The relative importance among anthropogenic forcings of land use/land cover change in affecting temperature extremes
Land use/land cover change (LULCC) exerts significant influence on regional climate extremes, but its relative importance compared with other anthropogenic climate forcings has not been thoroughly investigated. This study compares land use forcing with other forcing agents in explaining the simulated historical temperature extreme changes since preindustrial times in the CESM-Last Millennium Ensemble (LME) project. CESM-LME suggests that the land use forcing has caused an overall cooling in both warm and cold extremes, and has significantly decreased diurnal temperature range (DTR). Due to the competing effects of the GHG and aerosol forcings, the spatial pattern of changes in 1850–2005 climatology of temperature extremes in CESM-LME can be largely explained by the land use forcing, especially for hot extremes and DTR. The dominance of land use forcing is particularly evident over Europe, eastern China, and the central and eastern US. Temporally, the land-use cooling is relatively stable throughout the historical period, while the warming of temperature extremes is mainly influenced by the enhanced GHG forcing, which has gradually dampened the local dominance of the land use effects. Results from the suite of CMIP5 experiments partially agree with the local dominance of the land use forcing in CESM-LME, but inter-model discrepancies exist in the distribution and sign of the LULCC-induced temperature changes. Our results underline the overall importance of LULCC in historical temperature extreme changes, implying land use forcing should be highlighted in future climate projections.
This study was supported by the National Science Foundation (AGS-1419445). We acknowledge the CESM1(CAM5) Last Millennium Ensemble Community Project and supercomputing resources provided by NSF/CISL/Yellowstone. We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.
- Herring SC, Hoell A, Hoerling MP et al (2016) Explaining extreme events of 2015 from a climate perspective. Bull Amer Meteor Soc 97(12):S1–S145. https://doi.org/10.1175/BAMS-ExplainingExtremeEvents2015.1 Google Scholar
- Lawrence PJ, Feddema JJ, Bonan GB et al (2012) Simulating the biogeochemical and biogeophysical impacts of transient land cover change and wood harvest in the community climate system model (CCSM4) from 1850 to 2100. J Clim 25(9):3071–3095. https://doi.org/10.1175/JCLI-D-11-00256.1 CrossRefGoogle Scholar
- Meehl GA, Washington WM, Ammann CM et al (2004) Combinations of natural and anthropogenic forcings in twentieth-century climate. J Climate 17(19):3721–3727. https://doi.org/10.1175/1520-0442(2004)017<3721:CONAAF>2.0.CO;2 CrossRefGoogle Scholar
- Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds.) (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. Cambridge University Press, Cambridge, pp 1535Google Scholar