Quantifying the Likelihood of Regional Cimate Change: A hybridized Approach
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MITJPSPGC_Rpt205.pdf
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Author(s)
Schlosser, C. Adam
Forest, C.
Awadalla, S.
Farmer, W.
Gao, X.
Strzepek, K.
Date Issued
September 2011
Publisher
MIT Joint Program on the Science and Policy of Global Change
Citation
Report no. 205
Series/Report no.
Joint Program Report Series;205
Abstract
The growing need for risk-based assessments of impacts and adaptation to climate change calls for
increased capability in climate projections: the quantification of the likelihood of regional outcomes
and the representation of their uncertainty. Herein, we present a technique that extends the latitudinal
projections of the 2-D atmospheric model of the MIT Integrated Global System Model (IGSM) by
applying longitudinally resolved patterns from observations, and from climate-model projections
archived from exercises carried out for the 4th Assessment Report (AR4) of the Intergovernmental
Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a
set of transformation coefficients, and we demonstrate this approach in application to near-surface
air temperature and precipitation, for which high-quality observational datasets and model
simulations of climate change are available. The current climatology of the transformation
coefficients is observationally based. To estimate how these coefficients may alter with climate, we
characterize the climate models’ spatial responses, relative to their zonal mean, from transient
increases in trace-gas concentrations and then normalize these responses against their corresponding
transient global temperature responses. This procedure allows for the construction of meta-ensembles
of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and
latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with
regionally resolved patterns from the archived IPCC climate-model projections. This approach also
provides a hybridization of the climate-model longitudinal projections with the global and latitudinal
patterns projected by the IGSM, and can be applied to any given state or flux variable that has the
sufficient observational and model-based information.
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