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Uncertainty in climate change projections

TitleUncertainty in climate change projections
Publication TypeManual Entry
Year of Publication2011
AuthorsLatif, M.
Journal of Geochemical Exploration

Twentieth century climate exhibits a strong warming trend. There is a broad scientific consensus that the warming contains a significant contribution from enhanced atmospheric greenhouse gas (GHG) concentrations due to anthropogenic emissions. The climate will continue to warm during the 21st century due to the large inertia of the Earth System and in response to additional GHG emissions, but by how much remains highly uncertain. This is mainly due to three factors: natural variability, model uncertainty, and GHG emission scenario uncertainty. Uncertainty due to natural variability dominates at short time scales of a few years up to a few decades, while at the longer centennial time scales scenario uncertainty provides the largest contribution to the total uncertainty. Model uncertainty is important at all lead times. Furthermore, our understanding of the Earth System dynamics is incomplete. Potentially important feedbacks such as the carbon cycle feedback are not well understood and not even taken into account in many model projections. Yet the scientific evidence is overwhelming that the global mean surface temperature will exceed a level toward the end of the 21st century that will be unprecedented during the history of mankind, even if strong measures are taken to reduce global GHG emissions. It is this long-term perspective that demands immediate political action. (C) 2010 Elsevier B.V. All rights reserved.

Citation Key119
Community Notes

Latif discusses uncertainty in climate projections due to uncertainties associated with natural variability, model uncertainty, and GHG emission scenario uncertainty.  Natural variability uncertainties are associated with our understanding of natural climate variability and their predictability in events such as volcanic eruptions, ENSO, and Meridional Overturning Circulation.  The uncertainty associated with these events can be limited in near term climate projections by initializing climate models with the observed climate state.  Uncertainty associated with models is seen in the spread of model projections for future climate.  Even models forced with the same GHG concentration or emission scenario produce different outcomes.  A means to improve model uncertainty is to improve physical processes (cloud formation and radiation processes for example) and to replace parameterization schemes with physical processes.  Latif claims that natural variability (internal and external) is the largest contributor to uncertainty in the near term climate and scenario uncertainty is largest for long term climate studies.  Model uncertainty is important for all times.  This article gives a good basic description of the sources of uncertainty in climate model projections.