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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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