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Proposing Institution

Institute of atmospheric Sciences and Climate (ISAC-CNR)
Project Manager

Dr. Jost von Hardenberg
Corso Fiume 4
I-10133 Torino
Current climate models are still unable to represent many important climate features, such as weather regimes and midlatitude blocking, and recent studies have shown that they may benefit if they were resolved at higher resolutions (~16km). Instead of explicitly resolving small-scale processes by increasing the resolution of climate models, an alternative is to use stochastic parameterization schemes. There is mounting evidence that these schemes, by including a statistical representation of small-scale variability, are able also to represent the upscale propagation of errors and to improve the simulation of large-scale climate variability.Climate SPHINX aims at investigating the sensitivity of climate simulations to model resolution and stochastic parameterisations, and to determine if very high resolution is truly necessary to facilitate the simulation of the main features of climate variability. The EC-Earth Earth-System model will be used to explore the impact of Stochastic Physics in long centennial climate integrations as a function both of model resolution (from 80km to 16km for the atmosphere and from 1° to 0.25° for the ocean), in coupled and uncoupled configurations. The experiments will include historical and scenario projection following CMIP5 specifications. Comparing high and low resolutions integrations will allow to estimate the impact of the increased resolution, while comparing experiments with and without the implementation of stochastic physics will allow to estimate the impact of stochastic physics. A comparison of experiments with stochastic physics with experiments carried out without stochastic physics, but at higher resolutions, will help to determine to what extent the stochastic representation of the sub-grid processes can compare with an explicit representation. By exploring extensively and systematically the respective role of numerical resolution and stochastic parameterisations in improving climate simulation quality, this project aims at allowing more reliable climate predictions.

Impressum, Conny Wendler