Article | Published:

Local temperature response to land cover and management change driven by non-radiative processes

Nature Climate Change volume 7, pages 296302 (2017) | Download Citation

Abstract

Following a land cover and land management change (LCMC), local surface temperature responds to both a change in available energy and a change in the way energy is redistributed by various non-radiative mechanisms. However, the extent to which non-radiative mechanisms contribute to the local direct temperature response for different types of LCMC across the world remains uncertain. Here, we combine extensive records of remote sensing and in situ observation to show that non-radiative mechanisms dominate the local response in most regions for eight of nine common LCMC perturbations. We find that forest cover gains lead to an annual cooling in all regions south of the upper conterminous United States, northern Europe, and Siberia—reinforcing the attractiveness of re-/afforestation as a local mitigation and adaptation measure in these regions. Our results affirm the importance of accounting for non-radiative mechanisms when evaluating local land-based mitigation or adaptation policies.

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References

  1. 1.

    Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

  2. 2.

    et al. Land use/land cover changes and climate: modeling analysis and observational evidence. WIREs Clim. Change 2, 828–850 (2011).

  3. 3.

    et al. Land cover changes and their biogeophysical effects on climate. Int. J. Climatol. 34, 929–953 (2013).

  4. 4.

    et al. The importance of land-cover change in simulating future climates. Science 310, 1674–1678 (2005).

  5. 5.

    Implications of land ecosystem-atmosphere interactions for strategies for climate change adaptation and mitigation. Tellus B 59, 602–615 (2007).

  6. 6.

    et al. 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. Phil. Trans. R. Soc. Lond. A 360, 1705–1719 (2002).

  7. 7.

    , , , & Separating the effects of albedo from eco-physiological changes on surface temperature along a successional chronosequence in the southeastern United States. Geophys. Res. Lett. 34, L21408 (2007).

  8. 8.

    et al. Land management and land-cover change have impacts of similar magnitude on surface temperature. Nat. Clim. Change 4, 389–393 (2014).

  9. 9.

    et al. Observed increase in local cooling effect of deforestation at higher latitudes. Nature 479, 384–387 (2011).

  10. 10.

    , , , & New insights in the capability of climate models to simulate the impact of LUC based on temperature decomposition of paired site observations. J. Geophys. Res. 120, 2015JD023095 (2015).

  11. 11.

    , & On the additivity of radiative forcing between land use change and greenhouse gases. Geophys. Res. Lett. 40, 4036–4041 (2013).

  12. 12.

    , & Impact of land cover change on surface climate: relevance of the radiative forcing concept. Geophys. Res. Lett. 34, L13702 (2007).

  13. 13.

    et al. Tradeoffs between three forest ecosystem services across the state of New Hampshire, USA: timber, carbon, and albedo. Ecol. Appl. 26, 146–161 (2015).

  14. 14.

    et al. Quantifying the climate impacts of albedo changes due to biofuel production: a comparison with biogeochemical effects. Enviro. Res. Lett. 9, 024015 (2014).

  15. 15.

    & Contribution of semi-arid forests to the climate system. Science 327, 451–454 (2010).

  16. 16.

    et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 659–740 (IPCC, Cambridge Univ. Press, 2013).

  17. 17.

    et al. Climate-regulation services of natural and agricultural ecoregions of the Americas. Nat. Clim. Change 2, 177–181 (2012).

  18. 18.

    , , , & An alternative approach for quantifying climate regulations by ecosystems. Front. Ecol. Environ. 9, 126–133 (2011).

  19. 19.

    IPCC 2006 IPCC Guidelines for National Greenhouse Gas Inventories (eds Eggleston, H. S., Buendia, L., Miwa, K., Ngara, T. & Tanabe, K.) Vol. 4 (IGES, 2006).

  20. 20.

    et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. 116, G00J07 (2011).

  21. 21.

    et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834–838 (2010).

  22. 22.

    & How will land use affect air temperature in the surface boundary layer? Lessons learned from a comparative study on the energy balance of an oak savanna and annual grassland in California, USA. Tellus B 65, 19994 (2013).

  23. 23.

    , , & Strong contributions of local background climate to urban heat islands. Nature 511, 216–219 (2014).

  24. 24.

    & Adapting observationally based metrics of biogeophysical feedbacks from land cover/land use change to climate modeling. Environ. Res. Lett. 11, 034002 (2016).

  25. 25.

    & Land surface skin temperature climatology: benefitting from the strengths of satellite observations. Environ. Res. Lett. 5, 044004 (2010).

  26. 26.

    et al. Uncertainties in climate responses to past land cover change: first results from the LUCID intercomparison study. Geophys. Res. Lett. 36, L14814 (2009).

  27. 27.

    et al. Attributing the impacts of land-cover changes in temperate regions on surface temperature and heat fluxes to specific causes: results from the first LUCID set of simulations. J. Geophys. Res. 117, D12116 (2012).

  28. 28.

    et al. Response of surface air temperature to small-scale land clearing across latitudes. Environ. Res. Lett. 9, 034002 (2014).

  29. 29.

    et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).

  30. 30.

    et al. Local cooling and warming effects of forests based on satellite observations. Nat. Commun. 6, 6603 (2015).

  31. 31.

    & Biophysical forcings of land-use changes from potential forestry activities in North America. Ecol. Monogr. 84, 329–353 (2014).

  32. 32.

    et al. Satellite-derived land surface temperature: current status and perspectives. Remote Sens. Environ. 131, 14–37 (2013).

  33. 33.

    , & Mid-latitude afforestation shifts general circulation and tropical precipitation. Proc. Natl Acad. Sci. USA 109, 712–716 (2011).

  34. 34.

    , & Robust identification of local biogeopysical effects of land-cover change in a global climate model. J. Clim. 30, 1159–1176 (2017).

  35. 35.

    , , & 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 (2015).

  36. 36.

    et al. Land use/cover change impacts in CMIP5 climate simulations: a new methodology and 21st century challenges. J. Geophys. Res. 118, 6337–6353 (2013).

  37. 37.

    & Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).

  38. 38.

    et al. Global land cover mapping from MODIS: algorithms and early results. Remote Sens. Environ. 83, 287–302 (2002).

  39. 39.

    et al. Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US. Glob. Change Biol. 12, 2115–2135 (2006).

  40. 40.

    et al. Europe’s forest management did not mitigate climate warming. Science 351, 597–600 (2016).

  41. 41.

    et al. Cooling of US Midwest summer temperature extremes from cropland intensification. Nat. Clim. Change 6, 317–322 (2016).

  42. 42.

    & Three distinct global estimates of historical land-cover change and land-use conversions for over 200 years. Front. Earth Sci. 6, 122–139 (2012).

  43. 43.

    et al. The role of land use change on the development and evolution of the west coast trough, convective clouds, and precipitation in southwest Australia. J. Geophys. Res. 116, D07103 (2011).

  44. 44.

    et al. The net carbon drawdown of small scale afforestation from satellite observations. Glob. Planet. Change 69, 195–204 (2009).

  45. 45.

    , , , & Changes in Arctic vegetation amplify high-latitude warming through the greenhouse effect. Proc. Natl Acad. Sci. USA 107, 1295–1300 (2010).

  46. 46.

    , , & Carbon equivalent metrics for albedo changes in land management contexts: relevance of the time dimension. Ecol. Appl. 26, 1868–1880 (2016).

  47. 47.

    Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408, 187–190 (2000).

  48. 48.

    et al. Importance of background climate in determining impact of land-cover change on regional climate. Nat. Clim. Change 1, 472–475 (2011).

  49. 49.

    et al. Greening of the Earth and its drivers. Nat. Clim. Change 6, 791–795 (2016).

  50. 50.

    , & Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. 11, 1633–1644 (2007).

  51. 51.

    et al. Multi-scale climatological albedo look-up maps derived from MODIS BRDF/albedo products. J. Appl. Remote Sens. 8, 083532-1 (2014).

  52. 52.

    et al. Relations between albedos and emissivities from MODIS and ASTER data over North African Desert. Geophys. Res. Lett. 30, 2026 (2003).

  53. 53.

    et al. Energy balance closure at FLUXNET sites. Agric. For. Meteorol. 113, 223–243 (2002).

  54. 54.

    , & 2006: MODIS/Terra Snow Cover Monthly L3 Global 0.05Deg CMG, Version 5 (National Snow and Ice Data Center (NSIDC), accessed 11 November 2015);

  55. 55.

    et al. Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances. J. Clim. 26, 2719–2740 (2012).

  56. 56.

    & Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (1950–1999) (Univ. Delaware, 2001);

  57. 57.

    et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ. 83, 214–231 (2002).

  58. 58.

    et al. Development and evaluation of an Earth-System model—HadGEM2. Geosci. Model Dev. 4, 1051–1075 (2011).

  59. 59.

    World Research Climate Programme. CMIP5 Multi-Model Ensemble “HadGEM2-ES historicalGHG_r1i1p1” (US Department of Energy/Lawrence Livermore National Laboratory, accessed 23 November 2016);

Download references

Acknowledgements

R.M.B. was supported with funding provided by The Research Council of Norway (250113/F20) and the Norwegian Ministry of Food and Agriculture (355002). J.P. was supported by German Research Foundation’s Emmy Noether Program (PO 1751/1-1). A.C. was supported by EU-FP7-LUC4C (603542).

Author information

Affiliations

  1. The Norwegian Institute of Bioeconomy Research, 1431 Ås, Norway

    • Ryan M. Bright
  2. Institute for Atmospheric and Climate Science, ETH-Zürich, 8092 Zürich, Switzerland

    • Edouard Davin
  3. Department of Forestry and Environmental Conservation, Clemson University, Clemson, South Carolina 29634, USA

    • Thomas O’Halloran
  4. Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, South Carolina 29440, USA

    • Thomas O’Halloran
  5. Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany

    • Julia Pongratz
  6. School of Environment and Natural Resources, OARDC, The Ohio State University, Wooster, Ohio 44691, USA

    • Kaiguang Zhao
  7. European Commission, Joint Research Centre, Directorate for Sustainable Resources, I-21027 Ispra (VA), Italy

    • Alessandro Cescatti

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Contributions

R.M.B. conceived and scoped the study, downloaded and analysed data, produced figures, and wrote the manuscript. All authors contributed equally to the analysis and interpretation of data, drafting and revising the article critically for important intellectual content, and approving the final version to be published.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Ryan M. Bright.

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https://doi.org/10.1038/nclimate3250

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