Weather and Climate Computing Futures in the context of European Competitiveness

Presentation: pdf (4 MB).

In this talk I addressed some elements of how climate science interacts with policy and societal competitiveness in the contentxt of extreme climate events etc, but the main body was on the consequences for modelling and underlying infrastructure.

This table drives much of the conversation:

Key numbers for Climate Earth System Modelling 2012 2016 2020
Horizontal resolution of each coupled model component (km) 125 50 10
Increase in horizontal parallelisation wrt 2012
(hyp: weak scaling in 2 directions)		 1 6.25 156.25
Horizontal parallelization of each coupled model component
(number of cores)		 1,00E+03 6,25E+03 1,56E+05
Vertical resolution of each coupled model component
(number of levels)		 30 50 100
Vertical parallelization of each coupled model component 1 1 10
Number of components in the coupled model 2 2 5
Number of members in the ensemble simulation 10 20 50
Number of models/groups in the ensemble experiments 4 4 4
Total number of cores (4x6x7x8x9)
(Increase:)		 8,00E+04
(1)		 1,00E+06
(13)		 1,56E+09
(19531)
Data produced (for one component in
Gbytes/month-of-simulation)		 2,5 26 1302
Data produced in total (in
Gbytes/month-of-simulation)		 200 4167 1302083
Increase 1 21 6510

The bottom line in the talk was that to deliver on all of this requires European scale infrastructure, that is, computing AND networks targeted at data analysis as well as data production!