论文标题
在MITGCM的伴随模型中使用还原精确的算术
Using reduced-precision arithmetic in the adjoint model of MITgcm
论文作者
论文摘要
近年来，人们令人信服地表明，天气预报模型可以在单精度算术中运行。几种模型或其组件的精度比这更低的精度进行了测试。这项先前的工作主要集中在主要的非线性“正向”模型上。非线性模型（在天气预报或其他方式中）可以具有相应的切线线性和伴随模型，这些模型用于4D变化数据同化。线性化模型对数值精度的降低更为敏感，因为无界误差生长可能发生，而没有非线性饱和的可能性。在本文中，我们提出了一个地球物理实验，该实验利用伴随模型来计算敏感性并进行优化。使用软件仿真，我们研究了降低伴随模型的数值精度的效果。我们发现，合理的结果是只有10个显着的位置，等于IEEE半精度标准中的显着精度。
In recent years, it has been convincingly shown that weather forecasting models can be run in single-precision arithmetic. Several models or components thereof have been tested with even lower precision than this. This previous work has largely focused on the main nonlinear `forward' model. A nonlinear model (in weather forecasting or otherwise) can have corresponding tangent linear and adjoint models, which are used in 4D variational data assimilation. The linearised models are plausibly far more sensitive to reductions in numerical precision since unbounded error growth can occur with no possibility of nonlinear saturation. In this paper, we present a geophysical experiment that makes use of an adjoint model to calculate sensitivities and perform optimisation. Using software emulation, we investigate the effect of degrading the numerical precision of the adjoint model. We find that reasonable results are obtained with as few as 10 significand bits, equal to the significand precision in the IEEE half-precision standard.
