Future changes in rainfall have serious impacts on human adaptation to climate change, but quantification of these changes is subject to large uncertainties in climate model projections. To narrow these uncertainties, significant efforts have been made to understand the intermodel differences in future rainfall changes. Here, we show a strong inverse relationship between present-day precipitation and its future change to possibly calibrate future precipitation change by removing the present-day bias in climate models.

Aridity—the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET)—is projected to decrease (that is, areas will become drier) as a consequence of anthropogenic climate change, exacerbating land degradation and desertification. However, the timing of significant aridification relative to natural variability—defined here as the time of emergence for aridification (ToEA)—is unknown, despite its importance in designing and implementing mitigation policies.

Trees impacted by the forces of natural processes such as flash floods, snow avalanches, landslides, rockfalls or earthquakes, record these events and exhibit growth disturbances in their growth-ring series. As a consequence, these disturbances provide an excellent signal for the spatio-temporal reconstruction of past natural hazard activity and a means to date and document past disasters.

Original Source

Models show that several aspects of Earth’s top-of-atmosphere energy budget and the magnitude of projected global warming are correlated, enabling us to infer that future warming has been underestimated.