DECADAL TO CENTENNIAL SCALE CLIMATE DYNAMICS IN MODELS OF VARYING COMPLEXITY
Though concerted climate action by the world's governments intends to limit long-term (e.g. 100 years) global average temperature rise, attention has recently focused on reducing climate impacts in our lifetime by reducing emissions of short-lived climate forcers (SLCFs). SLCFs are pollutants t...
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| Other Authors: | , , , , |
| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1903/26217 https://doi.org/10.13016/rpqj-eru7 |
| Summary: | Though concerted climate action by the world's governments intends to limit long-term (e.g. 100 years) global average temperature rise, attention has recently focused on reducing climate impacts in our lifetime by reducing emissions of short-lived climate forcers (SLCFs). SLCFs are pollutants that remain in the atmosphere for a short time (e.g. methane or black carbon) and have the potential to impact the climate in the near-term by increasing or decreasing temperature, depending on the species emitted. There is a more limited set of literature, however, that robustly characterizes short-term climate dynamics in the 20-30 year time horizon within models or observations that can be used to inform scientific and policy work. In this dissertation, we seek to clarify climate dynamics on shorter time scales using models of varying complexity---from complex models, which take several months to simulate 100 years of climate on a supercomputer, to simple climate models (SCMs) that can simulate the same period on a personal computer in less than a minute, in addition to using several observational datasets. We first characterize the basic climate processes within several SCMs, finding that some comprehensive SCMs fail to capture response timescales of more complex models, for example under BC forcing perturbations. These results suggest where improvements should be made to SCMs, which affect numerous scientific endeavors and illustrates the necessity of integrating fundamental tests into SCM development. We then robustly determine how realistic complex model variability is compared to observations across all time scales using power spectra of temperature-time series. We investigate model variability at the regional level, using the continental-scale regions defined by PAGES2k. We find that compared to observations the suite of CMIP5 models investigated have lower variability in certain regions (e.g. Antarctica) and higher variability in others (e.g., Australasia), with some consistency across timescales. Our approach ... |
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