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| Titel |
An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0) |
| VerfasserIn |
E. Monier, J. R. Scott, A. P. Sokolov, C. E. Forest, C. A. Schlosser |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 6 ; Nr. 6, no. 6 (2013-12-04), S.2063-2085 |
| Datensatznummer |
250085021
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| Publikation (Nr.) |
 copernicus.org/gmd-6-2063-2013.pdf |
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| Zusammenfassung |
| This paper describes a computationally efficient framework for uncertainty
studies in global and regional climate change. In this framework, the
Massachusetts Institute of Technology (MIT) Integrated Global System Model
(IGSM), an integrated assessment model that couples an Earth system model of
intermediate complexity to a human activity model, is linked to the National
Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM).
Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity
model, it is possible to analyze uncertainties in emissions resulting from
both uncertainties in the underlying socio-economic characteristics of the
economic model and in the choice of climate-related policies. Another major
feature is the flexibility to vary key climate parameters controlling the
climate system response to changes in greenhouse gases and aerosols
concentrations, e.g., climate sensitivity, ocean heat uptake rate, and
strength of the aerosol forcing. The IGSM-CAM is not only able to
realistically simulate the present-day mean climate and the observed trends
at the global and continental scale, but it also simulates ENSO variability
with realistic time scales, seasonality and patterns of SST anomalies, albeit
with stronger magnitudes than observed. The IGSM-CAM shares the same general
strengths and limitations as the Coupled Model Intercomparison Project Phase
3 (CMIP3) models in simulating present-day annual mean surface temperature
and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR
Community Climate System Model (CCSM) version 3, which shares the same
atmospheric model. This study also presents 21st century simulations based on
two emissions scenarios (unconstrained scenario and stabilization scenario at
660 ppm CO2-equivalent) similar to, respectively, the Representative
Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate
parameters. Results of the simulations with the chosen climate parameters
provide a good approximation for the median, and the 5th and 95th percentiles
of the probability distribution of 21st century changes in global mean
surface air temperature from previous work with the IGSM. Because the
IGSM-CAM framework only considers one particular climate model, it cannot be
used to assess the structural modeling uncertainty arising from differences
in the parameterization suites of climate models. However, comparison of the
IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and
RCP8.5 scenarios show that the range of warming at the continental scale
shows very good agreement between the two ensemble simulations, except over
Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates
that by sampling the climate system response, the IGSM-CAM, even though it
relies on one single climate model, can essentially reproduce the range of
future continental warming simulated by more than 30 different models.
Precipitation changes projected in the IGSM-CAM simulations and the CMIP5
multi-model ensemble both display a large uncertainty at the continental
scale. The two ensemble simulations show good agreement over Asia and Europe.
However, the ranges of precipitation changes do not overlap – but display
similar size – over Africa and South America, two continents where models
generally show little agreement in the sign of precipitation changes and
where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an
efficient and consistent framework to explore the large uncertainty in future
projections of global and regional climate change associated with uncertainty
in the climate response and projected emissions. |
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