Impact of Optimal Observational Time Window on Coupled Data Assimilation: Simulation with a Simple Climate Model
Other literature type
(issn: 1607-7946, eissn: 1607-7946)
arxiv: Physics::Geophysics | Physics::Atmospheric and Oceanic Physics
Climate signals are the results of interactions of multiple time scale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples. Given different time scales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system, we address this issue here. Results show that required by retrieval of characteristic variability of each coupled medium, an optimal OTW determined from the de-correlation time scale provides maximal observational information that best fits characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulted CDA improves the analysis of climate signals greatly. The simple model results
provide a guideline when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.