Search for: All records

Weighted ensemble (WE) is an enhanced sampling method based on periodically replicating and pruning trajectories generated in parallel. WE has grown increasingly popular for computational biochemistry problems due, in part, to improved hardware and accessible software implementations. Algorithmic and analytical improvements have played an important role, and progress has accelerated in recent years. Here, we discuss and elaborate on the WE method from a mathematical perspective, highlighting recent results that enhance the computational efficiency. The mathematical theory reveals a new strategy for optimizing trajectory management that approaches the best possible variance while generalizing to systems of arbitrary dimension.

The La Niña and El Niño phases of the El Niño-Southern Oscillation (ENSO) have major impacts on regional rainfall patterns around the globe, with substantial environmental, societal and economic implications. Long-term perspectives on ENSO behaviour, under changing background conditions, are essential to anticipating how ENSO phases may respond under future climate scenarios. Here, we derive a 7700-year, quantitative precipitation record using carbon isotope ratios from a single species of leaf preserved in lake sediments from subtropical eastern Australia. We find a generally wet (more La Niña-like) mid-Holocene that shifted towards drier and more variable climates after 3200 cal. yr BP, primarily driven by increasing frequency and strength of the El Niño phase. Climate model simulations implicate a progressive orbitally-driven weakening of the Pacific Walker Circulation as contributing to this change. At centennial scales, high rainfall characterised the Little Ice Age (~1450–1850 CE) in subtropical eastern Australia, contrasting with oceanic proxies that suggest El Niño-like conditions prevail during this period. Our data provide a new western Pacific perspective on Holocene ENSO variability and highlight the need to address ENSO reconstruction with a geographically diverse network of sites to characterise how both ENSO, and its impacts, vary in a changing climate.