| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000434623 |
| 005 | | 20200226161504 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781687956057 |
| 035 | |
▼a (MiAaPQ)AAI22621252 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 551.5 |
| 100 | 1 |
▼a Perkins, Walter Andre. |
| 245 | 10 |
▼a Reconstructing Coupled Atmosphere-ocean Variability over the Last Millennium. |
| 260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 148 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B. |
| 500 | |
▼a Includes supplementary digital materials. |
| 500 | |
▼a Advisor: Hakim, Gregory. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 506 | |
▼a This item must not be added to any third party search indexes. |
| 520 | |
▼a Coupled interactions between oceans and the atmosphere are fundamental to low-frequency variability of the Earth System. While the instrumental record provides an account of this coupled variability over time, the length of record often hinders investigation of the mechanisms of variability on decadal and longer timescales. Paleoclimate data assimilation offers an objective method to investigate dynamic field variability of the past constrained by climate proxies and climate model information. This dissertation presents results from coupled atmosphere-ocean field reconstructions over the last millennium using online data assimilation (DA). To achieve online DA-based reconstructions, we implement and examine a linear inverse model (LIM) as a climate model forecast approximation to constrain temporal dynamics of coupled fields. We find LIMs skillfully capture underlying dynamics from coupled global climate models (GCMs) for ensemble climate forecasts. Additionally, the efficiency allows us to perform experiments using large ensembles over long periods, which is not possible with GCMs. When employing LIMs as a forecast model for online paleoclimate DA, we find reconstructions display significantly improved consistency for upper-ocean heat content variability and that they maintain dynamical consistency for specific field relationships when less proxy information is available. These reconstructions also validate well against instrumental ocean data for both spatial and aggregate measures. We find that the reconstructed large-scale temperature averages tend to be cooler than previous reconstructions, especially during the early period (1000-1200 C.E.). However, despite cooler global-scale temperatures, we find early periods of decadal-scale warmth over high-latitude Europe in agreement with previous documentary and proxy-based evidence. Overall, the annually-resolved multivariate reconstructions produced in this dissertation present a more comprehensive account of low-frequency atmosphere-ocean variability over the last millennium. Furthermore, the generality of the presented methodology allows for continued refinement of the reconstruction product over time as the availability of proxy information grows and GCMs improve. |
| 590 | |
▼a School code: 0250. |
| 650 | 4 |
▼a Paleoclimate science. |
| 650 | 4 |
▼a Atmospheric sciences. |
| 690 | |
▼a 0653 |
| 690 | |
▼a 0725 |
| 710 | 20 |
▼a University of Washington.
▼b Atmospheric Sciences. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-04B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0250 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493792
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |