OS41A-1988
The Human Influence on Global Warming: Sensitivity to AMOC and OHE

Thursday, 17 December 2015
Poster Hall (Moscone South)
Ross J Salawitch1, Austin Patrick Hope2, Nora Rose Mascioli3 and Timothy P Canty2, (1)University of Maryland, College Park, MD, United States, (2)University of Maryland College Park, College Park, MD, United States, (3)Columbia University of New York, Palisades, NY, United States
Abstract:
We use an empirical model of global climate to quantify the role of human activity on global mean surface temperature (GMST), with particular attention to the treatment of Atlantic Meridional Overturning Circulation (AMOC) and the export of heat from the atmosphere to the world’s oceans. The study examines changes in GMST from 1860 to present with particular attention focused on two time periods: 1998 to 2012, the time of the so-called global warming hiatus and 1979 to 2010, a three decade span for which researchers have attempted to quantify the human influence on GMST. We will show that the existence of the global warming hiatus depends on which dataset is used to define GMST: in our model framework there is little or no global warming hiatus upon use of either the recent NOAA record for GMST (Karl et al., 2015) or the use of a revision to the CRU4 dataset suggested by Cowtan and Way (2014). Next, we show that humans have been responsible for 0.13±0.06°C/decade rise in GMST during the past three decades (1979 to 2010), considerably less than the rise in GMST attributed to humans over this same time period (0.17±0.01°C/decade) by Foster and Rahmstorf (2011). We suggest this prior study obtained an erroneously high value due to their neglect of the influence of variations in the strength of the AMOC on global climate. Finally, we’ll provide projections of GMST over the next four decades based on the rise in greenhouse gases (GHGs) given in the four Representative Concentration Pathway scenarios of IPCC AR5. These projections include detailed quantitative assessments of the sensitivity of global warming to the efficiency of ocean heat export, resulting in a probability distribution function of future GMST for each RCP scenario.