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Key factors governing uncertainty in the response to sunshade 
geoengineering from a comparison of the GeoMIP ensemble and 
a perturbed parameter ensemble

 

Peter J. Irvine^1,*, Olivier Boucher², Ben Kravitz³,Kari Alterskjær⁴, Jason N. S. Cole⁵, Duoying Ji⁶,Andy Jones⁷,  Daniel J. Lunt⁸, John C. Moore⁶,Helene Muri⁴, Ulrike Niemeier⁹, Alan Robock¹⁰,Balwinder Singh³, Simone Tilmes¹¹, Shingo Watanabe¹², Shuting Yang¹³ and Jin-Ho Yoon³

 

1 Institute for Advanced Sustainability Studies, Potsdam, Germany,

2 Laboratoire de Météorologie Dynamique, IPSL, CNRS/UPMC, Paris, France,

3 Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA,

4 Department of Geosciences, University of Oslo, Oslo, Norway,

5 Canadian Centre for Climate Modeling and Analysis, Environment Canada, Toronto, Ontario, Canada,

6 State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China,

7 Met Office Hadley Centre, Exeter, UK,

8 School of Geographical Sciences, University of Bristol, Bristol, UK,

9 Max Planck Institute for Meteorology, Hamburg, Germany,

10 Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey, USA,

11 National Center for Atmospheric Research, Boulder, Colorado, USA,

12 Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan,

13 Danish Meteorological Institute, Copenhagen, Denmark

 

ABSTRACT

Climate model studies of the consequences of solar geoengineering are central to evaluating whether such approaches may help to reduce the harmful impacts of global warming. In this study we compare the sunshade solar geoengineering response of a perturbed parameter ensemble (PPE) of the Hadley Centre Coupled Model version 3 (HadCM3) with a multimodel ensemble (MME) by analyzing the G1 experiment from the Geoengineering Model Intercomparison Project (GeoMIP). The PPE only perturbed a small number of parameters and shares a common structure with the unperturbed HadCM3 model, and so the additional weight the PPE adds to the robustness of the common climate response features in the MME is minor. However, analysis of the PPE indicates some of the factors that drive the spread within the MME. We isolate the role of global mean temperature biases for both ensembles and find that these biases have little effect on the ensemble spread in the hydrological response but do reduce the spread in surface air temperature response, particularly at high latitudes. We investigate the role of the preindustrial climatology and find that biases here are likely a key source of ensemble spread at the zonal and grid cell level. The role of vegetation, and its response to elevated CO2 concentrations through the CO2 physiological effect and changes in plant productivity, is also investigated and proves to have a substantial effect on the terrestrial hydrological response to solar geoengineering and to be a major source of variation within the GeoMIP ensemble.

 

PUBLISHED BY: JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (13): 10.1002

 

SOURCE:  http://onlinelibrary.wiley.com/doi/10.1002/2013JD020716/abstract