University of Washington
Steiger, Nathan John.
Global climate reconstruction across time and space using data assimilation.
Degree: PhD, 2016, University of Washington
Paleoclimate proxy data span seasonal to millennial time scales, and Earth's climate system has both high- and low-frequency components. Yet it is currently unclear how best to incorporate multiple time scales of proxy data into a single reconstruction framework and to also capture both high- and low-frequency components of reconstructed variables. In the first half of this dissertation we present a data assimilation algorithm that can explicitly incorporate proxy data at arbitrary time scales. Through a series of pseudoproxy experiments, we find that atmosphere – ocean states are most skilfully reconstructed by incorporating proxies across multiple time scales compared to using proxies at short (annual) or long (∼ decadal) time scales alone. Additionally, reconstructions that incorporate long time-scale pseudoproxies improve the low-frequency components of the reconstructions relative to using only high-resolution pseudoproxies. We argue that this is because time averaging high-resolution observations improves their covariance relationship with the slowly-varying components of the coupled-climate system, which the data assimilation algorithm can exploit. These results are insensitive to the choice of climate model, despite the model variables having very different spectral characteristics. Our results also suggest that it may be possible to reconstruct features of the oceanic meridional overturning circulation based solely on atmospheric surface temperature proxies. Water isotope data from ice cores, particularly δ18
O, has long been used as a paleoclimate proxy. In the past decade or so isotope-enabled climate models have allowed for a more rich understanding of the climate processes that produce the isotopic signals in precipitation. Such modeling-based studies tend to complicate simple temperature-isotope interpretations by pointing to the many non-local influences on isotopic signals at coring locations. Recent observational studies have also linked ice cores to non-local patterns of climate variability, particularly to mid-latitude atmospheric circulation patterns and to variations in tropical climate. However, the full spatial and temporal extent to which ice cores can robustly inform past climate is unknown. In the second half of this dissertation we estimate a realistic upper-bound on what ice cores can tell us about climate at annual and decadal time scales in a paleoclimate reconstruction context. We employ a similar data assimilation-based reconstruction technique that optimally combines isotopic proxy information with the dynamical constraints of climate models. Through several pseudo and real proxy experiments we assess the spatial and temporal extent to which ice cores can reconstruct the key variables of surface temperature, geopotential height at 500 hPa, and precipitation. We find local reconstruction skill to be the most robust across the reconstructions, particularly for temperature and geopotential heights. Non-local skill is also found for these variables in certain locations. For…
Advisors/Committee Members: Hakim, Greg (advisor).
to Zotero / EndNote / Reference
APA (6th Edition):
Steiger, N. J. (2016). Global climate reconstruction across time and space using data assimilation. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/35123
Chicago Manual of Style (16th Edition):
Steiger, Nathan John. “Global climate reconstruction across time and space using data assimilation.” 2016. Doctoral Dissertation, University of Washington. Accessed December 12, 2019.
MLA Handbook (7th Edition):
Steiger, Nathan John. “Global climate reconstruction across time and space using data assimilation.” 2016. Web. 12 Dec 2019.
Steiger NJ. Global climate reconstruction across time and space using data assimilation. [Internet] [Doctoral dissertation]. University of Washington; 2016. [cited 2019 Dec 12].
Available from: http://hdl.handle.net/1773/35123.
Council of Science Editors:
Steiger NJ. Global climate reconstruction across time and space using data assimilation. [Doctoral Dissertation]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/35123