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Influence of proxy data uncertainty on data assimilation for the past climate

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 <cite class="cite"/...

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Tác giả chính:	A., Matsikaris, M., Widmann, J., Jungclaus
Ngôn ngữ:	English
Năm xuất bản:	Copernicus Publications 2018
Chủ đề:	Technology Environmental technology. Sanitary engineering Environmental pollution
Truy cập Trực tuyến:	http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3962
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spelling	oai:localhost:DHQB_123456789-39622018-10-22T08:43:48Z Influence of proxy data uncertainty on data assimilation for the past climate A., Matsikaris M., Widmann J., Jungclaus Technology Environmental technology. Sanitary engineering Environmental pollution 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 <cite class="cite"/>. 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 Northern Hemisphere (NH) continental mean temperatures; 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 in Europe and the NH. It can thus be concluded that assimilating continental mean temperatures is not ideal for providing skill on small spatial scales. 2018-09-04T08:33:46Z 2018-09-04T08:33:46Z 2018 http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3962 en Copernicus Publications
institution	Trung tâm Học liệu Đại học Quảng Bình (Dspace)
collection	Trung tâm Học liệu Đại học Quảng Bình (Dspace)
language	English
topic	Technology Environmental technology. Sanitary engineering Environmental pollution
spellingShingle	Technology Environmental technology. Sanitary engineering Environmental pollution A., Matsikaris M., Widmann J., Jungclaus Influence of proxy data uncertainty on data assimilation for the past climate
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 <cite class="cite"/>. 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 Northern Hemisphere (NH) continental mean temperatures; 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 in Europe and the NH. It can thus be concluded that assimilating continental mean temperatures is not ideal for providing skill on small spatial scales.
author	A., Matsikaris M., Widmann J., Jungclaus
author_facet	A., Matsikaris M., Widmann J., Jungclaus
author_sort	A., Matsikaris
title	Influence of proxy data uncertainty on data assimilation for the past climate
title_short	Influence of proxy data uncertainty on data assimilation for the past climate
title_full	Influence of proxy data uncertainty on data assimilation for the past climate
title_fullStr	Influence of proxy data uncertainty on data assimilation for the past climate
title_full_unstemmed	Influence of proxy data uncertainty on data assimilation for the past climate
title_sort	influence of proxy data uncertainty on data assimilation for the past climate
publisher	Copernicus Publications
publishDate	2018
url	http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3962
_version_	1717292461326336000
score	9,463379

Influence of proxy data uncertainty on data assimilation for the past climate

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