Single precision in weather forecasting models: An evaluation with the IFS
Earth’s climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model’s physical variables as a function of scale and variable type. Answering this questi...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
American Meteorological Society
2017
|
| _version_ | 1797083855636660224 |
|---|---|
| author | Váňa, F Düben, P Lang, S Palmer, T Leutbecher, M Salmond, D Carver, G |
| author_facet | Váňa, F Düben, P Lang, S Palmer, T Leutbecher, M Salmond, D Carver, G |
| author_sort | Váňa, F |
| collection | OXFORD |
| description | Earth’s climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model’s physical variables as a function of scale and variable type. Answering this question is of crucial practical importance given that the development of weather and climate models is strongly constrained by available supercomputer power. As a starting point for answering this question, the impact of limiting almost all real-number variables in the forecasting mode of ECMWF Integrated Forecast System (IFS) from 64 to 32 bits is investigated. Results for annual integrations and medium-range ensemble forecasts indicate no noticeable reduction in accuracy, and an average gain in computational efficiency by approximately 40%. This study provides the motivation for more scale-selective reductions in numerical precision. |
| first_indexed | 2024-03-07T01:47:23Z |
| format | Journal article |
| id | oxford-uuid:98e3dd2c-c487-403a-91a5-5da9493e8b38 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:47:23Z |
| publishDate | 2017 |
| publisher | American Meteorological Society |
| record_format | dspace |
| spelling | oxford-uuid:98e3dd2c-c487-403a-91a5-5da9493e8b382022-03-27T00:10:09ZSingle precision in weather forecasting models: An evaluation with the IFSJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:98e3dd2c-c487-403a-91a5-5da9493e8b38EnglishSymplectic Elements at OxfordAmerican Meteorological Society2017Váňa, FDüben, PLang, SPalmer, TLeutbecher, MSalmond, DCarver, GEarth’s climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model’s physical variables as a function of scale and variable type. Answering this question is of crucial practical importance given that the development of weather and climate models is strongly constrained by available supercomputer power. As a starting point for answering this question, the impact of limiting almost all real-number variables in the forecasting mode of ECMWF Integrated Forecast System (IFS) from 64 to 32 bits is investigated. Results for annual integrations and medium-range ensemble forecasts indicate no noticeable reduction in accuracy, and an average gain in computational efficiency by approximately 40%. This study provides the motivation for more scale-selective reductions in numerical precision. |
| spellingShingle | Váňa, F Düben, P Lang, S Palmer, T Leutbecher, M Salmond, D Carver, G Single precision in weather forecasting models: An evaluation with the IFS |
| title | Single precision in weather forecasting models: An evaluation with the IFS |
| title_full | Single precision in weather forecasting models: An evaluation with the IFS |
| title_fullStr | Single precision in weather forecasting models: An evaluation with the IFS |
| title_full_unstemmed | Single precision in weather forecasting models: An evaluation with the IFS |
| title_short | Single precision in weather forecasting models: An evaluation with the IFS |
| title_sort | single precision in weather forecasting models an evaluation with the ifs |
| work_keys_str_mv | AT vanaf singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT dubenp singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT langs singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT palmert singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT leutbecherm singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT salmondd singleprecisioninweatherforecastingmodelsanevaluationwiththeifs AT carverg singleprecisioninweatherforecastingmodelsanevaluationwiththeifs |