Abstract

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

Highlights

  • The simulation and prediction of Earth’s climate is one of the scientific and computational grand challenges

  • A detailed analysis of the mean climate in all the simulations performed would be excessively long to be included in the present work, we introduce a couple of figures showing the sensitivity to resolution and stochastic physics parameterisation of the climatology of precipitation (Fig. 5)

  • In the present work we have described the scientific configuration and technical set-up/tuning of the EC-Earth Earth system model used for the Climate SPHINX project, which defines the SPHINX v1.0 protocol

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Summary

Introduction

The simulation and prediction of Earth’s climate is one of the scientific and computational grand challenges. As was the case for the mean state, the observed improvements can be similar to that observed on increasing the resolution of the model (Dawson et al, 2012) These results highlight the influence of small-scale processes on large-scale climate variability, and indicate that simulating variability at small scales is a necessity, it may not be necessary to represent the small scales accurately, or even explicitly, in order to improve the simulation of large-scale climate. By comparing integrations carried out at different resolutions, we evaluate the impact of increased atmospheric horizontal resolution on the simulation of key climate processes and of climate variability.

The EC-Earth global climate model
The stochastic physics parameterisation schemes
Model tuning
Climate SPHINX simulations
Initial conditions
Forcing and boundary conditions
Present-day SST and SIC
Future scenario SST and SIC
High-performance computing details
GB 24 GB 35 GB 57 GB 111 GB
Results overview
Mean climate
Tropical rainfall variability
The Madden–Julian Oscillation variability
Mid-latitude atmospheric blocking variability
Conclusions
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