Greenhouse- and orbital-forced climate extremes during the early Eocene.

The Palaeocene-Eocene Thermal Maximum (PETM) was a significant global warming event in Earth's deep past (56 Mya). The warming across the PETM boundary was driven by a rapid rise in greenhouse gases. The event also coincided with a time of maximum insolation in Northern Hemisphere summer. There is increased evidence that the mean warming was accompanied by enhanced seasonality and/or extremes in precipitation (and flooding) and drought. A high horizontal resolution (50 km) global climate model is used to explore changes in the seasonal cycle of surface temperature, precipitation, evaporation minus precipitation and river run-off for regions where proxy data are available. Comparison for the regions indicates the model accurately simulates the observed changes in these climatic characteristics with North American interior warming and drying, and warming and increased river run-off at other regions. The addition of maximum insolation in Northern Hemisphere summer leads to a drier North America, but wetter conditions at most other locations. Long-range transport of atmospheric moisture plays a critical role in explaining regional changes in the water cycle. Such high-frequency variations in precipitation might also help explain discrepancies or misinterpretation of some climate proxies from the same locations, especially where sampling is coarse, i.e. at or greater than the frequency of precession.This article is part of a discussion meeting issue 'Hyperthermals: rapid and extreme global warming in our geological past'.

Sensitivity of the Palaeocene-Eocene Thermal Maximum climate to cloud properties.

The Palaeocene-Eocene Thermal Maximum (PETM) was a significant global warming event in the Earth's history (approx. 55 Ma). The cause for this warming event has been linked to increases in greenhouse gases, specifically carbon dioxide and methane. This rapid warming took place in the presence of the existing Early Eocene warm climate. Given that projected business-as-usual levels of atmospheric carbon dioxide reach concentrations of 800-1100 ppmv by 2100, it is of interest to study past climates where atmospheric carbon dioxide was higher than present. This is especially the case given the difficulty of climate models in simulating past warm climates. This study explores the sensitivity of the simulated pre-PETM and PETM periods to change in cloud condensation nuclei (CCN) and microphysical properties of liquid water clouds. Assuming lower levels of CCN for both of these periods leads to significant warming, especially at high latitudes. The study indicates that past differences in cloud properties may be an important factor in accurately simulating past warm climates. Importantly, additional shortwave warming from such a mechanism would imply lower required atmospheric CO2 concentrations for simulated surface temperatures to be in reasonable agreement with proxy data for the Eocene.

Paleoclimatic evidence for future ice-sheet instability and rapid sea-level rise.

Sea-level rise from melting of polar ice sheets is one of the largest potential threats of future climate change. Polar warming by the year 2100 may reach levels similar to those of 130,000 to 127,000 years ago that were associated with sea levels several meters above modern levels; both the Greenland Ice Sheet and portions of the Antarctic Ice Sheet may be vulnerable. The record of past ice-sheet melting indicates that the rate of future melting and related sea-level rise could be faster than widely thought.

Evidence for large decadal variability in the tropical mean radiative energy budget.

It is widely assumed that variations in Earth's radiative energy budget at large time and space scales are small. We present new evidence from a compilation of over two decades of accurate satellite data that the top-of-atmosphere (TOA) tropical radiative energy budget is much more dynamic and variable than previously thought. Results indicate that the radiation budget changes are caused by changes in tropical mean cloudiness. The results of several current climate model simulations fail to predict this large observed variation in tropical energy budget. The missing variability in the models highlights the critical need to improve cloud modeling in the tropics so that prediction of tropical climate on interannual and decadal time scales can be improved.