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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
Author(s) -
Irvine Peter J.,
Boucher Olivier,
Kravitz Ben,
Alterskjær Kari,
Cole Jason N. S.,
Ji Duoying,
Jones Andy,
Lunt Daniel J.,
Moore John C.,
Muri Helene,
Niemeier Ulrike,
Robock Alan,
Singh Balwinder,
Tilmes Simone,
Watanabe Shingo,
Yang Shuting,
Yoon JinHo
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2013jd020716
Subject(s) - hadcm3 , environmental science , geoengineering , climate change , climatology , robustness (evolution) , ensemble forecasting , grid cell , latitude , climate model , atmospheric sciences , meteorology , grid , general circulation model , gcm transcription factors , mathematics , ecology , biochemistry , chemistry , physics , geometry , biology , geodesy , gene , geology , geography
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 CO 2 concentrations through the CO 2 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.