发表机构
Graduate School of Science and Engineering, Chiba University; Center for Environmental Remote Sensing, Chiba University; Institute for Advanced Academic Research, Chiba University; Research Institute of Disaster Medicine, Chiba University（千叶大学理工学研究科; 千叶大学环境遥感研究中心; 千叶大学高级学术研究研究所; 千叶大学灾害医学研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出抢占式EFSO（PEFSO）方法，利用切线性近似免重积分估计新增观测影响，并发展ADD-SEL-PRE近似更新集合预报，在Lorenz-96实验中验证了其与EFSO和ADD-SEL相当的精度。
AI 中文摘要
估计向现有数值天气预报（NWP）系统中新增观测的影响，需要从同化了额外观测的分析场重新积分集合预报，这既费时又计算成本高昂。因此，我们提出了抢占式EFSO（PEFSO；抢占式集合预报对观测的敏感性），该方法通过使用比EFSO更强的切线性近似，无需模型重新积分即可估计观测影响。然而，估计的影响在指定验证时间仅为标量值，因此，在拒绝有害观测后同化剩余额外观测以获得集合预报也是有价值的。我们将此过程称为ADD-SEL，但执行它需要重新积分。因此，我们提出了两种无需重新积分即可更新集合预报的方法，作为ADD-SEL的近似，统称为ADD-SEL-PRE：一种重新计算集合变换矩阵（即卡尔曼增益），另一种仅以较低成本修改新息。使用Lorenz-96模型的实验检验了这两种方法是否可以在不重新积分的情况下进行近似。在切线性近似保持有效的范围内，即使在实际条件下（集合大小为10、以分析场为参考状态、仅有额外观测可用），PEFSO估计的观测影响与EFSO获得的结果相当。当在拒绝有害观测后同化额外观测时，两种ADD-SEL-PRE方法都能更新集合预报，其预报误差与ADD-SEL相当，特别是在预计切线性近似成立的前两天的预报时效内。
英文摘要
Estimating the impact of observations newly added to an existing numerical weather prediction (NWP) system requires reintegrating the ensemble forecast from the analysis that assimilates the additional observations, which is laborious and computationally expensive. We therefore propose preemptive EFSO (PEFSO; preemptive ensemble forecast sensitivity to observations), which estimates observation impact without model reintegration by invoking a stronger tangent-linear approximation than that used in EFSO. The estimated impact, however, is merely a scalar quantity at a specified verification time, so it is also valuable to obtain the ensemble forecast in which the remaining additional observations are assimilated after denying the detrimental ones. We refer to this procedure as ADD-SEL, but carrying it out requires reintegration. We therefore propose two methods for updating the ensemble forecast without reintegration as approximations to ADD-SEL, collectively termed ADD-SEL-PRE: one recomputes the ensemble transform matrix (i.e., the Kalman gain), and the other modifies only the innovations at lower cost. Experiments with the Lorenz-96 model examine whether both can be approximated without reintegration. PEFSO estimates observation impact comparable to that obtained by EFSO within the range where the tangent-linear approximation remains valid, even under more practical conditions: an ensemble size of 10, the analysis as the reference state, and only the additional observations available. When additional observations are assimilated after denying detrimental ones, both ADD-SEL-PRE methods update the ensemble forecast, giving forecast errors comparable to those from ADD-SEL, particularly for lead times up to two days, where the tangent-linear approximation is expected to hold.
