impact of an observational time window on coupled data assimilation: simulation with a simple climate model
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2017
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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
twinCDA 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.
| Reference Key |
zhao2017nonlinearimpact
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|---|---|
| Authors | ;Y. Zhao;X. Deng;X. Deng;S. Zhang;Z. Liu;Z. Liu;C. Liu;C. Liu;G. Vecchi;G. Han;X. Wu |
| Journal | BMC research notes |
| Year | 2017 |
| DOI |
10.5194/npg-24-681-2017
|
| URL | |
| Keywords |
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