New paper finds the same climate model produces different results when run on different computers

As if climate models didn't already have enough problems, a paper published today in the Monthly Weather Review finds that the same climate model run on different computer hardware and operating systems produces different results, "primarily due to the treatment of rounding errors by the different software systems" and that these errors propagate over time. According to the authors, "The [hardware & software] system dependency, which is the standard deviation of the 500-hPa geopotential height [areas of high & low pressure] averaged over the globe, increases with time." The authors find, "the ensemble spread due to the differences in software system is comparable to the ensemble spread due to the differences in initial conditions that is used for the traditional ensemble forecasting." The initial conditions of climate models have already been shown by many papers to produce significantly different projections of climate. 

Could climate catastrophe be due to a rounding error?

Monthly Weather Review 2013 ; e-View

doi: http://dx.doi.org/10.1175/MWR-D-12-00352.1

An Evaluation of the Software System Dependency of a Global Atmospheric Model

Song-You Hong,¹ Myung-Seo Koo,¹ Jihyeon Jang,¹ Jung-Eun Esther Kim,² Hoon Park,^1,3 Min-Su Joh,⁴ Ji-Hoon Kang,⁴ and Tae-Jin Oh⁵

¹ Department of Atmospheric Sciences, Yonsei University, Seoul, Korea

² National Oceanic and Atmospheric Administration (NOAA)/Earth System Research Laboratory (ESRL), Boulder, Colorado, USA

³ Numerical Weather Prediction center, Korea Meteorological Administration, Seoul, Korea

⁴ Supercomputer Center, Korea Institute of Science and Technology Information, Daejeon, Korea

⁵ Korea Institute of Atmospheric Prediction Systems, Seoul, Korea

Abstract

This study presents the dependency of the simulation results from a global atmospheric numerical model on machines with different hardware and software systems. The global model program (GMP) of the Global/Regional Integrated Model system (GRIMs) is tested on 10 different computer systems having different central processing unit (CPU) architectures or compilers. There exist differences in the results for different compilers, parallel libraries, and optimization levels, primarily due to the treatment of rounding errors by the different software systems. The system dependency, which is the standard deviation of the 500-hPa geopotential height averaged over the globe, increases with time. However, its fractional tendency, which is the change of the standard deviation relative to the value itself, remains nearly zero with time. In a seasonal prediction framework, the ensemble spread due to the differences in software system is comparable to the ensemble spread due to the differences in initial conditions that is used for the traditional ensemble forecasting.