Paxton, EA, Chantry, M, Klöwer, M et al. (2 more authors) (2022) Climate Modeling in Low Precision: Effects of Both Deterministic and Stochastic Rounding. Journal of Climate, 35 (4). pp. 1215-1229. ISSN 0894-8755
Abstract
Motivated by recent advances in operational weather forecasting, we study the efficacy of low-precision arithmetic for climate simulations. We develop a framework to measure rounding error in a climate model, which provides a stress test for a low-precision version of the model, and we apply our method to a variety of models including the Lorenz system, a shallow water approximation for flow over a ridge, and a coarse-resolution spectral global atmospheric model with simplified parameterizations (SPEEDY). Although double precision [52 significant bits (sbits)] is standard across operational climate models, in our experiments we find that single precision (23 sbits) is more than enough and that as low as half precision (10 sbits) is often sufficient. For example, SPEEDY can be run with 12 sbits across the code with negligible rounding error, and with 10 sbits if minor errors are accepted, amounting to less than 0.1 mm (6 h)−1 for average gridpoint precipitation, for example. Our test is based on the Wasserstein metric and this provides stringent nonparametric bounds on rounding error accounting for annual means as well as extreme weather events. In addition, by testing models using both round-to-nearest (RN) and stochastic rounding (SR) we find that SR can mitigate rounding error across a range of applications, and thus our results also provide some evidence that SR could be relevant to next-generation climate models. Further research is needed to test if our results can be generalized to higher resolutions and alternative numerical schemes. However, the results open a promising avenue toward the use of low-precision hardware for improved climate modeling.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 American Meteorological Society. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) |
Keywords: | Error analysis; Numerical analysis/modeling; Climate models |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > National Centre for Atmos Science (NCAS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Apr 2022 11:58 |
Last Modified: | 22 Apr 2022 11:58 |
Status: | Published |
Publisher: | American Meteorological Society |
Identification Number: | 10.1175/JCLI-D-21-0343.1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185933 |