• Anderson, R. G., and Coauthors, 2011: Biophysical considerations in forestry for climate protection. Front. Ecol. Environ., 9, 174182, https://doi.org/10.1890/090179.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson-Teixeira, K. J., P. K. Snyder, T. E. Twine, S. V. Cuadra, M. H. Costa, and E. H. DeLucia, 2012: Climate-regulation services of natural and agricultural ecoregions of the Americas. Nat. Climate Change, 2, 177181, https://doi.org/10.1038/nclimate1346.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and A. Montenegro, 2011: Small temperature benefits provided by realistic afforestation efforts. Nat. Geosci., 4, 514518, https://doi.org/10.1038/ngeo1182.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bala, G., K. Caldeira, M. Wickett, T. J. Phillips, D. B. Lobell, C. Delire, and A. Mirin, 2007: Combined climate and carbon-cycle effects of large-scale deforestation. Proc. Natl. Acad. Sci. USA, 104, 65506555, https://doi.org/10.1073/pnas.0608998104.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barnes, C. A., and D. P. Roy, 2008: Radiative forcing over the conterminous United States due to contemporary land cover land use albedo change. Geophys. Res. Lett., 35, L09706, https://doi.org/10.1029/2008GL033567.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bastiaanssen, W. G. M., M. Menenti, R. A. Feddes, and A. A. M. Holtslagc, 1998: A remote sensing Surface Energy Balance Algorithm for Land (SEBAL). 1. Formulation. J. Hydrol., 212–213, 198212, https://doi.org/10.1016/S0022-1694(98)00253-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Benali, A., A. C. Carvalho, J. P. Numes, N. Carvalhais, and A. Santos, 2012: Estimating air surface temperature in Portugal using MODIS LST data. Remote Sens. Environ., 124, 108121, https://doi.org/10.1016/j.rse.2012.04.024.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Betts, R. A., 2000: Offset of the potential carbon sink from boreal afforestation by decreases in surface albedo. Nature, 408, 187190, https://doi.org/10.1038/35041545.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Betts, R. A., 2011: Afforestation cools more or less. Nat. Geosci., 4, 504505, https://doi.org/10.1038/ngeo1223.

  • Bonan, G. B., 2008: Forests and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 320, 14441449, https://doi.org/10.1126/science.1155121.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brovkin, V., and Coauthors, 2006: Biogeophysical effects of historical land cover changes simulated by six Earth system models of intermediate complexity. Climate Dyn., 26, 587600, https://doi.org/10.1007/s00382-005-0092-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chapin, F. S., III, J. T. Randerson, A. D. McGuire, J. A. Foley, and C. B. Field, 2008: Changing feedbacks in the climate–biosphere system. Front. Ecol. Environ., 6, 313320, https://doi.org/10.1890/080005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Claussen, M., V. Brovkin, and A. Ganopolski, 2001: Biogeophysical versus biogeochemical feedbacks of large-scale land cover change. Geophys. Res. Lett., 28, 10111014, https://doi.org/10.1029/2000GL012471.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clinton, N., and P. Gong, 2013: MODIS detected surface urban heat islands and sinks: Global locations and controls. Remote Sens. Environ., 134, 294304, https://doi.org/10.1016/j.rse.2013.03.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diffenbaugh, N. S., 2009: Influence of modern land cover on the climate of the United States. Climate Dyn., 33, 945958, https://doi.org/10.1007/s00382-009-0566-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fall, S., D. Niyogi, A. Gluhovsky Sr., R. A. Pielke, E. Kalnay, and G. Rochon, 2010: Impacts of land use land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., 30, 19801993, https://doi.org/10.1002/joc.1996.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feddema, J. J., K. W. Oleson, G. B. Bonan, L. O. Mearns, L. E. Buja, G. A. Meehl, and W. M. Washington, 2005: The importance of land-cover change in simulating future climates. Science, 310, 16741678, https://doi.org/10.1126/science.1118160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Field, C. B., D. B. Lobell, H. A. Peters, and N. R. Chiariello, 2007: Feedbacks of terrestrial ecosystems to climate change. Annu. Rev. Environ. Resour., 32, 129, https://doi.org/10.1146/annurev.energy.32.053006.141119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Forzieri, G., R. Alkama, D. G. Miralles, and A. Cescatti, 2017: Satellites reveal contrasting responses of regional climate to the widespread greening of Earth. Science, 356, 11801184, https://doi.org/10.1126/science.aal1727.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hallgren, W., C. A. Schlosser, E. Monier, D. Kicklighter, A. Sokolov, and J. Melillo, 2013: Climate impacts of a large-scale biofuels expansion. Geophys. Res. Lett., 40, 16241630, https://doi.org/10.1002/grl.50352.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jackson, R., and Coauthors, 2008: Protecting climate with forests. Environ. Res. Lett., 3, 044006, https://doi.org/10.1088/1748-9326/3/4/044006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, M., and S. Liang, 2006: An improved land surface emissivity parameter for land surface models using global remote sensing observations. J. Climate, 19, 28672881, https://doi.org/10.1175/JCLI3720.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, A. D., and Coauthors, 2013a: Greenhouse gas policy influences climate via direct effects of land-use change. J. Climate, 26, 36573670, https://doi.org/10.1175/JCLI-D-12-00377.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, A. D., W. D. Collins, and M. S. Torn, 2013b: On the additivity of radiative forcing between land use change and greenhouse gases. Geophys. Res. Lett., 40, 40364041, https://doi.org/10.1002/grl.50754.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, H., and S. Liang, 2010: Development of a new hybrid method for estimating land surface shortwave net radiation from MODIS data. Remote Sens. Environ., 114, 23932402, https://doi.org/10.1016/j.rse.2010.05.012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kueppers, L. M., M. A. Snyder, and L. C. Sloan, 2007: Irrigation cooling effect: Regional climate forcing by land‐use change. Geophys. Res. Lett., 34, L03703, https://doi.org/10.1029/2006GL028679.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawrence, P. J., and T. N. Chase, 2010: Investigating the climate impacts of global land cover change in the community climate system model. Int. J. Climatol., 30, 20662087, https://doi.org/10.1002/joc.2061.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, X., and Coauthors, 2011: Observed increase in local cooling effect of deforestation at higher latitudes. Nature, 479, 384387, https://doi.org/10.1038/nature10588.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., M. S. Zhao, S. Motesharrei, Q. Mu, E. Kalnay, and S. Li, 2015: Local cooling and warming effects of forests based on satellite observations. Nat. Commun., 6, 6603, https://doi.org/10.1038/ncomms7603.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, J., and Coauthors, 2014: Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J. Geogr. Sci., 24, 195210, https://doi.org/10.1007/s11442-014-1082-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, J., Q. Shao, X. Yan, J. Fan, J. Zhan, X. Deng, W. Kuang, and L. Huang, 2016: The climatic impacts of land use and land cover change compared among countries. J. Geogr. Sci., 26, 889903, https://doi.org/10.1007/s11442-016-1305-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loarie, S. R., D. B. Lobell, G. P. Asner, Q. Mu, and C. B. Field, 2011: Direct impacts on local climate of sugar-cane expansion in Brazil. Nat. Climate Change, 1, 105109, https://doi.org/10.1038/nclimate1067.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, C. N., and K. L. Gaustad, 2004: The shortwave (SW) clear-sky detection and fitting algorithm: Algorithm operational details and explanations. Pacific Northwest National Laboratory Doc. DOE/SC-ARM/TR-004.1, 24 pp., https://doi.org/10.2172/1020737.

    • Crossref
    • Export Citation
  • Luyssaert, S., and Coauthors, 2014: Land management and land-cover change have impacts of similar magnitude on surface temperature. Nat. Climate Change, 4, 389393, https://doi.org/10.1038/nclimate2196.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahmood, R., and Coauthors, 2010: Impacts of land use/land cover change on climate and future research priorities. Bull. Amer. Meteor. Soc., 91, 3746, https://doi.org/10.1175/2009BAMS2769.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McAlpine, C., and Coauthors, 2010: More than CO2: A broader paradigm for managing climate change and variability to avoid ecosystem collapse. Curr. Opin. Environ. Sustainability, 2, 334346, https://doi.org/10.1016/j.cosust.2010.10.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mu, Q., M. S. Zhao, and S. Running, 2011: Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ., 115, 17811800, https://doi.org/10.1016/j.rse.2011.02.019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pan, Y., and Coauthors, 2011: A large and persistent carbon sink in the world’s forests. Science, 333, 988993, https://doi.org/10.1126/science.1201609.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, S. S., and Coauthors, 2012: Surface urban heat island across 419 global big cities. Environ. Sci. Technol., 46, 696703, https://doi.org/10.1021/es2030438.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, S. S., and Coauthors, 2013: Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature, 501, 8892, https://doi.org/10.1038/nature12434.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, S. S., and Coauthors, 2014: Afforestation in China cools local land surface temperature. Proc. Natl. Acad. Sci. USA, 111, 29152919, https://doi.org/10.1073/pnas.1315126111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., G. Marland, R. A. Betts, T. N. Chase, J. L. Eastman, J. O. Niles, D. Niyogi, and S. W. Running, 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. Roy. Soc. London, 360A, 17051719, https://doi.org/10.1098/rsta.2002.1027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pitman, A. J., and Coauthors, 2009: Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study. Geophys. Res. Lett., 36, L14814, https://doi.org/10.1029/2009GL039076.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pitman, A. J., F. B. Avila, G. Abramowitz, Y. P. Wang, S. J. Phipps, and N. de Noblet-Ducoudré, 2011: Importance of background climate in determining impact of land-cover change on regional climate. Nat. Climate Change, 1, 472475, https://doi.org/10.1038/nclimate1294.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pongratz, J., C. H. Reick, T. Raddatz, and M. Claussen, 2010: Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change. Geophys. Res. Lett., 37, 162169, https://doi.org/10.1029/2010GL043010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Román, M. O., and Coauthors, 2010: Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes. Remote Sens. Environ., 114, 738760, https://doi.org/10.1016/j.rse.2009.11.014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotenberg, E., and D. Yakir, 2010: Contribution of semi-arid forests to the climate system. Science, 327, 451454, https://doi.org/10.1126/science.1179998.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wan, L., X. P. Zhang, Q. Ma, J. J. Zhang, T. Y. Ma, and Y. P. Ma, 2014: Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009. Hydrol. Processes, 28, 49714983, https://doi.org/10.1002/hyp.9951.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Q.-X., M.-B. Wang, X.-H. Fan, F. Zhang, S.-Z. Zhu, and T.-L. Zhao, 2017: Trends of temperature and precipitation extremes in the Loess Plateau Region of China, 1961–2010. Theor. Appl. Climatol., 129, 949963, https://doi.org/10.1007/s00704-016-1820-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Werth, D., and R. Avissar, 2002: The local and global effects of Amazon deforestation. J. Geophys. Res., 107, 8087, https://doi.org/10.1029/2001JD000717.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, L., X. Lee, R. B. Smith, and K. Oleson, 2014: Strong contributions of local background climate to urban heat islands. Nature, 511, 216219, https://doi.org/10.1038/nature13462.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zheng, J. Y., J. J. Bian, Q. S. Ge, Z. X. Hao, Y. H. Yin, and Y. M. Liao, 2013: The climate regionalization in China for 1981–2010. Chin. Sci. Bull., 58, 30883099.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 38 38 24
PDF Downloads 29 29 19

Biogeophysical Forcing of Land-Use Changes on Local Temperatures across Different Climate Regimes in China

View More View Less
  • 1 Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
  • 2 Satellite Environment Center, Ministry of Environmental Protection, Beijing, China
  • 3 National Climate Center, China Meteorological Administration, Beijing, China
  • 4 Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
© Get Permissions
Restricted access

Abstract

Land-use changes (LUCs) strongly influence regional climates through both the biogeochemical and biogeophysical processes. However, many studies have ignored the biogeophysical processes, which in some cases can offset the biogeochemical impacts. We integrated the field observations, satellite-retrieved data, and a conceptual land surface energy balance model to provide new evidence to fill our knowledge gap concerning how regional warming or cooling is affected by the three main types of LUCs (afforestation, cropland expansion, and urbanization) in different climate zones of China. According to our analyses, similar LUCs presented varied, even reverse, biogeophysical forcing on local temperatures across different climate regimes. Afforestation in arid and semiarid regions has caused increased net radiation that has typically outweighed increased latent evapotranspiration, thus warming has been the net biogeophysical effect. However, it has resulted in cooling in subtropical zones because the increase in net radiation has been exceeded by the increase in latent evapotranspiration. Cropland expansion has decreased the net radiation more than latent evapotranspiration, which has resulted in biogeophysical cooling in arid and semiarid regions. Conversely, it has caused warming in subtropical zones as a result of increases in net radiation and decreases in latent evapotranspiration. In all climatic regions, the net biogeophysical effects of urbanization have generally resulted in more or less warming because urbanization has led to smaller net radiation decreases than latent evapotranspiration. This study reinforces the need to adjust land-use policies to consider biogeophysical effects across different climate regimes and to adapt to and mitigate climate change.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-17-0116.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: J. Zhai, zhaij@lreis.ac.cn

Abstract

Land-use changes (LUCs) strongly influence regional climates through both the biogeochemical and biogeophysical processes. However, many studies have ignored the biogeophysical processes, which in some cases can offset the biogeochemical impacts. We integrated the field observations, satellite-retrieved data, and a conceptual land surface energy balance model to provide new evidence to fill our knowledge gap concerning how regional warming or cooling is affected by the three main types of LUCs (afforestation, cropland expansion, and urbanization) in different climate zones of China. According to our analyses, similar LUCs presented varied, even reverse, biogeophysical forcing on local temperatures across different climate regimes. Afforestation in arid and semiarid regions has caused increased net radiation that has typically outweighed increased latent evapotranspiration, thus warming has been the net biogeophysical effect. However, it has resulted in cooling in subtropical zones because the increase in net radiation has been exceeded by the increase in latent evapotranspiration. Cropland expansion has decreased the net radiation more than latent evapotranspiration, which has resulted in biogeophysical cooling in arid and semiarid regions. Conversely, it has caused warming in subtropical zones as a result of increases in net radiation and decreases in latent evapotranspiration. In all climatic regions, the net biogeophysical effects of urbanization have generally resulted in more or less warming because urbanization has led to smaller net radiation decreases than latent evapotranspiration. This study reinforces the need to adjust land-use policies to consider biogeophysical effects across different climate regimes and to adapt to and mitigate climate change.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-17-0116.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: J. Zhai, zhaij@lreis.ac.cn

Supplementary Materials

    • Supplemental Materials (PDF 1.35 MB)
Save