Abstract
Abstract. Climate signals are the results of interactions of multiple timescale 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 that are sequentially assimilated with their original error scales. Given different timescales 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 and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for 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.
Highlights
The interactions between the earth climate system’s major components, such as the atmosphere, ocean, land, and sea ice, have been reasonably simulated by coupled climate models, which can give the evaluation of climate changes (Randall et al, 2007)
With a simple conceptual climate model and the EAKF method, the impact of observational time window (OTW) on the quality of coupled data assimilation (CDA) has been investigated in this study
Determined from the characteristic variability timescale in each coupled medium, an optimal OTW provides maximal observational information to best fit the characteristic variability of the medium during the data blending process
Summary
The interactions between the earth climate system’s major components, such as the atmosphere, ocean, land, and sea ice, have been reasonably simulated by coupled climate models, which can give the evaluation of climate changes (Randall et al, 2007). With a simple conceptual coupled climate model and a sequential implementation of the ensemble Kalman filter, this study first analyses the characteristic variability timescale of each coupled medium and identifies the corresponding optimal OTW. Using the EAKF with the simple coupled model, we first establish a twin experiment framework Within such a framework, the degree to which the state estimation based on a certain OTW recovers the truth is an assessment of the influence of the OTW on the quality of CDA.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have