Oral Presentation:

Island observations as proxies for precipitation sensitivity to temperature over oceans


D. Polson, G. C. Hegerl and S. Solomon


Abstract: Some of the most damaging impacts of climate change are a consequence of changes to the global water cycle, with atmospheric warming causing the water cycle to intensify, increasing global precipitation and enhancing existing patterns of precipitation minus evaporation (P - E). While observed changes to atmospheric water vapour concentrations are consistent with the Clausius-Clapeyron relationship at ~7 %/K, energy budget constraints limit the increase in global precipitation to ~2-3 %/K in climate models. However, calculating observed precipitation sensitivity to temperature (dP/dT) over the 20th century is made difficult by the absence of longstanding observational records in much of the world, in particular changes to ocean precipitation can not be assessed for the pre-satellite era (pre-1979). Satellite observations suggest a large increase in precipitation with temperature over wet tropical ocean regions, with climate models capturing the sign but underestimating the magnitude of these changes. Here, we analyze longer (1930-2005), islands-based observations to estimate precipitation sensitivity in ocean regions for an independent, in-situ dataset. We calculate dP/dT for islands observations of precipitation and show that as in the satellite observations, dP/dT can exceed the Clausius-Clapeyron scaling in wet tropical ocean regions. Furthermore, the islands records clearly show the expected pattern of increasing precipitation in the tropics and decreasing precipitation in the subtropics predicted from physical arguments. Analysis of daily station data also shows that heavy precipitation has increased more than mean precipitation which has important implications for soil erosion on vulnerable tropical islands.




Oral Presentation:

The importance of ENSO phase during volcanic eruptions for detection and attribution


Flavio Lehner1, Andrew P. Schurer2, Gabriele C. Hegerl2, Clara Deser1, and Thomas L. Frölicher3


1Climate Analysis Section, National Center for Atmospheric Research, Boulder, USA

2School of Geosciences, University of Edinburgh, Edinburgh, UK

3Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Switzerland


Detection and attribution methods applied to the Coupled Model Intercomparison Project 5 (CMIP5) models indicate that, from 1951 to present day, the models overestimate the magnitude of the global mean surface temperature response to natural radiative forcing changes, in particular volcanic eruptions. Here we show that this overestimation might merely be a sampling issue, arising because all three large tropical volcanic eruptions since 1951 coincided with El Niño events, which cause global-scale warming that partially counteracts the volcanically-induced cooling. By subsampling the CMIP5 models according to the observed El Niño Southern Oscillation (ENSO) phase during each eruption, we find that the simulated global mean surface temperature response to volcanic forcing is consistent with observations. Volcanic eruptions pose a particular challenge for the detection and attribution methodology, as their surface impacts are relatively short-lived and hence can be confounded by internal variability, in this case ENSO, even if the methodology implicitly accounts for internal variability. Our results imply that detection and attribution studies must carefully consider sampling biases due to internal climate variability induced by ENSO and other phenomena.




Oral Presentation:

Probabilistic estimation of climate changes by large ensemble experiment


Chiharu Takahashi1 and d4PDF group


1 Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan


 A number of uncertainties for the global warming prediction exist in the CMIP5 simulations. Especially, one of the problems is the inadequate evaluations of the change in natural variability for extreme climate and weather with less-frequency. Here, we generate the “database for Policy Decision making for Future climate change (d4PDF)” which is a large ensemble up to 100 members of the past and future climate simulations using a high-resolution Meteorological Research Institute (MRI) atmospheric general and regional circulation models. By use of the large-ensembles, we are able to identify probabilistic changes in extreme phenomena such as heavy rainfall, heat wave, and typhoon. The natural variability simulation that is removed the warming trend from a past climate enables attribution analyses to past weather events. The research project on event attribution (EA) by large-ensembles is also being advanced using our atmosphere-ocean coupled model, MIROC5. Overviews and examples for the probabilistic estimation of climate changes in global warming and EA are presented.





Oral Presentation:

Does the rate of change of extreme precipitation intensity depend on the forcing?

Angeline Pendergrass

The rate of increase of global-mean precipitation per degree global-mean surface temperature increase differs for greenhouse gas and aerosol forcings. I will show that, in contrast, the rate of increase of extreme precipitation per degree global-mean surface temperature increase averaged over large spatial scales does not depend on the type of forcing in most CMIP5 models.  Implications for detection and attribution will be discussed.





Oral Presentation:

Attribution of extreme events using the W@H ANZ system


David Karoly, Mitchell Black, Andrew King, Fredi Otto and Sue Rosier


A brief overview of some activities with the weather@home ANZ modelling system for attribution of extreme events in Australia. Specific events and activities that will be presented include:

  • Real-time attribution of record October 2015 monthly maximum temperatures for Melbourne, the state of Victoria and across Australia prior to the end of the month, assessing the role of global warming in addition to El Niño
  • Attribution of record high mslp anomalies in winter 2014
  • The impact of perturbed physics ensembles on rainfall extremes in Australia



Poster Presentation:

Competitive influences on droughts: present and future


Celine Bonfils


A “super El Niño” with above-normal precipitation over California is providing some drought relief in the region. We argue that ENSO is not always be a source of relief in the future in regions where the mean change in terrestrial aridity/moistening in response to greenhouse warming becomes larger than the expected range of current variability. We use a suite of state-of-the-art climate model simulations to identify the regions where a projected change in aridity exists, and consider whether this change is large enough to overwhelm the effect of local drying/moistening associated with ENSO variability. 


By the end of the 21st century, warming is expected virtually everywhere, independent of the phase of ENSO. In contrast, expectations regarding the net anomalies in regional precipitation are less evident, because changes in the mean state and variability are governed by a number of different, spatially-complex mechanisms. Here, we provide a comprehensive assessment of the relative contributions to future drought from changes in moisture supply and demand. We also investigate the competing effects of mean changes and ENSO variability in terms of ameliorating or exacerbating drought.


This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.



Poster Presentation:

Does External Forcing Interfere with the AMOC’s Influence on North Atlantic Sea Surface Temperature?


Neil F. Tandon and Paul J. Kushner,


J. Climate, 28, 6309-6323, doi:10.1175/JCLI-D-14-00664.1


Numerous studies have suggested that variations in the strength of the Atlantic meridional overturning circulation (AMOC) may drive predictable variations in North Atlantic sea surface temperature (NASST). How- ever, two recent studies have presented results suggesting that coupled models disagree on both the sign and the phasing of the correlation between AMOC and NASST indices. These studies analyzed linearly detrended output from twentieth-century historical simulations in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The present study argues that the apparent disagreement among models arises from a comingling of two processes: 1) a bottom-up effect in which unforced AMOC changes lead to NASST changes of the same sign and 2) a top-down effect in which forced NASST changes lead to AMOC changes of the opposite sign. Linear detrending is not appropriate for separating these two effects because the time scales of forced and unforced variations are not well separated. After forced variations are properly removed, the models come into much closer agreement with each other. This argument is supported by analysis of CMIP5 historical simulations, as well as preindustrial control simulations and a 29-member ensemble of the Community Earth System Model, version 1, covering the period 1920–2005. Additional analysis is presented suggesting that, even after the data are linearly detrended, a significant portion of observed NASST persistence may be externally forced.



Poster Presentation:

Predicting future uncertainty constraints on global warming projections


H. Shiogama1*, D. Stone2, S. Emori1, K. Takahashi3, S. Mori4, A. Maeda5, Y. Ishizaki1 & M. R. Allen6, 7


1Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan

2Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

3Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan

4Department of Industrial Administration, Faculty of Science and Technology, Tokyo University of Science, Chiba 278-8510, Japan

5Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo, 153-8902, Japan

6School of Geography and the Environment, University of Oxford, OX1 3QY, Oxford, UK

7Department of Physics, University of Oxford, OX1 3QY, Oxford, UK


Projections of global mean temperature changes (DT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by “current knowledge” of the DTsuncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of DT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the DTs uncertainty in the 2040s by 2029, and more than 60% of the DTs uncertainty in the 2090s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.