期刊
MONTHLY WEATHER REVIEW
卷 148, 期 4, 页码 1541-1552出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/MWR-D-19-0291.1
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资金
- NERC [NE/L002612/1]
- Royal Society
- ESiWACE project
- ESiWACE2 project
- European Union's Horizon 2020 research and innovation programme [675191, 823988]
- European Research Council under the European Union's Horizon 2020 research and innovation programme [741112]
The use of single-precision arithmetic in ECMWF's forecasting model gave a 40% reduction in wall-clock time over double-precision, with no decrease in forecast quality. However, using reduced-precision in 4D-Var data assimilation is relatively unexplored and there are potential issues with using single-precision in the tangent-linear and adjoint models. Here, we present the results of reducing numerical precision in an incremental 4D-Var data assimilation scheme, with an underlying two-layer quasigeostrophic model. The minimizer used is the conjugate gradient method. We show how reducing precision increases the asymmetry between the tangent-linear and adjoint models. For ill-conditioned problems, this leads to a loss of orthogonality among the residuals of the conjugate gradient algorithm, which slows the convergence of the minimization procedure. However, we also show that a standard technique, reorthogonalization, eliminates these issues and therefore could allow the use of single-precision arithmetic. This work is carried out within ECMWF's data assimilation framework, the Object Oriented Prediction System.
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