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Sensitivity of High-Resolution Forecasts Using the Adjoint Technique at the 10-km Scale

机译:使用伴随技术在10公里范围内进行高分辨率预报的敏感性

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This paper provides an experimental framework designed to assess the performance and the evolution of the diabatic Aire Limitee Adaptation Dynamique Developpement International (ALADIN) adjoint model at 10-km grid size. Numerical experiments are carried out with the goal of evaluating the adjoint model solutions and the benefit of employing a complex linearized physical parameterization package in the gradient computation. Sensitivity studies with respect to initial conditions at high resolution on real meteorological events are performed. Numerical results obtained in the gradient computations show that, at high resolution, a strong nonlinear flow over complex orography might be a potential source of numerical instability in the absence of a robust dissipative physics employed in the adjoint model. Also, the scheme of the linearized large-scale precipitation is a source of noise in precipitating areas. The results on one particular case suggest that on the one hand the adjoint model is able to capture the dynamically sensitive area, but on the other hand the subsequent sensitivity forecast is more sensitive to the sign and the amplitude of the initial state perturbation rather than the structure of the gradient field.
机译:本文提供了一个实验框架,旨在评估10 km网格大小的非绝热的Aire Limitee适应性动态发展国际(ALADIN)伴随模型的性能和演变。进行数值实验的目的是评估伴随模型的解,并在梯度计算中采用复杂的线性物理参数化程序包。针对高分辨率对真实气象事件的初始条件进行了敏感性研究。在梯度计算中获得的数值结果表明,在高分辨率的情况下,如果在伴随模型中没有强大的耗散物理,则复杂地形上的强非线性流动可能是数值不稳定的潜在来源。同样,线性化的大规模降水方案也是在降水区产生噪声的源头。在一个特定情况下的结果表明,伴随模型一方面能够捕获动态敏感区域,但是另一方面,随后的敏感度预测对初始状态扰动的符号和幅度更敏感,而不是对初始状态摄动的敏感度。梯度场的结构。

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