EGU25-17712, updated on 09 Apr 2025
https://doi.org/10.5194/egusphere-egu25-17712
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Technical improvements with the GLOBO atmospheric model, through collaboration with ESiWACE3
David Guibert1, Loris Lucido1, Erwan Raffin1, Alessio Bellucci2, Paolo Davini2, Federico Fabiano2, Antonella Galizia3, Valerio Lembo2, and Daniele Mastrangelo2
David Guibert et al.
  • 1EVIDEN, CEPP, NANTES, France (david.guibert@eviden.com)
  • 2CNR-ISAC, Bologna, Italy
  • 3CNR-IMATI, Pavia, Italy

GLOBO is an atmospheric general circulation model developed at the Institute of Atmospheric Sciences and Climate of the National Research Council of Italy (CNR-ISAC). It is largely equivalent to the BOLAM atmospheric model, used for synoptic-scale operational numerical weather prediction. The GLOBO model is currently part of the S2S multi-model initiative for prediction at the sub-seasonal to seasonal timescale range. 

Here, we present improvements to the performance of GLOBO that were obtained through collaboration with the ESiWACE3 initiative. This service is aimed at supporting the exascale preparations for the weather and climate modelling community in Europe through the establishment of short collaborative projects between Research Software Engineers (RSEs) and model development groups. These collaborations provide guidance, engineering, and advice to improve model efficiency and port models to existing and upcoming computing infrastructures

The main tasks that were carried out throughout the collaboration were aimed at:

  • getting a better vectorized instruction set on AMD processors using the Intel compilers
  • improving the efficiency of inline functions called inside some loops
  • gathering parallel communications before waiting for the data to be exchanged
  • reducing the number of unnecessary or redundant communications;

The model was tested at a 78km horizontal resolution with a number of processors ranging  between 8 and 240. An improvement in the scalability of the model was observed, leading up to 25-34% speedup (on 240 or 160 processors resp.).

How to cite: Guibert, D., Lucido, L., Raffin, E., Bellucci, A., Davini, P., Fabiano, F., Galizia, A., Lembo, V., and Mastrangelo, D.: Technical improvements with the GLOBO atmospheric model, through collaboration with ESiWACE3, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17712, https://doi.org/10.5194/egusphere-egu25-17712, 2025.