Recent  

Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.

Ecosystem resistance reflects their susceptibility during adverse conditions and can be changed by land management. We estimate ecosystem resistance to drought and temperature globally. We find a higher resistance to drought in forests compared to croplands and an evident loss of resistance to drought when primary forests are converted to secondary forests or they are harvested. Old-growth trees tend to be more resistant in some forests and crops benefit from irrigation during drought periods.

We present model-based topographic sensitivity experiments that provide valuable constraints for interpreting past proxies and records of climate and tectonic processes. The study uses a climate model to quantify the response of regional climate and oxygen isotopic composition of precipitation to diachronous surface uplift scenarios across the European Alps. The results suggest that isotopic signal changes can be measured in geologic archives using stable isotope paleoaltimetry.

The Arctic is warming several times faster than the rest of the planet. Here, we use climate model projections to quantify for the first time how this faster warming in the Arctic impacts the timing of crossing the 1.5 °C and 2 °C thresholds defined in the Paris Agreement. We show that under plausible emissions scenarios that fail to meet the Paris 1.5 °C target, a hypothetical world without faster warming in the Arctic would breach that 1.5 °C target around 5 years later.

The worsening effects of climate change and other environmental problems impact the ability of societies to tackle the causes of these problems. We term this "derailment risk": the risk that the path to re-stabilising the natural world is derailed by the worsening instability of societies. But, conversely, instability can also provide opportunities for positive change. Acting on derailment risk is needed to ensure positive change can win out and so is critical for avoiding catastrophic outcomes.

Our study focuses on Chile, which is affected by the prevailing ocean currents, upwellings and El Niño; these generate the weather in Chile. That is why we conducted a study on the dynamics of this system using spectral and nonlinear analysis techniques. We obtained periodicities related to internal and external forcing; we find that the dynamics is not chaotic but nonlinear. Finally, the northern part presents a strong correlation between ONI and LLE due to regional characteristics.

We produced one of the largest single model initial-condition ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). MIROC6-LE includes historical simulations, eight single forcing historical experiments, five future scenario experiments and three single forcing future experiments with 10- or 50-ensemble members. We describe the experimental design and show initial analyses. This dataset would be useful to a wide range of research communities.

This study investigates the temporal stability and reliability of winter-month trends of air–sea heat fluxes from ERA5 forecasts over the North Atlantic basin for the period 1950–2019. Driving forces of trends and the impact of modes of climate variability and analysis increments on air–sea heat fluxes are investigated. Finally, a new and independent estimate of the Atlantic Meridional Overturning Circulation weakening is provided and associated with a decrease in air–sea heat fluxes.

Adapting to climate change requires an understanding of how extreme weather events are changing. We propose a new approach to examine how the consequences of a particular weather pattern have been made worse by climate change, using an example of a severe windstorm that occurred in 1903. When this storm is translated into a warmer world, it produces higher wind speeds and increased rainfall, suggesting that this storm would be more damaging if it occurred today rather than 120 years ago.

The Benguela Upwelling System hosts highly productive marine ecosystems, supporting the livelihood of the local inhabitants. Regional distribution of nutrients in this system is affected by upwelling, primarily wind-driven and related to the South Atlantic Anticyclone, which is believed to intensify in the future. We found that this system's southern and northern parts respond to the anticyclone changes differently. Due to climate variability, the uncertainty in the upwelling trend is high.

Savannas account for over half of global landscape fire emissions. Although environmental and fuel conditions affect the ratio of species the fire emits, these dynamics have not been implemented in global models. We measured CO₂, CO, CH₄, and N₂O emission factors (EFs), fuel parameters, and fire severity proxies during 129 individual fires. We identified EF patterns and trained models to estimate EFs of these species based on satellite observations, reducing the estimation error by 60–85 %.