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Evapotranspiration-dominated biogeophysical warming effect of urbanization in the Beijing-Tianjin-Hebei region, China

  • Guosong Zhao
  • Jinwei Dong
  • Yaoping Cui
  • Jiyuan Liu
  • Jun Zhai
  • Tian He
  • Yuyu Zhou
  • Xiangming Xiao
Article

Abstract

Given the considerable influences of urbanization on near-surface air temperature (T a ) and surface skin temperature (T s ) at local and regional scales, we investigated the biogeophysical effects of urbanization on T a and T s in the Beijing-Tianjin-Hebei (BTH) region of China, a typical rapidly urbanizing area, using the weather research and forecasting model (WRF). Two experiments were conducted using satellite-derived realistic areal fraction land cover data in 2010 and 1990 as well as localized parameters (e.g. albedo and leaf area index). Without considering anthropogenic heat, experimental differences indicated a regional biogeophysical warming of 0.15 °C (0.16 °C) in summer T a (T s ), but a negligible warming in winter T a (T s ). Sensitivity analyses also showed a stronger magnitude of local warming in summer than in winter. Along with an increase of 10% in the urban fraction, local T a (T s ) increases of 0.185 °C (0.335 °C), 0.212 °C (0.464 °C), and 0.140 °C (0.220 °C) were found at annual, summer, and winter scales, respectively, according to a space-for-time substitution method. The sensitivity analyses will be beneficial to get a rough biogeophysical warming estimation of future urbanization projections. Furthermore, a decomposed temperature metric (DTM) method was applied for the attribution analyses of the change in T s induced by urbanization. Our results showed that the decrease in evapotranspiration-induced latent heat played a dominate role in biogeophysical warming due to urbanization in BTH, indicating that increasing green space could alleviate warming effects, especially in summer.

Keywords

Urbanization Local effect Surface energy balance Numerical modeling 

Notes

Acknowledgements

This research is supported by the Strategic Priority Research Program (XDA19040301) and Key Research Program of Frontier Sciences (QYZDB-SSW-DQC005), the Chinese Academy of Sciences (CAS), the National Natural Science Foundation of China (41501484, 41671425, and 41701501), and the “Thousand Youth Talents Plan”. We want to thank ECMWF for providing ERA-Interim reanalysis data (http://apps.ecmwf.int/datasets/), Global Land Cover Facility (GLCF) and Beijing Normal University for providing Global LAnd Surface Satellite (GLASS) albedo/LAI data (http://glcf.umd.edu/data/), and China Meteorological Data Service Center (CMDC) for providing grid air temperature observations (http://data.cma.cn/data/detail/dataCode/SURF_CLI_CHN_TEM_MON_GRID_0.5/). We also want to thank Xiaoming Hu from the University of Oklahoma and Jilin Yang from the Institute of Geographic Sciences and Natural Resources Research, CAS for their helps to improve the manuscript, as well as the three anonymous reviewers for their insightful comments.

Supplementary material

382_2018_4189_MOESM1_ESM.docx (3 mb)
Supplementary material 1 (DOCX 3111 KB)

References

  1. Betts R (2001) Biogeophysical impacts of land use on present-day climate: near-surface temperature change and radiative forcing. Atmos Sci Lett 2:39–51.  https://doi.org/10.1006/asle.2001.0023 CrossRefGoogle Scholar
  2. Cao C, Lee X, Liu S, Schultz N, Xiao W, Zhang M, Zhao L (2016a) Urban heat islands in China enhanced by haze pollution. Nat Commun 7:12509.  https://doi.org/10.1038/ncomms12509 CrossRefGoogle Scholar
  3. Cao L, Zhu Y, Tang G, Yuan F, Yan Z (2016b) Climatic warming in China according to a homogenized data set from 2419 stations. Int J Climatol 36:4384–4392.  https://doi.org/10.1002/joc.4639 CrossRefGoogle Scholar
  4. Cao Q, Yu D, Georgescu M, Wu J (2016c) Impacts of urbanization on summer climate in China: an assessment with coupled land-atmospheric modeling. J Geophys Res Atmos 121:10505–10521.  https://doi.org/10.1002/2016JD025210 CrossRefGoogle Scholar
  5. Cao Q, Yu D, Georgescu M, Wu J (2017) Substantial impacts of landscape changes on summer climate with major regional differences: the case of China. Sci Total Environ 625:416.  https://doi.org/10.1016/j.scitotenv.2017.12.290 CrossRefGoogle Scholar
  6. Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  7. Chen L, Frauenfeld OW (2015) Impacts of urbanization on future climate in China. Clim Dyn 47:345–357.  https://doi.org/10.1007/s00382-015-2840-6 CrossRefGoogle Scholar
  8. Clinton N, Gong P (2013) MODIS detected surface urban heat islands and sinks: global locations and controls. Remote Sens Environ 134:294–304CrossRefGoogle Scholar
  9. Collins WD et al (2004) Description of the NCAR community atmosphere model (CAM 3.0). NCAR Technical Note NCAR/TN-464 + STR.  https://doi.org/10.5065/D63N21CH
  10. de Noblet-Ducoudré N et al (2012) Determining robust impacts of land-use-induced land cover changes on surface climate over North America and Eurasia: results from the first set of LUCID experiments. J Clim 25:3261–3281.  https://doi.org/10.1175/JCLI-D-11-00338.1 CrossRefGoogle Scholar
  11. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorolog Soc 137:553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  12. Feddema JJ, Oleson KW, Bonan GB, Mearns LO, Buja LE, Meehl GA, Washington WM (2005) The importance of land-cover change in simulating future climates. Science 310:1674–1678CrossRefGoogle Scholar
  13. Georgescu M, Miguez-Macho G, Steyaert LT, Weaver CP (2009) Climatic effects of 30 years of landscape change over the Greater Phoenix, Arizona, region: 1. Surface energy budget changes. J Geophys Res.  https://doi.org/10.1029/2008jd010745 Google Scholar
  14. Georgescu M, Moustaoui M, Mahalov A, Dudhia J (2013) Summer-time climate impacts of projected megapolitan expansion in Arizona. Nat Clim Change 3:37–41.  https://doi.org/10.1038/nclimate1656 CrossRefGoogle Scholar
  15. Grimmond S (2007) Urbanization and global environmental change: local effects of urban warming. Geogr J 173:83–88.  https://doi.org/10.1111/j.1475-4959.2007.232_3.x CrossRefGoogle Scholar
  16. Guo W, Wang X, Sun J, Ding A, Zou J (2016) Comparison of land–atmosphere interaction at different surface types in the mid- to lower reaches of the Yangtze River valley. Atmos Chem Phys 16:9875–9890.  https://doi.org/10.5194/acp-16-9875-2016 CrossRefGoogle Scholar
  17. He Y, Jia G, Hu Y, Zhou Z (2013) Detecting urban warming signals in climate records. Adv Atmos Sci 30:1143–1153.  https://doi.org/10.1007/s00376-012-2135-3 CrossRefGoogle Scholar
  18. Hong S-Y, Dudhia J, Chen S-H (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120CrossRefGoogle Scholar
  19. Hong S-Y, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341CrossRefGoogle Scholar
  20. Hu Y, Jia G, Hou M, Zhang X, Zheng F, Liu Y (2015) The cumulative effects of urban expansion on land surface temperatures in metropolitan JingjinTang, China. J Geophys Res Atmos 120:9932–9943.  https://doi.org/10.1002/2015jd023653 CrossRefGoogle Scholar
  21. Hu X-M, Xue M, Klein PM, Illston BG, Chen S (2016) Analysis of urban effects in Oklahoma City using a dense surface observing network. J Appl Meteorol Clim 55:723–741.  https://doi.org/10.1175/jamc-d-15-0206.1 CrossRefGoogle 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.  https://doi.org/10.1029/2008JD009944 Google Scholar
  23. Juang J-Y, Katul G, Siqueira M, Stoy P, Novick K (2007) Separating the effects of albedo from eco-physiological changes on surface temperature along a successional chronosequence in the southeastern United States. Geophys Res Lett.  https://doi.org/10.1029/2007gl031296 Google Scholar
  24. Kain JS (2004) The Kain–Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181CrossRefGoogle Scholar
  25. Kalnay E, Cai M (2003) Impact of urbanization and land-use change on climate. Nature 423:528.  https://doi.org/10.1038/nature01675 CrossRefGoogle Scholar
  26. Kumar S, Dirmeyer PA, Merwade V, DelSole T, Adams JM, Niyogi D (2013) Land use/cover change impacts in CMIP5 climate simulations: a new methodology and 21st century challenges. J Geophys Res Atmos 118:6337–6353.  https://doi.org/10.1002/jgrd.50463 CrossRefGoogle Scholar
  27. Lee X et al (2011) Observed increase in local cooling effect of deforestation at higher latitudes. Nature 479:384–387.  https://doi.org/10.1038/nature10588 CrossRefGoogle Scholar
  28. Lejeune Q, Seneviratne SI, Davin EL (2017) Historical land-cover change impacts on climate: comparative assessment of LUCID and CMIP5 multimodel experiments. J Clim 30:1439–1459.  https://doi.org/10.1175/jcli-d-16-0213.1 CrossRefGoogle Scholar
  29. Li D, Bou-Zeid E, Barlage M, Chen F, Smith JA (2013) Development and evaluation of a mosaic approach in the WRF-Noah framework. J Geophys Res Atmos 118:11918–11935.  https://doi.org/10.1002/2013JD020657 CrossRefGoogle Scholar
  30. Li X, Zhou Y, Asrar GR, Imhoff M, Li X (2017) The surface urban heat island response to urban expansion: a panel analysis for the conterminous United States. Sci Total Environ 605–606:426–435.  https://doi.org/10.1016/j.scitotenv.2017.06.229 CrossRefGoogle Scholar
  31. Liu J et al (2005) Spatial and temporal patterns of China’s cropland during 1990–2000: an analysis based on Landsat TM data. Remote Sens Environ 98:442–456.  https://doi.org/10.1016/j.rse.2005.08.012 CrossRefGoogle Scholar
  32. Liu Q, Wang L, Qu Y, Liu N, Liu S, Tang H, Liang S (2013) Preliminary evaluation of the long-term GLASS albedo product. Int J Digital Earth 6:69–95.  https://doi.org/10.1080/17538947.2013.804601 CrossRefGoogle Scholar
  33. Liu J et al (2014) Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J Geog Sci 24:195–210.  https://doi.org/10.1007/s11442-014-1082-6 CrossRefGoogle Scholar
  34. Luyssaert S et al (2014) Land management and land-cover change have impacts of similar magnitude on surface temperature. Nat Clim Change 4:389–393.  https://doi.org/10.1038/nclimate2196 CrossRefGoogle Scholar
  35. Mahmood R et al (2014) Land cover changes and their biogeophysical effects on climate. Int J Climatol 34:929–953.  https://doi.org/10.1002/joc.3736 CrossRefGoogle Scholar
  36. Malyshev S, Shevliakova E, Stouffer RJ, Pacala SW (2015) Contrasting local versus regional effects of land-use-change-induced heterogeneity on historical climate: analysis with the GFDL earth system model. J Clim 28:5448–5469.  https://doi.org/10.1175/JCLI-D-14-00586.1 CrossRefGoogle Scholar
  37. McNider RT et al (2012) Response and sensitivity of the nocturnal boundary layer over land to added longwave radiative forcing. J Geophys Res Atmos.  https://doi.org/10.1029/2012jd017578 Google Scholar
  38. Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305:994–997.  https://doi.org/10.1126/science.1098704 CrossRefGoogle Scholar
  39. Niyogi D, Lei M, Kishtawal C, Schmid P, Shepherd M (2017) Urbanization impacts on the summer heavy rainfall climatology over the eastern United States. Earth Interact 21:1–17.  https://doi.org/10.1175/ei-d-15-0045.1 Google Scholar
  40. Oke TR (1982) The energetic basis of the urban heat island. Q J R Meteorolog Soc 108:1–24.  https://doi.org/10.1002/qj.49710845502 Google Scholar
  41. Oleson K et al (2015) Interactions between urbanization, heat stress, and climate change. Clim Change 129:525–541CrossRefGoogle Scholar
  42. Peterson TC (2003) Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found. J Clim 16:2941–2959CrossRefGoogle Scholar
  43. Pielke RA et al (2002) The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases. Philos Trans R Soc A 360:1705–1719.  https://doi.org/10.1098/rsta.2002.1027 CrossRefGoogle Scholar
  44. Pielke RA, Davey C, Morgan J (2004) Assessing “global warming” with surface heat content. Eos Trans Am Geophys Union 85:210–211CrossRefGoogle Scholar
  45. Pielke RA et al (2011) Land use/land cover changes and climate: modeling analysis and observational evidence. Wiley Interdiscip Rev Clim Change 2:828–850.  https://doi.org/10.1002/wcc.144 CrossRefGoogle Scholar
  46. Pielke RA, Mahmood R, McAlpine C (2016) Land’s complex role in climate change. Phys Today 69:40–46.  https://doi.org/10.1063/pt.3.3364 CrossRefGoogle Scholar
  47. Pitman AJ et al. (2009) Uncertainties in climate responses to past land cover change: first results from the LUCID intercomparison study. Geophys Res Lett.  https://doi.org/10.1029/2009gl039076 Google Scholar
  48. Pongratz J, Reick C, Raddatz T, Claussen M (2010) Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change. Geophys Res Lett.  https://doi.org/10.1029/2010GL043010 Google Scholar
  49. Ren Y, Ren G (2011) A remote-sensing method of selecting reference stations for evaluating urbanization effect on surface air temperature trends. J Clim 24:3179–3189.  https://doi.org/10.1175/2010JCLI3658.1 CrossRefGoogle Scholar
  50. Rigden AJ, Li D (2017) Attribution of surface temperature anomalies induced by land use and land cover changes. Geophys Res Lett 44:6814–6822.  https://doi.org/10.1002/2017GL073811 CrossRefGoogle Scholar
  51. Schwarz N, Lautenbach S, Seppelt R (2011) Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures. Remote Sens Environ 115:3175–3186.  https://doi.org/10.1016/j.rse.2011.07.003 CrossRefGoogle Scholar
  52. Sharma A, Fernando HJS, Hamlet AF, Hellmann JJ, Barlage M, Chen F (2017) Urban meteorological modeling using WRF: a sensitivity study. Int J Climatol 37:1885–1900.  https://doi.org/10.1002/joc.4819 CrossRefGoogle Scholar
  53. Skamarock WC, Klemp JB (2008) A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227:3465–3485.  https://doi.org/10.1016/j.jcp.2007.01.037 CrossRefGoogle Scholar
  54. Solomon S et al (eds) (2007) Climate change 2007-the physical science basis: working group I contribution to the fourth assessment report of the IPCC. Cambridge University Press, CambridgeGoogle Scholar
  55. Stewart ID, Oke TR (2012) Local climate zones for urban temperature studies. Bull Am Meteorol Soc 93:1879–1900.  https://doi.org/10.1175/bams-d-11-00019.1 CrossRefGoogle Scholar
  56. Sun Y et al (2014) Rapid increase in the risk of extreme summer heat in Eastern China. Nat Clim Change 4:1082–1085.  https://doi.org/10.1038/nclimate2410 CrossRefGoogle Scholar
  57. Vahmani P, Ban-Weiss GA (2016) Impact of remotely sensed albedo and vegetation fraction on simulation of urban climate in WRF-urban canopy model: a case study of the urban heat island in Los Angeles. J Geophys Res Atmos 121:624–624.  https://doi.org/10.1002/2015JD023718 CrossRefGoogle Scholar
  58. Voogt JA, Oke TR (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86:370–384.  https://doi.org/10.1016/S0034-4257(03)00079-8 CrossRefGoogle Scholar
  59. Wang K, Dickinson RE (2012) A review of global terrestrial evapotranspiration: observation, modeling, climatology, and climatic variability. Rev Geophys.  https://doi.org/10.1029/2011RG000373 Google Scholar
  60. Wang M, Yan X (2015) A comparison of two methods on the climatic effects of urbanization in the Beijing-Tianjin-Hebei metropolitan area. Adv Meteorol 2015:1–12.  https://doi.org/10.1155/2015/352360 Google Scholar
  61. Wang J, Feng J, Yan Z, Hu Y, Jia G (2012) Nested high-resolution modeling of the impact of urbanization on regional climate in three vast urban agglomerations in China. J Geophys Res Atmos 117:D21103.  https://doi.org/10.1029/2012jd018226 Google Scholar
  62. Wang J, Yan Z, Jones PD, Xia J (2013a) On “observation minus reanalysis” method: a view from multidecadal variability. J Geophys Res Atmos 118:7450–7458.  https://doi.org/10.1002/jgrd.50574 CrossRefGoogle Scholar
  63. Wang M, Zhang X, Yan X (2013b) Modeling the climatic effects of urbanization in the Beijing–Tianjin–Hebei metropolitan area. Theor Appl Climatol 113:377–385.  https://doi.org/10.1007/s00704-012-0790-z CrossRefGoogle Scholar
  64. Wang F, Ge Q, Wang S, Li Q, Jones PD (2015a) A new estimation of urbanization’s contribution to the warming trend in China. J Clim 28:8923–8938.  https://doi.org/10.1175/JCLI-D-14-00427.1 CrossRefGoogle Scholar
  65. Wang L, Gao Z, Miao S, Guo X, Sun T, Liu M, Li D (2015b) Contrasting characteristics of the surface energy balance between the urban and rural areas of Beijing. Adv Atmos Sci 32:505.  https://doi.org/10.1007/s00376-014-3222-4 CrossRefGoogle Scholar
  66. Wang J, Yan Z, Quan X-W, Feng J (2016) Urban warming in the 2013 summer heat wave in eastern China. Clim Dyn 48:3015–3033.  https://doi.org/10.1007/s00382-016-3248-7 CrossRefGoogle Scholar
  67. Wang K, Jiang S, Wang J, Zhou C, Wang X, Lee X (2017a) Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network. J Geophys Res Atmos 122:2131–2154.  https://doi.org/10.1002/2016JD025304 CrossRefGoogle Scholar
  68. Wang X, Guo W, Qiu B, Liu Y, Sun J, Ding A (2017b) Quantifying the contribution of land use change to surface temperature in the lower reaches of the Yangtze River. Atmos Chem Phys 17:4989–4996.  https://doi.org/10.5194/acp-17-4989-2017 CrossRefGoogle Scholar
  69. Winckler J, Reick CH, Pongratz J (2017a) Robust identification of local biogeophysical effects of land-cover change in a global climate model. J Clim 30:1159–1176.  https://doi.org/10.1175/jcli-d-16-0067.1 CrossRefGoogle Scholar
  70. Winckler J, Reick CH, Pongratz J (2017b) Why does the locally induced temperature response to land cover change differ across scenarios? Geophys Res Lett 44:3833–3840.  https://doi.org/10.1002/2017gl072519 CrossRefGoogle Scholar
  71. Wolf S et al (2016) Warm spring reduced carbon cycle impact of the 2012 US summer drought. PNAS 113:5880–5885.  https://doi.org/10.1073/pnas.1519620113 CrossRefGoogle Scholar
  72. Xiao Z, Liang S, Wang J, Xiang Y, Zhao X, Song J (2016) Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. IEEE Trans Geosci Remote Sens 54:5301–5318.  https://doi.org/10.1109/TGRS.2016.2560522 CrossRefGoogle Scholar
  73. Yang P, Ren G, Liu W (2013) Spatial and temporal characteristics of Beijing urban heat island intensity. J Appl Meteorol Clim 52:1803–1816.  https://doi.org/10.1175/jamc-d-12-0125.1 CrossRefGoogle Scholar
  74. Zhao D, Wu J (2017) The influence of urban surface expansion in china on regional climate. J Clim 30:1061–1080.  https://doi.org/10.1175/jcli-d-15-0604.1 CrossRefGoogle Scholar
  75. Zhao L, Lee X, Smith RB, Oleson K (2014) Strong contributions of local background climate to urban heat islands. Nature 511:216–219.  https://doi.org/10.1038/nature13462 CrossRefGoogle Scholar
  76. Zhao G, Dong J, Liu J, Zhai J, Cui Y, He T, Xiao X (2017) Different patterns in daytime and nighttime thermal effects of urbanization in Beijing-Tianjin-Hebei urban agglomeration. Remote Sens 9:121.  https://doi.org/10.3390/rs9020121 CrossRefGoogle Scholar
  77. Zhou L et al (2004) Evidence for a significant urbanization effect on climate in China. PNAS 101:9540–9544.  https://doi.org/10.1073/pnas.0400357101 CrossRefGoogle Scholar
  78. Zhou D, Zhao S, Liu S, Zhang L, Zhu C (2014) Surface urban heat island in China’s 32 major cities: spatial patterns and drivers. Remote Sens Environ 152:51–61.  https://doi.org/10.1016/j.rse.2014.05.017 CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.College of Environment and PlanningHenan UniversityKaifengChina
  3. 3.Satellite Environment CenterMinistry of Environmental ProtectionBeijingChina
  4. 4.School of Water Conservancy and EnvironmentZhengzhou UniversityZhengzhouChina
  5. 5.Department of Geological and Atmospheric SciencesIowa State UniversityAmesUSA
  6. 6.Department of Microbiology and Plant Biology, and Center for Spatial AnalysisUniversity of OklahomaNormanUSA
  7. 7.Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity ScienceFudan UniversityShanghaiChina

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