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DTSTART;TZID=Europe/Stockholm:20190614T113000
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UID:submissions.pasc-conference.org_PASC19_sess119_msa173@linklings.com
SUMMARY:Reduced Numerical Precision in Atmosphere Models and Computational
Performance Evaluation
DESCRIPTION:Minisymposium\nClimate and Weather\n\nReduced Numerical Precis
ion in Atmosphere Models and Computational Performance Evaluation\n\nDuebe
n, Acosta\n\nIn atmosphere models values of relevant physical parameters a
re often uncertain by more than 100% and weather forecast skill is decreas
ing significantly after a couple of days. Still, numerical operations are
typically calculated with 15 decimal digits of numerical precision for rea
l numbers. If we reduce numerical precision, we can reduce power consumpti
on and increase computational performance significantly. Savings can be re
invested to allow simulations at higher resolution. We aim to reduce numer
ical precision to the minimal level that can be justified by information c
ontent in the different components of weather and climate models. But how
can we identify the optimal precision for a complex model with chaotic dyn
amics? We found that a comparison between the impact of rounding errors an
d the influence of sub-grid-scale variability can provide valuable informa
tion and that the influence of rounding errors can actually be beneficial
for simulations since variability is increased. We have performed multiple
studies that investigate the use of reduced numerical precision for atmos
pheric applications of different complexity (from Lorenz'95 to global circ
ulation models) and studied the trade of numerical precision against perfo
rmance. Results of a computational performance evaluation will be presente
d during the talk.
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