Atmospheric processes

El Niño Southern Oscillation (ENSO) events yield precipitation deficits and ensuing droughts, often damaging regional forests, in many parts of the world. The relative roles of ENSO, other natural climate changes, and anthropogenic factors on the forest clearing of Easter Island over the last millennium are still debated. Here, we analyze Easter Island precipitation changes using in situ, satellite-derived and reanalysis products spanning the last 4–7 decades, and 46 monthly 156-year-long (1850–2014) simulations derived from 25 CMIP5 and 21 CMIP6 (Coupled Model Intercomparison Project phases 5 and 6) General Circulation Models. Our analysis shows that La Niña events, the cold phases of ENSO, cause precipitation deficits of −0.2 to −0.3 standard deviation (relative to long-term mean) in all analyzed data types. ENSO-like events are further examined over the last millennium (850–1981). A new multiproxy reconstruction of the NINO3.4 index based on proxy records from the Past Global Changes 2k database and Random Forest method is produced. Our reconstruction reveals unusual high recurrences of La Niña-like situations during the fifteenth to seventeenth centuries, which likely induced significant precipitation deficits on the island. These situations are compared to published vegetation reconstructions based on pollen analyses derived from sedimentary cores collected in three island sites. We conclude the environmental consequences of cumulative precipitation deficits over long-lasting La Niña-like situations reconstructed here over the fifteenth to seventeenth centuries were likely favoring drought and forest flammability. La Niña events should be better accounted for among the causes of forest clearing on Easter Island.

Atlantic multidecadal variability is a coherent mode of natural climate variability occurring in the North Atlantic Ocean, with strong impacts on human societies and ecosystems worldwide. However, its periodicity and drivers are widely debated due to the short temporal extent of instrumental observations and competing effects of both internal and external climate factors acting on North Atlantic surface temperature variability. Here, we use a paleoclimate database and an advanced statistical framework to generate, evaluate, and compare 312 reconstructions of the Atlantic multidecadal variability over the past millennium, based on different indices and regression methods. From this process, the best reconstruction is obtained with the random forest method, and its robustness is checked using climate model outputs and independent oceanic paleoclimate data. This reconstruction shows that memory in variations of Atlantic multidecadal variability have strongly increased recently—a potential early warning signal for the approach of a North Atlantic tipping point.