Abstract

Abstract. This paper investigates the impact of the parallel computational uncertainty due to the round-off error on climate simulations using the Community Climate System Model Version 3 (CCSM3). A series of sensitivity experiments have been conducted and the analyses are focused on the Global and Nino3.4 average sea surface temperatures (SST). For the monthly time series, it is shown that the amplitude of the deviation induced by the parallel computational uncertainty is the same order as that of the climate system change. However, the ensemble mean method can reduce the influence and the ensemble member number of 15 is enough to ignore the uncertainty. For climatology, the influence can be ignored when the climatological mean is calculated by using more than 30-yr simulations. It is also found that the parallel computational uncertainty has no distinguishable effect on power spectrum analysis of climate variability such as ENSO. Finally, it is suggested that the influence of the parallel computational uncertainty on Coupled General Climate Models (CGCMs) can be a quality standard or a metric for developing CGCMs.

Highlights

  • Coupled General Circulation Models (CGCMs) have been widely used since they serve as a powerful tool for climate research and prediction

  • The influence cannot be ignored if the computing platform or the CPU distribution scheme used by CGCMs is changed

  • We investigate the influence of the parallel computational uncertainty on climatology

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Summary

Introduction

Coupled General Circulation Models (CGCMs) have been widely used since they serve as a powerful tool for climate research and prediction. Chen et al (2008) introduced the uncertainty of the global mean Sea Surface Temperature (SST) simulated by the Community Climate System Model Version 3 (CCSM3) with different computational platforms or different CPU configuration. Their analysis showed that the simulation results are dependent on the computational environments and the magnitude of uncertainty due to the parallel computational error could be in the same order as that of natural variations in the climate system.

Model description and experimental designs
Impact on simulated periods
Results with the climatological mean
Discussion and conclusion
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