Relative contributions of the uncertainty in climate sensitivity and rate of the heat uptake by the ocean in the uncertainty of the projected climate change
Abstract
Climate sensitivity and rate of the heat uptake by the deep ocean are two main characteristics of the Climate System defining its response to a prescribed external forcing. We study relative contributions of the uncertainty in these two characteristics by means of numerical simulations with the MIT Earth System Model (MESM) of intermediate complexity. The MESM consists of a 2D (zonally averaged) atmospheric model coupled to an anomaly diffusing ocean model. Probability distributions for climate sensitivity and rate of oceanic heat uptake are obtained using available data on radiative forcing and temperature changes over 20th century. The results from three 400-member ensembles of long-term (years 1860 to 3000) climate simulations for the IPCC RCP6.0 forcing scenario will be presented. The values of climate sensitivity and rate of oceanic heat uptake, used in the first ensemble, were chosen by sampling their joint probability distribution. In the other two ensembles uncertainty in only one characteristic was taken into account, while the median value was used for the other. Results show that contribution of the uncertainty in climate sensitivity and rate of heat uptake by the deep ocean into the overall uncertainty in projected surface warming and sea level rise is time dependent. Contribution of the uncertainty in rate of heat uptake into uncertainty in the projected surface air temperature increase is rather similar to that of the uncertainty in climate sensitivity while forcing is increasing, but it becomes significantly smaller after forcing is stabilized. The magnitude of surface warming at the end of 30th century is defined almost exclusively by the climate sensitivity distribution. In contrast, uncertainty in the heat uptake has a noticeable effect on projected sea level rise for the whole period of simulations.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFMGC31B1045S
- Keywords:
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- 1622 GLOBAL CHANGE Earth system modeling