Assessing a New Coupled Data Assimilation System Based on the Met Office Coupled Atmosphere-Land-Ocean-Sea Ice Model
Assessing a New Coupled Data Assimilation System Based on the Met Office Coupled Atmosphere-Land-Ocean-Sea Ice Model
复制标题
DOI：
10.1175/mwr-d-15-0174.1
复制
发表时间：
2015-11-01
影响因子：
3.2
通讯作者：
Thurlow, M.
中科院分区：
文献类型：
--
作者：
Lea, D. J.;Mirouze, I.;Thurlow, M.
本文介绍了一种新的耦合数据同化（DA）系统，其目的是改善从短距离到季节的各种时间范围的耦合预报的初始化。这里的实现基于弱耦合数据同化方法，即使用耦合模型为单独的海洋-海冰和大气-陆地分析提供背景信息。然后，从这些单独的分析中生成的增量被添加回耦合模型中。这与现有的气象局初始化耦合预报系统不同，后者使用的是分别由FOAM海洋数据同化系统和NWP大气同化系统独立生成的海洋和大气分析。已经进行了一系列试验，以研究弱耦合数据同化对分析的影响，以及对5-10天的耦合预测技能的影响。通过将分析和预测结果与观测结果进行比较，并检查模式场的差异，对分析和预测结果进行了评估。对于这个新系统来说，令人鼓舞的是，海洋和大气评估都表明，使用耦合数据分析产生的分析和耦合预报与使用单独的海洋-大气数据同化产生的分析和耦合预报非常相似。这项工作的好处是突出了需要关注的一些方面，以改进耦合数据分析结果。特别是，改进海温日变化和河流径流的模拟和数据同化应加以研究。
A new coupled data assimilation (DA) system developed with the aim of improving the initialization of coupled forecasts for various time ranges from short range out to seasonal is introduced. The implementation here is based on a weakly coupled data assimilation approach whereby the coupled model is used to provide background information for separate ocean-sea ice and atmosphere-land analyses. The increments generated from these separate analyses are then added back into the coupled model. This is different from the existing Met Office system for initializing coupled forecasts, which uses ocean and atmosphere analyses that have been generated independently using the FOAM ocean data assimilation system and NWP atmosphere assimilation systems, respectively. A set of trials has been run to investigate the impact of the weakly coupled data assimilation on the analysis, and on the coupled forecast skill out to 5-10 days. The analyses and forecasts have been assessed by comparing them to observations and by examining differences in the model fields. Encouragingly for this new system, both ocean and atmospheric assessments show the analyses and coupled forecasts produced using coupled DA to be very similar to those produced using separate ocean-atmosphere data assimilation. This work has the benefit of highlighting some aspects on which to focus to improve the coupled DA results. In particular, improving the modeling and data assimilation of the diurnal SST variation and the river runoff should be examined.