| one publication added to basket [311566] | Reconstructing East African rainfall and Indian Ocean sea surface temperatures over the last centuries using data assimilation
Klein, F.; Goosse, H. (2018). Reconstructing East African rainfall and Indian Ocean sea surface temperatures over the last centuries using data assimilation. Clim. Dyn. 50(11-12): 3909-3929. https://dx.doi.org/10.1007/s00382-017-3853-0 In: Climate Dynamics. Springer: Berlin; Heidelberg. ISSN 0930-7575; e-ISSN 1432-0894, more |  |
| Author keywords | Data assimilation; East Africa; Indian Ocean; Model-data comparison |
| Abstract | The relationship between the East African rainfall and Indian Ocean sea-surface temperatures (SSTs) is well established. The potential interest of this covariance to improve reconstructions of both variables over the last centuries is examined here. This is achieved through an off-line method of data assimilation based on a particle filter, using hydroclimate-related records at four East African sites (Lake Naivasha, Lake Challa, Lake Malawi and Lake Masoko) and SSTs-related records at six oceanic sites spread over the Indian Ocean to constrain the Last Millennium Ensemble of simulations performed by CESM1. Skillful reconstructions of the Indian SSTs and East African rainfall can be obtained based on the assimilation of only one of these variables, when assimilating pseudo-proxy data deduced from the model CESM1. The skill of these reconstructions increases with the number of particles selected in the particle filter, although the improvement becomes modest beyond 99 particles. When considering a more realistic framework, the skill of the reconstructions is strongly deteriorated because of the model biases and the uncertainties of the real proxy-based reconstructions. However, it is still possible to obtain a skillful reconstruction of SSTs over most of the Indian Ocean only based on the assimilation of the six SST-related proxy records selected, as far as a local calibration is applied at all individual sites. This underlines once more the critical role of an adequate integration of the signal inferred from proxy records into the climate models for reconstructions based on data assimilation. |
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