Influence of parallel computational uncertainty on simulations of the Coupled General Climate Model
Influence of parallel computational uncertainty on simulations of the Coupled General Climate Model
复制标题
DOI：
10.5194/gmd-5-313-2012
复制
发表时间：
2011-11
影响因子：
5.1
通讯作者：
Zhenya Song;F. Qiao;X. Lei;Chunzai Wang
中科院分区：
文献类型：
--
作者：
Zhenya Song;F. Qiao;X. Lei;Chunzai Wang
抽象。本文研究了由于舍入误差引起的并行计算不确定性对使用共同体气候系统模式第三版（CCSM 3）进行气候模拟的影响。对全球和Nino3.4平均海表温度（SST）进行了一系列敏感性试验和分析。对于月时间序列，它表明，由并行计算的不确定性所导致的偏差的幅度是相同的数量级的气候系统的变化。然而，集合平均法可以减少影响，集合成员数为15就足以忽略不确定性。对于气候学而言，当使用超过30年的模拟计算气候平均值时，可以忽略这种影响。并行计算的不确定性对ENSO等气候变率的功率谱分析没有明显的影响。最后，提出了并行计算不确定性对耦合气候模式（CGCM）的影响可以作为发展CGCM的质量标准或度量。
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.