Skip to main content

Advertisement

SpringerLink
Log in

WRF/UCM simulations of the impacts of urban expansion and future climate change on atmospheric thermal environment in a Chinese megacity

  • Published:
Climatic Change Aims and scope Submit manuscript

Abstract

Urban expansion and climate change can considerably influence the regional thermal environment. In this study, the effects of changes in land cover type and vegetation coverage (referred to as LU for short), gridded anthropogenic heat (AH) emission and future climate change on atmospheric thermal environment in a Chinese megacity, Hefei, are investigated by Weather Research and Forecasting (WRF)/Urban Canopy Model (UCM) model. It is found that the increase of surface sensible heat in old urban areas is contributed by AH emission, while that in new urban areas is attributed to LU change. The LU change in new urban areas can lead to the decreased latent heat flux due to the reduction of vegetation coverage and the increase of impervious land surface. The contribution of LU change to the summer UHI intensity is about 0.76 ℃, and AH emission to that is about 0.17 ℃. The combined effects of LU change and AH emission in old urban areas are greater than those in new urban areas, leading to changes in daily mean 2-m air temperature, 2-m relative humidity (RH), and heat index in old (new) urban areas to be 1.08 ℃ (0.75 ℃), – 5.93% (– 4.96%), and 2.77 ℃ (1.76 ℃), respectively. At the end of the twenty-first century, the urban air temperature under RCP 4.5 (RCP 8.5) scenario is 0.7 ℃ (3 ℃) higher than that at present.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The MODIS products used in this study can be downloaded from https://lpdaac.usgs.gov/tools/data-pool/. The GLASS LAI products were obtained from National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn). The Daily Surface Climate Dataset for China (V3.0) can be obtained from http://data.cma.cn/.

References

  • Adachi SA, Kimura F, Kusaka H, Inoue T, Ueda H (2012) Comparison of the impact of global climate changes and urbanization on summertime future climate in the Tokyo metropolitan area. J Appl Meteorol Clim 51:2074–2075

    Article  Google Scholar 

  • Arnfield AJ (2003) Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol 23:1–26

    Article  Google Scholar 

  • Bruyere CL, Monaghan AJ, Steinhoff DF, Yates D (2015) Bias-corrected CMIP5 CESM data in WRF/MPAS intermediate file format. NCAR Technical Note TN-515+STR, National Center for Atmospheric Research: Boulder, CO, 27 pp.

  • Buzan JR, Oleson K, Huber M (2015) Implementation and comparison of a suite of heat stress metrics within the Community Land Model version 4.5. Geosci Model Dev 8:151–170

    Article  Google Scholar 

  • Cao Q, Yu D, Georgescu M, Wu J (2016) Impacts of urbanization on summer climate in China: an assessment with coupled land-atmospheric modeling. J Geophys Res 121:10505–510521

    Article  Google Scholar 

  • 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 129:569–585

    Article  Google Scholar 

  • Chen F, Mitchell K, Schaake J, Xue Y, Pan H, Koren V, Duan Q, Ek M, Betts A (1996) Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J Geophys Res 101:7251–7268

    Article  Google Scholar 

  • Chen F, Yang X, Wu J (2016a) Simulation of the urban climate in a Chinese megacity with spatially heterogeneous anthropogenic heat data. J Geophys Res 121:5193–5212

    Article  Google Scholar 

  • Chen F, Yang X, Zhu W (2014) WRF simulations of urban heat island under hot-weather synoptic conditions: the case study of Hangzhou City, China. Atmos Res 138:364–377

    Article  Google Scholar 

  • Chen G, Zhao LH, Mochida A (2016b) Urban heat island simulations in Guangzhou, China, using the coupled WRF/UCM model with a land use map extracted from remote sensing data. Sustainability 8:628

    Article  Google Scholar 

  • Chen L, Frauenfeld OW (2014) Surface air temperature changes over the twentieth and twenty-first centuries in China simulated by 20 CMIP5 models. J Climate 27:3920–3937

    Article  Google Scholar 

  • Chen L, Frauenfeld OW (2016) Impacts of urbanization on future climate in China. Climate Dyn 47:345–357

    Article  Google Scholar 

  • Chen Q, Yang XC, Ouyang Z, Zhao NZ, Jiang QT, Ye TT, Qi J, Yue WZ (2020) Estimation of anthropogenic heat emissions in China using Cubist with points-of-interest and multisource remote sensing data. Environ Pollut 266:115183

    Article  Google Scholar 

  • Conlon K, Monaghan A, Hayden M, Wilhelmi O (2016) Potential impacts of future warming and land use changes on intra-urban heat exposure in Houston, Texas. PLoS One 11

  • Elvidge CD, Baugh K, Dietz J, Bland T, Sutton P, Kroehl H (1999) Radiance calibration of DMSP-OLS low-light imaging data of human settlements. Remote Sens Environ 68:77–88

    Article  Google Scholar 

  • Elvidge CD, Baugh K, Kihn E, Kroehl H, Davis E (1997) Mapping city lights with nighttime data from the DMSP operational linescan system. Photogramm Eng Rem S 63:727–734

    Google Scholar 

  • Elvidge CD, Imhoff ML, Baugh KE, Hobson VR, Nelson I, Safran J, Dietz JB, Tuttle BT (2001) Night-time lights of the world: 1994–1995. Isprs J Photogramm 56:81–99

    Article  Google Scholar 

  • Gao Y, Fu J, Drake JB, Liu Y, Lamarque JF (2012) Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system. Environ Res Lett 7

  • Holt T, Pullen J (2007) Urban canopy modeling of the New York City metropolitan area: a comparison and validation of single- and multilayer parameterizations. Mon Wea Rev 135:1906–1930

    Article  Google Scholar 

  • IPCC (2013) Summary for Policymakers. In: Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA

  • Iizuka S (2018) Future environmental assessment and urban planning by downscaling simulations. J Wind Eng Ind Aerod 181:69–78

    Article  Google Scholar 

  • Jacquemin B, Noilhan J (1990) Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY data set. Bound -Layer Meteor 52:93–134

    Article  Google Scholar 

  • Jones PD, Lister DH, Li Q (2008) Urbanization effects in large-scale temperature records, with an emphasis on China. J Geophys Res 113:D16122

    Article  Google Scholar 

  • Kikumoto H, Ooka R, Arima Y (2016) A study of urban thermal environment in Tokyo in summer of the 2030s under influence of global warming. Energy Buildings 114:54–61

    Article  Google Scholar 

  • Kong SSK, Sentian J, Chuang MT, Ooi MCG, Chee FP, Chang JHW (2019) Simulation analysis of the future surface ozone in Malaysian region under representative concentration pathways (RCPs) emission scenarios. Int J Environ Sci Te 16:7357–7374

    Article  Google Scholar 

  • Kuo CC, Gan TY, Wang JW (2020) Climate change impact to Mackenzie river Basin projected by a regional climate model. Clim Dynam 54:7–8

    Article  Google Scholar 

  • Kusaka H, Kimura F (2004) Thermal effects of urban canyon structure on the nocturnal heat island: numerical experiment using a mesoscale model coupled with an urban canopy model. J Appl Meteor 43:1899–1910

    Article  Google Scholar 

  • Kusaka H, Kondo H, Kikegawa Y, Kimura F (2001) A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Bound -Layer Meteor 101:329–358

    Article  Google Scholar 

  • Lee HS, Trihamdani AR, Kubota T, Iizuka S, Phuong TTT (2017) Impacts of land use changes from the Hanoi Master Plan 2030 on urban heat islands: Part 2. Influence of global warming. Sustain Cities Soc 31:95–108

    Article  Google Scholar 

  • Li D, Bou-Zeid E (2014) Quality and sensitivity of high-resolution numerical simulation of urban heat islands. Environ Res Lett 9

  • Li HD, Zhou YY, Wang X, Zhou X, Zhang HW, Sodoudi S (2019a) Quantifying urban heat island intensity and its physical mechanism using WRF/UCM. Sci Total Eeviron 650:3110–3119

    Article  Google Scholar 

  • Li Y, Zhang JC, Sailor DJ, Ban-Weiss GA (2019b) Effects of urbanization on regional meteorology and air quality in Southern California. Atmos Chem Phys 19:4439–4457

    Article  Google Scholar 

  • Li M, Song Y, Huang X, Li J, Mao Y, Zhu T, Cai X, Liu B (2014) Improving mesoscale modeling using satellite-derived land surface parameters in the Pearl River Delta region, China. J Geophys Res 119:6325–6346

    Article  Google Scholar 

  • Liao W, Wang D, Liu X, Wang G, Zhang J (2017) Estimated influence of urbanization on surface warming in Eastern China using time-varying land use data. Int J Climatol 37:3197–3208

    Article  Google Scholar 

  • Liu B, Xie ZH, Qin PH, Liu S, Li RC, Wang LH, Wang Y, Jia BH, Chen S, Xie JB, Shi CX (2021) Increases in anthropogenic heat release from energy consumption lead to more frequent extreme heat events in urban cities. Adv Atmos Sci 38:430–445

    Article  Google Scholar 

  • Liu M, Tian H (2010) China's land cover and land use change from 1700 to 2005: Estimations from high-resolution satellite data and historical archives. Global Biogeochem Cy 24

  • Lu D, Tian H, Zhou G, Ge H (2008) Regional mapping of human settlements in southeastern China with multisensor remotely sensed data. Remote Sens Environ 112:3668–3679

    Article  Google Scholar 

  • Ma SX, Pitman A, Hart M, Evans JP, Haghdadi N, MacGill I (2017) The impact of an urban canopy and anthropogenic heat fluxes on Sydney’s climate. Int J Climatol 37:255–270

    Article  Google Scholar 

  • Menberg K, Blum P, Schaffitel A, Bayer P (2013) Long-term evolution of anthropogenic heat fluxes into a subsurface urban heat island. Environ Sci Technol 47:9747–9755

    Article  Google Scholar 

  • Meng X, Lü S, Zhang T, Guo J, Gao Y, Bao Y, Wen L, Luo S, Liu Y (2009) Numerical simulations of the atmospheric and land conditions over the Jinta oasis in northwestern China with satellite-derived land surface parameters. J Geophys Res 114

  • Miao S, Chen F, LeMone MA, Tewari M, Li Q, Wang Y (2009) An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing. J Appl Meteorol Clim 48:484–501

    Article  Google Scholar 

  • Morris KI, Chan A, Morris KJK, Ooi MCG, Oozeer MY, Abakr YA, Nadzir MSM, Mohammed IY, Al-Qrimli HF (2017) Impact of urbanization level on the interactions of urban area, the urban climate, and human thermal comfort. Appl Geogr 79:50–72

    Article  Google Scholar 

  • Morris KI, Salleh SA, Chan A, Ooi MCG, Abakr YA, Oozeer MY, Duda M (2015) Computational study of urban heat island of Putrajaya, Malaysia. Sustain Cities Soc 19:359–372

    Article  Google Scholar 

  • Nie W, Zaitchik BF, Ni G, Sun T (2017) Impacts of anthropogenic heat on summertime rainfall in Beijing. J Hydrometeorol 18:693–712

    Article  Google Scholar 

  • Pielke RA (2001) Influence of the spatial distribution of vegetation and soils on the prediction of cumulus Convective rainfall. Rev Geophys 39:151–177

    Article  Google Scholar 

  • Roberto SJ, Pérez JL, González RM, Pecci J, Garzón A, Palacios M (2016) Impacts of the 4.5 and 8.5 RCP global climate scenarios on urban meteorology and air quality: application to Madrid, Antwerp, Milan, Helsinki and London. J Comput Appl Math 293:192–207

    Article  Google Scholar 

  • Sertel E, Robock A, Ormeci C (2010) Impacts of land cover data quality on regional climate simulations. Int J Climatol 30:1942–1953

    Article  Google Scholar 

  • Schneider A, Mertes CM (2014) Expansion and growth in Chinese cities, 1978–2010. Environ Res Lett 9:024008

    Article  Google Scholar 

  • Skamarock WC, Klemp JB, Dudhia J, Gill DO, Liu Z, Berner J, Wang W, Powers JG, Duda MG, Barker DM, Huang X (2019) A description of the advanced research WRF model version 4. NCAR Technical Note, NCAR/TN-556+STR, Note NCAR/TN‐5561STR

  • Taha H (1996) Modeling impacts of increased urban vegetation on ozone air quality in the South Coast Air Basin. Atmos Environ 30:3423–3430

    Article  Google Scholar 

  • Tewari M, Chen F, Kusaka H, Miao S (2007) Coupled WRF/unified Noah/urban-canopy modeling system. NCAR Boulder 1–22

  • 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 121:1511–1531

    Article  Google Scholar 

  • Vahmani P, Hogue TS (2014) High-resolution land surface modeling utilizing remote sensing parameters and the Noah UCM: a case study in the Los Angeles Basin. Hydrol Earth Syst Sci 18:4791–4806

    Article  Google Scholar 

  • Victor B, Stephen S, Werner VB, Martin C, Eva B, Wolfgang C (2004) Role of land cover changes for atmospheric CO2 increase and climate change during the last 150 years. Global Change Biol 10:1253–1266

    Article  Google Scholar 

  • Wang J, Kotamarthi VR (2015) High-resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America. Earth’s Future 3:268–288

    Article  Google Scholar 

  • Wang Y, Leung L, McGregor J, Lee D, Wang W, Ding Y, Kimura F (2004) Regional climate modeling: progress, challenges, and prospects. J Meteorol Soc Jan 82:1599–1628

    Article  Google Scholar 

  • Xiao Z, Liang S, Wang J, Chen P, Yin X, Zhang L, Song J (2014) Use of general regression neural networks for generating the GLASS leaf area index product from time-series MODIS surface reflectance. IEEE Trans Geosci Remote Sens 52:209–223

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Xie M, Liao JB, Wang TJ, Zhu KG, Zhuang BL, Han Y, Li MM, Li S (2016a) Modeling of the anthropogenic heat flux and its effect on regional meteorology and air quality over the Yangtze River Delta region, China. Atmos Chem Phys 16:6071–6089

    Article  Google Scholar 

  • Xie M, Zhu KG, Wang TJ, Feng W, Gao D, Li MM, Li S, Zhuang BL, Han Y, Chen PL, Liao JB (2016b) Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China. Atmos Chem Phys 16:15011–15031

    Article  Google Scholar 

  • Yahya K, Campbell P, Zhang Y (2017) Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations. Atmos Environ 152:584–604

    Article  Google Scholar 

  • Yang B, Yang X, Leung LR, Zhong S, Qian Y, Zhao C, Chen F, Zhang Y, Qi J (2019) Modeling the impacts of urbanization on summer thermal comfort: the role of urban land use and anthropogenic heat. J Geophys Res 124:6681–6697

    Article  Google Scholar 

  • Yang Y, Shi T, Xun S, Tang W, Zhang H, Zhang A (2011) Impact of Hefei urbanization on temperature observation based on remote sensing data. Meteor Mon 37:1432–1430

    Google Scholar 

  • Yucel I (2006) Effects of implementing MODIS land cover and albedo in MM5 at two contrasting US regions. J Hydrometeorol 7:1043–1060

    Article  Google Scholar 

  • Zhao S, Zhou D, Zhu C, Sun Y, Wu W, Liu S (2015) Spatial and temporal dimensions of urban expansion in China. Environ Sci Technol 49:9600–9609

    Article  Google Scholar 

Download references

Funding

This research was jointly funded by the Chinese Academy of Sciences Basic Frontier Science Research Program from 0 to 1 Original Innovation Project (Grant No. ZDBS-LY-DQC005-01), Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20060101), the National Natural Science Foundation of China (Grant No. 41875031, 91837208), and the Chinese Academy of Sciences (Grant No. QYZDJ-SSW-DQC019).

Author information

Authors and Affiliations

  1. School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China

    Yang Zhao, Lei Zhong, Yunfei Fu, Chun Zhao, Ziyu Huang & Keqi Zhou

  2. CAS Center for Excellence in Comparative Planetology, Hefei, 230026, China

    Lei Zhong

  3. Jiangsu Collaborative Innovation Center for Climate Change, Nanjing, 210023, China

    Lei Zhong

  4. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Science, Beijing, 100101, China

    Yaoming Ma & Weiqiang Ma

  5. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101, China

    Yaoming Ma & Weiqiang Ma

  6. College of Earth and Planetary Sciences, University of Chinese Academy of Science, Beijing, 100049, China

    Yaoming Ma

  7. Frontier Center for Eco-Environment and Climate Change in Pan-Third Pole Regions, Lanzhou University, Lanzhou, 730000, China

    Yaoming Ma

  8. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China

    Mingxing Chen

Authors
  1. Yang Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lei Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yaoming Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yunfei Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mingxing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weiqiang Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chun Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ziyu Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Keqi Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

L.Z. conceptualized this study; L.Z., Y.Z., Y.M., and Y.F. designed the methodology; Y.Z. performed data analysis and wrote the original draft; M.C., W.M., C.Z., Z.H., and K.Z. contributed to edits and revisions.

Corresponding author

Correspondence to Lei Zhong.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2839 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, Y., Zhong, L., Ma, Y. et al. WRF/UCM simulations of the impacts of urban expansion and future climate change on atmospheric thermal environment in a Chinese megacity. Climatic Change 169, 38 (2021). https://doi.org/10.1007/s10584-021-03287-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10584-021-03287-7

Keywords

Search

Navigation