.
Zhang, D. Q., and Coauthors, 2008: Temporal and spatial variations of the atmospheric CO2 concentration in China. Geophys. Res. Lett., 35, L03801, https://doi.org/10.1029/2007GL032531.
Zhou, L. X., D. E. J. Worthy, P. M. Lang, M. K. Ernst, X. C. Zhang, Y. P. Wen, and J. L., 2004: Ten years of atmospheric methane observations at a high elevation site in Western China. Atmos. Environ., 38, 7041–7054, https://doi.org/10.1016/j.atmosenv.2004.02.072.
Zhou, L. X., J. W. C. White, T. J. Conway, H. Mukai, K. Mac-Clune, X. C. Zhang, Y. P. Wen, and J. L. Li, 2006: Long-term record of atmospheric CO2 and stable isotopic ratios at Waliguan Observatory: Seasonally averaged 1991–2002 source/sink signals, and a comparison of 1998–2002 record to the 11 selected sites in the Northern Hemisphere. Global Biogeochemical Cycles, 20, GB2001, https://doi.org/10.1029/2004GB002431.
Acknowledgements
This work was supported by the Korea Meteorological Administration Research and Development Program “Research and Development for KMA Weather, and Earth system Services-Development and Assessment of AR6 Climate Change Scenarios” under Grant (KMA2018-00321). We gratefully acknowledge those who provided the access to the in-situ data at the WDCGG (https://ds.data.jma.go.jp/gmd/wdcgg/cgi-bin/wdcgg/catalogue.cgi).
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• Model-simulated CO2 concentrations are evaluated with in-situ observations at diurnal and seasonal time scales.
• The model performs better in reproducing the daytime CO2 concentrations than the nighttime.
• The model captures well the seasonal variations of CO2 concentrations during daytime at most sites.
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Electronic Supplementary Material to: Evaluation of Simulated CO2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013
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Kenea, S.T., Oh, YS., Rhee, JS. et al. Evaluation of Simulated CO2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013. Adv. Atmos. Sci. 36, 603–613 (2019). https://doi.org/10.1007/s00376-019-8150-x
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DOI: https://doi.org/10.1007/s00376-019-8150-x