TY - JOUR
T1 - An evaluation of the software system dependency of a global atmospheric model
AU - Hong, Song You
AU - Koo, Myung Seo
AU - Jang, Jihyeon
AU - Esther Kim, Jung Eun
AU - Park, Hoon
AU - Joh, Min Su
AU - Kang, Ji Hoon
AU - Oh, Tae Jin
PY - 2013/11
Y1 - 2013/11
N2 - 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 a result of 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 systemis comparable to the ensemble spread due to the differences in initial conditions that is used for the traditional ensemble forecasting.
AB - 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 a result of 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 systemis comparable to the ensemble spread due to the differences in initial conditions that is used for the traditional ensemble forecasting.
UR - https://www.scopus.com/pages/publications/84888413626
U2 - 10.1175/MWR-D-12-00352.1
DO - 10.1175/MWR-D-12-00352.1
M3 - Article
AN - SCOPUS:84888413626
SN - 0027-0644
VL - 141
SP - 4165
EP - 4172
JO - Monthly Weather Review
JF - Monthly Weather Review
IS - 11
ER -