Abstract
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.
A weakly coupled data assimilation system of a coupled physical–biological model for the northeastern South China Sea
