资源环境科技发展态势分析平台

In numerical weather prediction it is important to objectively measure the value of the observations assimilated. However, methods such as the forecast sensitivity to observation impact and observing system experiments are difficult to apply to convective scale data assimilation (DA) systems such as the Met Office's UKV. We develop a new method to estimate the influence of the observations on the analysis, acknowledging that the influence depends not only on the uncertainty in the observations and prior, but how well these are prescribed in the assimilation. Monitoring both the actual and theoretical observation influence can flag observations that are being assimilated incorrectly and quantify the harm caused to the analysis. By applying these new estimates of the observation influence to the assimilation of Doppler Radial Winds in the UKV system, we demonstrate their ability, along with expert knowledge, to inform the optimisation of both the observation network and DA system.