Effective radiative forcing from historical land use change

The effective radiative forcing (ERF) from the biogeophysical effects of historical land use change is quantified using the atmospheric component of the Met Office Hadley Centre Earth System model HadGEM2-ES. The global ERF at 2005 relative to 1860 (1700) is −0.4 (−0.5) Wm−2, making it the fourth most important anthropogenic driver of climate change over the historical period (1860–2005) in this model and larger than most other published values. The land use ERF is found to be dominated by increases in the land surface albedo, particularly in North America and Eurasia, and occurs most strongly in the northern hemisphere winter and spring when the effect of unmasking underlying snow, as well as increasing the amount of snow, is at its largest. Increased bare soil fraction enhances the seasonal cycle of atmospheric dust and further enhances the ERF. Clouds are shown to substantially mask the radiative effect of changes in the underlying surface albedo. Coupled atmosphere–ocean simulations forced only with time-varying historical land use change shows substantial global cooling (dT = −0.35 K by 2005) and the climate resistance (ERF/dT = 1.2 Wm−2 K−1) is consistent with the response of the model to increases in CO2 alone. The regional variation in land surface temperature change, in both fixed-SST and coupled atmosphere–ocean simulations, is found to be well correlated with the spatial pattern of the forced change in surface albedo. The forcing-response concept is found to work well for historical land use forcing—at least in our model and when the forcing is quantified by ERF. Our results suggest that land-use changes over the past century may represent a more important driver of historical climate change then previously recognised and an underappreciated source of uncertainty in global forcings and temperature trends over the historical period.

[1]  K. Taylor,et al.  Quantifying components of aerosol‐cloud‐radiation interactions in climate models , 2014 .

[2]  Andrei P. Sokolov,et al.  Climate Dynamics (2006) DOI 10.1007/s00382-005-0092-6 , 2005 .

[3]  J. Gregory,et al.  Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change , 2012 .

[4]  Jeffrey T. Kiehl,et al.  Twentieth century climate model response and climate sensitivity , 2007 .

[5]  R. Houghton,et al.  Terminology as a key uncertainty in net land use and land cover change carbon flux estimates , 2014 .

[6]  P. Jones,et al.  Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set , 2012 .

[7]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[8]  T. Andrews Using an AGCM to Diagnose Historical Effective Radiative Forcing and Mechanisms of Recent Decadal Climate Change , 2014 .

[9]  Jonathan M. Gregory,et al.  Transient climate response estimated from radiative forcing and observed temperature change , 2008 .

[10]  C. Jones,et al.  Climatic impacts of land-use change due to crop yield increases and a universal carbon tax from a scenario model , 2014 .

[11]  J. Houghton,et al.  Climate Change 2013 - The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change , 2014 .

[12]  P. Stott,et al.  Uncertainties in the attribution of greenhouse gas warming and implications for climate prediction , 2016, 1606.05108.

[13]  Nicolas Bellouin,et al.  Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability , 2012, Nature.

[14]  S. Woodward,et al.  Modeling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model , 2001 .

[15]  M. Webb,et al.  Sensitivity of an Earth system climate model to idealized radiative forcing , 2012 .

[16]  V. Ramaswamy,et al.  Nonlocal component of radiative flux perturbation , 2012 .

[17]  R. Betts Offset of the potential carbon sink from boreal forestation by decreases in surface albedo , 2000, Nature.

[18]  D. Shindell,et al.  Anthropogenic and Natural Radiative Forcing , 2014 .

[19]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[20]  Johannes Quaas,et al.  Total aerosol effect: radiative forcing or radiative flux perturbation? , 2009 .

[21]  Peter E. Thornton,et al.  Greenhouse Gas Policy Influences Climate via Direct Effects of Land-Use Change , 2013 .

[22]  C. Müller,et al.  Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study , 2009 .

[23]  Alejandro Bodas-Salcedo,et al.  Evaluation of the Surface Radiation Budget in the Atmospheric Component of the Hadley Centre Global Environmental Model (HadGEM1) , 2008 .

[24]  R. Knutti,et al.  How well do climate models simulate precipitation , 2010 .

[25]  J. Hansen,et al.  Efficacy of climate forcings , 2005 .

[26]  C. Jones,et al.  The HadGEM2 family of Met Office Unified Model climate configurations , 2011 .

[27]  K. Taylor,et al.  Estimating shortwave radiative forcing and response in climate models , 2007 .

[28]  Victor Brovkin,et al.  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 , 2012 .

[29]  G. Cesana,et al.  How well do climate models simulate cloud vertical structure? A comparison between CALIPSO‐GOCCP satellite observations and CMIP5 models , 2012 .

[30]  B. Soden,et al.  An Assessment of Climate Feedbacks in Coupled Ocean–Atmosphere Models , 2006 .

[31]  J. Singarayer,et al.  The Role of CO2 and Dynamic Vegetation on the Impact of Temperate Land-Use Change in the HadCM3 Coupled Climate Model , 2016 .

[32]  Kees Klein Goldewijk,et al.  Biogeophysical effects of land use on climate : Model simulations of radiative forcing and large-scale temperature change , 2007 .

[33]  O. Boucher,et al.  Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2‐ES and the role of ammonium nitrate , 2011 .

[34]  T. Andrews,et al.  Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models , 2013 .

[35]  Olivier Boucher,et al.  Adjustments in the Forcing-Feedback Framework for Understanding Climate Change , 2014 .

[36]  P. Stott,et al.  Observed 21st century temperatures further constrain likely rates of future warming , 2012 .

[37]  M. Claussen,et al.  Radiative forcing from anthropogenic land cover change since A.D. 800 , 2009 .

[38]  S. Seneviratne,et al.  The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models , 2015, Climate Dynamics.

[39]  E. Stehfest,et al.  Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands , 2011 .

[40]  G. Hegerl,et al.  The role of land use change in the recent warming of daily extreme temperatures , 2013 .

[41]  Manoj Joshi,et al.  An alternative to radiative forcing for estimating the relative importance of climate change mechanisms , 2003 .

[42]  R. Bright,et al.  Radiative forcing bias of simulated surface albedo modifications linked to forest cover changes at northern latitudes , 2015 .

[43]  Pierre Friedlingstein,et al.  Impact of land cover change on surface climate: Relevance of the radiative forcing concept , 2007 .

[44]  K. Taylor,et al.  Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere‐ocean climate models , 2012 .

[45]  P. Valdes,et al.  Last glacial maximum radiative forcing from mineral dust aerosols in an Earth system model , 2015 .

[46]  Thomas Raddatz,et al.  Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change , 2010 .

[47]  O. Boucher,et al.  Aerosol forcing, climate response and climate sensitivity in the Hadley Centre climate model , 2007 .

[48]  O. Boucher,et al.  Direct human influence of irrigation on atmospheric water vapour and climate , 2004 .

[49]  C. Jones,et al.  Development and evaluation of an Earth-System model - HadGEM2 , 2011 .

[50]  Piers M. Forster,et al.  CO2 forcing induces semi‐direct effects with consequences for climate feedback interpretations , 2008 .

[51]  J. Lamarque,et al.  The HadGEM2-ES implementation of CMIP5 centennial simulations , 2011 .

[52]  Bas Eickhout,et al.  Impacts of future land cover changes on atmospheric CO2 and climate , 2005 .

[53]  P. Valdes,et al.  Last glacial maximum constraints on the Earth System model HadGEM2-ES , 2015, Climate Dynamics.

[54]  J. Randerson,et al.  Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model , 2010 .

[55]  C. Jones,et al.  Interactive comment on “ Development and evaluation of an Earth-system model – HadGEM 2 ” , 2011 .

[56]  Jonathan M. Gregory,et al.  A new method for diagnosing radiative forcing and climate sensitivity , 2004 .

[57]  Nathalie de Noblet-Ducoudré,et al.  Climatic Impact of Global-Scale Deforestation: Radiative versus Nonradiative Processes , 2010 .

[58]  Leon D. Rotstayn,et al.  Indirect Aerosol Forcing, Quasi Forcing, and Climate Response , 2001 .

[59]  V. Brovkin,et al.  Effect of Anthropogenic Land-Use and Land-Cover Changes on Climate and Land Carbon Storage in CMIP5 Projections for the Twenty-First Century , 2013 .

[60]  Steven J. Phipps,et al.  Importance of background climate in determining impact of land-cover change on regional climate , 2011 .