A pseudoproxy assessment of data assimilation for reconstructing the atmosphere–ocean dynamics of hydroclimate extremes
Because of the relatively brief observational record, the climate dynamics that drive multiyear to centennial hydroclimate variability are not adequately characterized and understood. Paleoclimate reconstructions based on data assimilation (DA) optimally fuse paleoclimate proxies with the dynam...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-10-01
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| Series: | Climate of the Past |
| Online Access: | https://www.clim-past.net/13/1435/2017/cp-13-1435-2017.pdf |
| Summary: | Because of the relatively brief observational record, the climate dynamics
that drive multiyear to centennial hydroclimate variability are not
adequately characterized and understood. Paleoclimate reconstructions based on data
assimilation (DA)
optimally fuse paleoclimate proxies with the
dynamical constraints of climate models, thus providing a coherent dynamical
picture of the past. DA is therefore an important new tool for elucidating
the mechanisms of hydroclimate variability over the last several millennia.
But DA has so far remained untested for global hydroclimate reconstructions.
Here we explore whether or not DA can be used to skillfully reconstruct
global hydroclimate variability along with the driving climate dynamics.
Through a set of idealized pseudoproxy experiments, we find that an
established DA reconstruction approach can in principle be used to
reconstruct hydroclimate at both annual and seasonal timescales. We find
that the skill of such reconstructions is generally highest near the proxy
sites. This set of reconstruction experiments is specifically designed to
estimate a realistic upper bound for the skill of this DA approach.
Importantly, this experimental framework allows us to see where and for what
variables the reconstruction approach may never achieve high skill. In
particular for tree rings, we find that hydroclimate reconstructions depend
critically on moisture-sensitive trees, while temperature reconstructions
depend critically on temperature-sensitive trees. Real-world DA-based
reconstructions will therefore likely require a spatial mixture of
temperature- and moisture-sensitive trees to reconstruct both temperature and
hydroclimate variables. Additionally, we illustrate how DA can be used to
elucidate the dynamical mechanisms of drought with two examples: tropical
drivers of multiyear droughts in the North American Southwest and in
equatorial East Africa. This work thus provides a foundation for future
DA-based hydroclimate reconstructions using real-proxy networks while also
highlighting the utility of this important tool for hydroclimate research. |
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| ISSN: | 1814-9324 1814-9332 |