Publication Date:
2016-01-18
Description:
Data assimilation (DA) is an emerging topic in palaeoclimatology and one of the key challenges in this field. Assimilating proxy-based continental mean temperature reconstructions into the MPI-ESM model showed a lack of information propagation to small spatial scales (Matsikaris et al., 2015b). Here, we investigate whether this lack of regional skill is due to the methodology or to errors in the assimilated reconstructions. Error separation is fundamental, as it can lead to improvements in DA methods. We address the question by performing a new set of simulations, using two different sets of target data; the proxy-based PAGES 2K reconstructions (DA-P scheme), and the HadCRUT3v instrumental observations (DA-I scheme). Again, we employ ensemble-member selection DA using the MPI-ESM model, and assimilate NH continental mean tempera- tures; the simulated period is 1850-1949 AD. Both DA schemes follow the large-scale target and observed climate variations well, but the assimilation of instrumental data improves the performance. This improvement cannot be seen for Asia, where the limited instrumental coverage leads to errors in the target data and low skill for the DA-I scheme. No skill on small spatial scales is found for either of the two DA schemes, demonstrating that errors in the assimilated data are not the main reason for the unrealistic representation of the regional temperature variability. It can thus be concluded that assimilating continental mean temperatures is not ideal for providing skill on small spatial scales.
Print ISSN:
1814-9340
Electronic ISSN:
1814-9359
Topics:
Geosciences
Permalink