What we can learn from studying the last millennium (or so)

With all of the emphasis that is often placed on hemispheric or global mean temperature trends during the past millennium, and the context they provide for interpreting modern warming trends, one thing is often lost in the discussion: space matters as much as time. Indeed, it is likely that the regional patterns of past climate changes, rather than simple hemispheric or global mean temperature trends, will best inform our understanding of the dynamical mechanisms involved. Since much of the uncertainty in future projections relates to regional climate change impacts, it makes particular sense to focus on those changes in the past that involve regional changes and the underlying mechanisms behind them.

For instance, melting of the cryosphere (and consequent rises in sea level), subtle shifts in drought and rainfall patterns, and extreme events, are all regional effects that could be important threats to ecosystems and our environment. Such changes are often associated with phenomena like ENSO or the North Atlantic Oscillation. Yet there remain large uncertainties about how such mechanisms will respond to anthropogenic climate change.

There are a number of potential ways forward to improve our understanding. A first step is to look directly at the time-series of specific systems (like the ENSO index or the ocean temperatures in the North Atlantic) and try to extend them as far back as possible using proxy data. This gives more information on what the natural variations in these phenomena look like, and thus a better idea of how big a forced response would need to be before it could be reliably detected. Secondly, we can look to see if there is a relationship between various natural drivers of climate change (volcanic eruptions, solar variability or orbital forcing say) and any characteristics of these phenomena – amplitude, frequency or duration. Do volcanic eruptions appear to affect El NiƱo for instance?

For phenomena that need annual or decadal resolution data to be resolved, the last millennium or so is an obvious (and only) time period to be looking at for it is only for that period that there is sufficient paleo-data coverage of high enough temporal resolution. Other periods – such as the mid-Holocene 6000 years ago – are also useful, but the results are more long-term in nature (there is also a discussion of the value of different periods for reducing future projection uncertainty in this recent paper).

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