A new ensemble of GCM simulations to assess avoided impacts in a climate mitigation scenario

There is growing evidence that the role internal variability plays in our confidence in future climate projections has been under-appreciated in past assessments of model projections for the coming decades. In light of this, a 15 member ensemble has been produced to complement the existing 30 member “Large Ensemble” conducted with the Community Earth System Model (CESM). In contrast to the Large Ensemble, which explored the variability in RCP8.5, our new ensemble uses the moderate mitigation scenario represented by RCP4.5. By comparing outputs from these two ensembles, we assess at what point in the future the climates conditioned on the two scenarios will begin to significantly diverge. We find in general that while internal variability is a significant component of uncertainty for periods before 2050, there is evidence of a significantly increased risk of extreme warm events in some regions as early as 2030 in RCP8.5 relative to RCP4.5. Furthermore, the period 2061-2080 sees largely separate joint distributions of annual mean temperature and precipitation in most regions for the two ensembles. Hence, in the CESM’s representation of the Earth System for the latter portion of the 21st century, the range of climatic states which might be expected in the RCP8.5 scenario is significantly and detectably further removed from today’s climate state than the RCP4.5 scenario even in the presence of internal variability.

[1]  C. Brooks Climatic Change , 1913, Nature.

[2]  E. Fischer,et al.  The usefulness of different realizations for the model evaluation of regional trends in heat waves , 2013 .

[3]  E. Fischer,et al.  Robust spatially aggregated projections of climate extremes , 2013 .

[4]  M. Kainuma,et al.  An emission pathway for stabilization at 6 Wm−2 radiative forcing , 2011 .

[5]  J. Edmonds,et al.  RCP4.5: a pathway for stabilization of radiative forcing by 2100 , 2011 .

[6]  Andrew J. Pitman,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 , 2012 .

[7]  W. Collins,et al.  The Community Earth System Model: A Framework for Collaborative Research , 2013 .

[8]  E. Lorenz The predictability of a flow which possesses many scales of motion , 1969 .

[9]  W. G. Strand,et al.  How much climate change can be avoided by mitigation? , 2009 .

[10]  N. Nakicenovic,et al.  Scenarios of long-term socio-economic and environmental development under climate stabilization , 2007 .

[11]  C. Tebaldi,et al.  Delayed detection of climate mitigation benefits due to climate inertia and variability , 2013, Proceedings of the National Academy of Sciences.

[12]  K. Oleson,et al.  Avoided climate impacts of urban and rural heat and cold waves over the U.S. using large climate model ensembles for RCP8.5 and RCP4.5 , 2018, Climatic Change.

[13]  Reto Knutti,et al.  A Representative Democracy to Reduce Interdependency in a Multimodel Ensemble , 2015 .

[14]  Brian C. O'Neill,et al.  Sensitivity of regional climate to global temperature and forcing , 2015 .

[15]  D. Nychka,et al.  The emerging anthropogenic signal in land–atmosphere carbon-cycle coupling , 2014 .

[16]  Reto Knutti,et al.  Early onset of significant local warming in low latitude countries , 2011 .

[17]  W. G. Strand,et al.  Climate Change Projections in CESM1(CAM5) Compared to CCSM4 , 2013 .

[18]  C. Deser,et al.  Uncertainty in climate change projections: the role of internal variability , 2012, Climate Dynamics.

[19]  Leo Schrattenholzer,et al.  MESSAGE-MACRO: Linking an energy supply model with a macroeconomic module and solving it iteratively , 2000 .

[20]  J. Lamarque,et al.  The importance of aerosol scenarios in projections of future heat extremes , 2018, Climatic Change.

[21]  G. Meehl,et al.  Systematic Estimates of Initial-Value Decadal Predictability for Six AOGCMs , 2012 .

[22]  E. Stehfest,et al.  RCP2.6: exploring the possibility to keep global mean temperature increase below 2°C , 2011 .

[23]  Raquel V. Francisco,et al.  Uncertainties in regional climate change prediction: a regional analysis of ensemble simulations with the HADCM2 coupled AOGCM , 2000 .

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

[25]  J. Lowe,et al.  Comparing the impacts of mitigation versus non-intervention scenarios on future temperature and precipitation extremes in the HadGEM2 climate model , 2012 .

[26]  A. Thomson,et al.  The representative concentration pathways: an overview , 2011 .

[27]  D. Streets,et al.  Dangerous human-made interference with climate: a GISS modelE study , 2006, physics/0610115.

[28]  Ed Hawkins,et al.  Influence of internal variability on Arctic sea-ice trends , 2015 .

[29]  Pete Smith,et al.  A global assessment of the effects of climate policy on the impacts of climate change , 2013 .