Advertisement

Seasonal climatic effects and feedbacks of anthropogenic heat release due to global energy consumption with CAM5

  • Bing Chen
  • C. Wu
  • X. Liu
  • L. Chen
  • Jian Wu
  • H. Yang
  • Tao Luo
  • Xue Wu
  • Yiquan Jiang
  • Lei Jiang
  • H. Y. Brown
  • Z. Lu
  • W. Fan
  • G. Lin
  • Bo Sun
  • M. Wu
Article

Abstract

Anthropogenic heat release (AHR) is the heat generated in global energy consumption, which has not been considered in global climate models generally. The global high-resolution AHR from 1992 to 2013, which is estimated by using the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) satellite data, is implemented into the Community Atmosphere Model version 5 (CAM5). The seasonal climatic effects and possible feedbacks of AHR are examined in this study. The modeling results show that AHR increases the global annual mean surface temperature and land surface temperature by 0.02 ± 0.01 K (1σ uncertainty) and 0.05 ± 0.02 K (1σ uncertainty), respectively. The global climatic effect of AHR varies with season: with a stronger climatic effect in the boreal winter leading to global mean land surface temperature increases by 0.10 ± 0.01 K (1σ uncertainty). In the selected regions (40°N–60°N, 0°E–45°E) of Central and Western Europe the average surface temperature increases by 0.46 K in the boreal summer, and in the selected regions (45°N–75°N, 30°E–140°E) of northern Eurasia the average surface temperature increases by 0.83 K in the boreal winter. AHR changes the height and thermodynamic structure of the global planetary boundary layer, as well as the stability of the lower troposphere, which affects the global atmospheric circulation and low cloud fraction. In addition, at the surface both the shortwave radiation flux in the boreal summer and the down-welling longwave flux in the boreal winter change significantly, as a result of the change in low clouds caused by the effect of AHR. This study suggests a possible new mechanism of AHR effect on global climate through changing the global low-cloud fraction, which is crucial for global energy balance, by modifying the thermodynamic structure and stability of the lower troposphere. Thus this study improves our understanding of the global climate change caused by human activities.

Keywords

Anthropogenic heat release Climatic effect Climate feedback Climate change 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 41505126 and 41865001), the Program for key Laboratory in University of Yunnan Province, and Open Project of the Ministry of Education Key Laboratory for Earth System Modeling of Tsinghua University in 2017.

References

  1. Abdul-Razzak H, Ghan SJ (2000) A parameterization of aerosol activation: 2. Multiple aerosol types. J Geophys Res 105(D5):6837–6844.  https://doi.org/10.1029/1999JD901161 CrossRefGoogle Scholar
  2. Allen L, Lindberg F, Grimmond C (2011) Global to city scale urban anthropogenic heat flux: model and variability. Int J Climatol 31(13):1990–2005CrossRefGoogle Scholar
  3. Bacmeister JT, Wehner MF, Neale RB, Gettelman A, Hannay C, Lauritzen PH, Caron JM, Truesdale JE (2014) Exploratory high-resolution climate simulations using the community atmosphere model (CAM). J Clim 27:3073–3099CrossRefGoogle Scholar
  4. Block A, Keuler K, Schaller E (2004) Impacts of anthropogenic heat on regional climate patterns, Geophys Res Lett 31:L12211.  https://doi.org/10.1029/2004GL019852 CrossRefGoogle Scholar
  5. Bretherton CS, Park S (2009) A new moist turbulence parameterization in the community atmosphere model. J Clim 22:3422–3448CrossRefGoogle Scholar
  6. Chaison EJ (2008) Long-term global heating from energy usage. EOS 89:253–260CrossRefGoogle Scholar
  7. Chen B, Shi GY (2012) Estimation of the distribution of global anthropogenic heat flux. Atmos Ocean Sci Lett 5:108–112.  https://doi.org/10.1080/16742834.2012.11446974 CrossRefGoogle Scholar
  8. Chen B, Shi GY,WANGB, Tan S, Zhao JQ (2012) Estimation of anthropogenic heat release distribution of China from 1992 to 2009. Acta Meteorol Sin 26(4):507–515CrossRefGoogle Scholar
  9. Chen B, Dong L, Shi GY, Li L, Chen L (2014) Anthropogenic heat release: estimation of global distribution and possible climate effect. J Meteorol Soc Jpn 92A:157–165CrossRefGoogle Scholar
  10. Chen B, Zhao JQ, Chen L, Shi GY (2015) Reply to the comments of F. Fujibe on “Anthropogenic heat release: estimation of global distribution and possible climate effect” by Chen. B. et al. J Meteorol Soc Jpn 93(4):505–508CrossRefGoogle Scholar
  11. Chen B, Dong L, Liu X, Shi GY, Chen L, Nakajima T, Habib A (2016) Exploring the possible effect of anthropogenic heat release due to global energy consumption upon global climate: a climate model study. Int J Climatol 36:4790–4796.  https://doi.org/10.1002/joc.4669 CrossRefGoogle Scholar
  12. Crutzen PJ (2004) New directions: the growing urban heat and pollution “island” effect—impact on chemistry and climate. Atmos Environ 38:3539–3540CrossRefGoogle Scholar
  13. Dong Y, Varquez ACG, Kanda M (2017) Global anthropogenic heat flux database with high spatial resolution. Atmos Environ 150:276–294CrossRefGoogle Scholar
  14. Fan H, Sailor DJ (2005) Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia: a comparison of implementations in two PBL schemes. Atmos Environ 39:73–84CrossRefGoogle Scholar
  15. Feng JM, Wang Y, Ma Z, Liu Y (2012) Simulating the regional impacts of urbanization and anthropogenic heat release on climate across China. J Clim 25:7187–7203CrossRefGoogle Scholar
  16. Flanner MG (2009) Integrating anthropogenic heat flux with global climate models. Geophys Res Lett 36:L02801.  https://doi.org/10.1029/2008GL036465 CrossRefGoogle Scholar
  17. Gates WL (1992) AMIP: the atmospheric model intercomparison project. Bull Am Meteorol Soc 73:1962–1970CrossRefGoogle Scholar
  18. Gettelman A, Liu X, Ghan SJ, Morrison H, Park S, Conley AJ, Klein SA, Boyle J, Mitchell DL, Li JLF (2010) Global simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the community atmosphere model. J Geophys Res Atmos 115:D18216.  https://doi.org/10.1029/2009JD013797 CrossRefGoogle Scholar
  19. Hansen J, Nazarenko L, Reudy R, Sato M, Willis J et al (2005) Earth’s energy imbalance: confirmation and Implications. Science 39:1431–1434CrossRefGoogle Scholar
  20. Hurrell JW, Hack JJ, Shea D, Caron JM, Rosinski J (2008) A new sea surface temperature and sea ice boundary dataset for the community atmosphere model. J Clim 21(19):5145–5153CrossRefGoogle Scholar
  21. Hurrell JW, Holland MM, Gent PR, Ghan S, Kay JE, Kushner PJ, Lamarque JF, Large WG, Lawrence D, Lindsay K, Lipscomb WH, Long MC, Mahowald N, Marsh DR, Neale RB, Rasch P, Vavrus S, Vertenstein M, Bader D, Collins WD, Hack JJ, Kiehl J, Marshall S (2013) The community earth system model: a framework for collaborative research. Bull Am Meteorol Soc 94:1339–1360CrossRefGoogle Scholar
  22. Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res Atmos 113:D13103.  https://doi.org/10.1029/2008JD009944 CrossRefGoogle Scholar
  23. Ichinose T, Shimodozono K, Hanaki K (1999) Impact of anthropogenic heat on urban climate in Tokyo. Atmos Environ 33:3897–3909CrossRefGoogle Scholar
  24. IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Cambridge University Press, CambridgeGoogle Scholar
  25. IPCC (2013) Climate change 2013. The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. In: Stocker TF, Qin D, Plattner GK et al (eds) Cambridge University Press, CambridgeGoogle Scholar
  26. Kay JE, Deser C, Phillips A, Mai A, Hannay C, Strand G, Arblaster J, Bates S, Danabasoglu G, Edwards J, Holland M, Kushner P, Lamarque J-F, Lawrence D, Lindsay K, Middleton A, Munoz E, Neale R, Oleson K, Polvani L, Vertenstein M (2015) The community earth system model (CESM) large ensemble project: a community resource for studying climate change in the presence of internal climate variability. Bull Am Meteorol Soc 96:1333–1349CrossRefGoogle Scholar
  27. Lee SH, Song CK, Baik JJ, Park SU (2009) Estimation of anthropogenic heat emission in the Gyeong-In region of Korea. Theor Appl Climatol 96:291–303CrossRefGoogle Scholar
  28. Lin CY, Chen F, Huang JC, Chen WC, Liou YA, Chen WN, Liu SC (2008) Urban heat island effect and its impact on boundary layer development and land–sea circulation over northern Taiwan. Atmos Environ 42:5635–5649.  https://doi.org/10.1016/j.atmosenv.2008.03.015 CrossRefGoogle Scholar
  29. Lindberg F, Grimmond C, Yogeswaran N, Kotthaus S and Allen L (2013) Impact of city changes and weather on anthropogenic heat flux in Europe 1995–2015. Urban Clim 4:1–15CrossRefGoogle Scholar
  30. Liu X, Penner JE (2005) Ice nucleation parameterization for global models. Meteorol Z 14(4):499–514CrossRefGoogle Scholar
  31. Liu X, Penner JE, Ghan SJ, Wang M (2007) Inclusion of ice microphysics in the NCAR community atmospheric model version 3 (CAM3). J Clim 20:4526–4547CrossRefGoogle Scholar
  32. Liu X, Easter RC, Ghan SJ, Zaveri R, Rasch P, Shi X, Lamarque JF, Gettelman A, Morrison H, Vitt F, Conley A, Park S, Neale R, Hannay C, Ekman AML, Hess P, Mahowald N, Collins W, Iacono MJ, Bretherton CS, Flanner MG, Mitchell D (2012) Toward a minimal representation of aerosols in climate models: description and evaluation in the community atmosphere model CAM5. Geosci Model Dev 5:709–739CrossRefGoogle Scholar
  33. McCarthy MP, Best MJ, Betts RA (2010) Climate change in cities due to global warming and urban effect. Geophys Res Lett 37:L09705.  https://doi.org/10.1029/2010GL042845 CrossRefGoogle Scholar
  34. Morrison H, Gettelman A (2008) A new two-moment bulk stratiform cloud microphysics scheme in the community atmosphere model, version 3 (CAM3). Part I: description and numerical tests. J Clim 21:3642–3659CrossRefGoogle Scholar
  35. Neale RB et al (2010) Description of the NCAR community atmosphere model (CAM5.0). NCAR Tech. Rep. NCAR/ TN-4861STR, p 274Google Scholar
  36. Oke TR (1988) The urban energy balance. Prog Phys Geogr 12:471–580CrossRefGoogle Scholar
  37. Oleson KW, Lawrence DM, Gordon B, Flanner MG, Kluzek E, Peter J, Levis S, Swenson SC, Thornton E, Feddema J (2010) Technical description of version 4.0 of the community land model (CLM), NCAR Tech. Note NCAR/TN-461 + STRGoogle Scholar
  38. Park S, Bretherton CS (2009) The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the community atmosphere model. J Clim 22:3449–3469CrossRefGoogle Scholar
  39. Park S, Bretherton CS, Rasch PJ (2014) Integrating cloud processes in the community atmosphere model, version 5. J Clim 27:6821–6856CrossRefGoogle Scholar
  40. Rachel ES, Clemesha K, Guirguis A, Gershunov IJ, Small A, Tardy (2018) California heat waves: their spatial evolution, variation, and coastal modulation by low clouds. Clim Dyn 50:4285–4301CrossRefGoogle Scholar
  41. Richter JH, Rasch PJ (2008) Effects of convective momentum transport on the atmospheric circulation in the community atmosphere model, version 3. J Clim 21:1487–1499CrossRefGoogle Scholar
  42. Sailor DJ, Lu L (2004) A top-down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos Environ 38:2737–2748CrossRefGoogle Scholar
  43. Wang X, Sun X, Tang J, Yang X (2015) Urbanization-induced regional warming in Yangtze river delta: potential role of anthropogenic heat release. Int J Climatol 35(15):4417–4430CrossRefGoogle Scholar
  44. Wood R, Bretherton CS (2006) On the relationship between stratiform low cloud cover and lower-tropospheric stability. J Clim 19:6425–6432CrossRefGoogle Scholar
  45. Wu K, Yang X (2013) Urbanization and heterogeneous surface warming in eastern China. Chin Sci Bull 58:1363CrossRefGoogle Scholar
  46. Yang W, Jiang C, Yu X et al (2014) Review of research on anthropogenic heat under climate change. Progr Geogr 33(8):1029–1038Google Scholar
  47. Zhang GJ, McFarlane NA (1995) Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian climate centre general circulation model. Atmos Ocean 33:407–446CrossRefGoogle Scholar
  48. Zhang GJ, Cai M, Hu A (2013) Energy consumption and the unexplained winter warming over northern Asia and North America. Nat Clim Change 3:466–470CrossRefGoogle Scholar
  49. Zhong S, Qian Y, Zhao C, Leung R, Wang H, Yang B, Fan J, Yan H, Yang XQ, Liu D (2017) Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China. Atmos Chem Phys 17:5439–5457CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Bing Chen
    • 1
    • 2
    • 3
  • C. Wu
    • 2
    • 5
  • X. Liu
    • 2
  • L. Chen
    • 4
  • Jian Wu
    • 1
  • H. Yang
    • 6
  • Tao Luo
    • 7
  • Xue Wu
    • 5
  • Yiquan Jiang
    • 8
  • Lei Jiang
    • 9
  • H. Y. Brown
    • 2
  • Z. Lu
    • 2
  • W. Fan
    • 1
  • G. Lin
    • 2
  • Bo Sun
    • 9
  • M. Wu
    • 2
  1. 1.Key Laboratory of Atmospheric Environment and Processes in the Boundary Layer over the Low-Latitude Plateau Region, Department of Atmospheric ScienceYunnan UniversityKunmingChina
  2. 2.Department of Atmospheric ScienceUniversity of WyomingLaramieUSA
  3. 3.Ministry of Education Key Laboratory for Earth System ModelingTsinghua UniversityBeijingChina
  4. 4.The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  5. 5.Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  6. 6.School of Earth and EnvironmentICAS, University of LeedsLeedsUK
  7. 7.Hefei Institutes of Physical ScienceChinese Academy of SciencesHefeiChina
  8. 8.CMA-NJU Joint Laboratory for Climate Prediction Studies, Institute for Climate and Global Change Research, School of Atmospheric SciencesNanjing UniversityNanjingChina
  9. 9.Nanjing University of Information Science and TechnologyNanjingChina

Personalised recommendations