This paper presents a new class of energy balance model that accounts for the long memory within the Earth's energy storage. The model is calibrated on instrumental temperature records and the historical energy budget of the Earth using an error model predicted by the model itself. Our equilibrium climate sensitivity and future temperature projection estimates are consistent with those estimated by complex climate models.

While several biological processes are similar among terrestrial and marine ecosystems, their representation in Earth System Models may differ. By comparing the terrestrial and marine modules of 17 Earth System Models, we found multiple evidences of unjustified differences in processes representation. These inconsistencies may lead to wrong predictions about the role of biosphere in the climate system and skew our perception of the relative influence of each ecosystem on climate.

We assess how three different geoengineering methods affect plant growth in different ecosystems. Changes in temperature and precipitation plays a large role in vegetation carbon uptake and storage, but our results show that CO₂ fertilization also plays a considerable role. Our findings show that there are unforeseen regional consequences under geoengineering application and these consequences should be taken into account in future climate policies before implementing policy.

We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on Lasso regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.

Small lakes are a dominant portion of inland freshwaters, but their response to climate change is rarely addressed. The thermal regime of a small and shallow lake was evaluated over a 6-decade period through hydrodynamic modelling. Significant changes were found: maximum water warming in Spring and Summer (0.7 °C/dec), increased stratification and energy for phytoplankton growth during Spring and Autumn. Such changes, must be considered for appropriate management policies of similar ecosystems.

Global water cycle involves water-mass transport on land, atmosphere, ocean, and among them. GRACE mission, launched in 2002, allowed to quantify water-mass variations. It was a revolution in the understanding of Earth dynamics. In this study, we develop and apply a novel method, based on GRACE data and atmospheric models, that allows to systematically estimate the water-mass exchange among ocean basins. Such information is valuable to understand the role of the ocean within the water cycle.

As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO₂ concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.

We demonstrate here that a single physical phenomenon, specifically, a naturally changing balance between intensities of temperature advection and diffusion in the viscous ice media, may influence the entire spectrum of the Pleistocene variability from orbital to millennial time-scales.

Several recent studies suggest a modulation of the Madden Julian Oscillation (MJO) by the Quasi-Biennial Oscillation (QBO). The physics behind this interaction, however, remains poorly understood. In this study, we investigated the QBO-MJO interaction as well as the role of the stratospheric ozone, as a forcing mechanism. A normal mode decomposition procedure combined with causality analysis reveal significant interactions between MJO-related modes and QBO-related modes.

We use an Earth system model with two new ecosystem features (plankton size traits and temperature-sensitive nutrient recycling) to revaluate the effect of climate change on organic carbon removal (the biological pump) and ocean carbon drawdown. These features lead to contrary pump responses to warming, and a stronger pump counter-intuitively leads to less carbon drawdown overall. These results show the importance of including ecological dynamics in models for understanding climate feedbacks.

Skillful forecasts of extreme weather events have a major socio-economic relevance. Here, we compare two approaches to diagnose the predictability of Eastern Mediterranean heat waves: one based on recent developments in dynamical systems theory and one leveraging numerical ensemble weather forecasts. We conclude that the former can be a useful and cost-efficient complement to conventional numerical forecasts for understanding the dynamics of Eastern Mediterranean heat waves.

This work covers multiple 3D simulations of the hydrodynamics of Lake Tanganyika, covering the inter-seasonal variations and the evolution linked to climate change. The research was done with COSMO-CLM² data, which was used to run the SLIM 3D Lake Tanganyika model. The main results explain how this stratified lake can still maintain a certain mixing between the different layers, but how this would come to an end due to climate change.

A collapse of the Atlantic Meridional Overturning Circulation can be described by six parameters and Langevin dynamics. These parameters can be found by a machine learning technique when applied to sample set of collapses seen in climate models of intermediate complexity. With this parametrisation, it might be possible to estimate how much freshwater is needed to observe a collapse in more complicated models and reality.

Variability of sea surface temperatures (SST) from 1200 to 2000 CE is quite well-known, but the history of deep ocean temperatures is not. Forcing an ocean model with these SSTs, we simulate temperatures in the ocean interior. The circulation changes alter amplitude and timing of deep ocean temperature fluctuations below 2 km depth, e.g., delay the atmospheric signal by ~ 200 yr in the deep Atlantic. Therefore, ocean circulation changes are shown to be as important as SST changes at these depths.

Many projections of future land use/cover exist. We evaluate a number of these and determine the variability they cause in ecosystems and their services. We found that projections differ a lot in regional patterns with some of them being at least questionable in a historical context. Across ecosystem service indicators resulting variability until 2040 was highest in crop production. Results emphasize that such variabilities should be acknowledged in assessments of future ecosystem provisions.

In the Paris Climate Agreement, countries agreed to keep global warming since pre-industrial times below 2 °C and ideally below 1.5 °C, requiring major reductions in greenhouse gas emissions. We investigate the regional effectiveness of lowering methane emissions from human activities, (re)afforestation, and growing bioenergy crops. Methane reduction always helps, especially for major methane-emitting regions. However, the preferred land-management strategy and its effectiveness is more variable.

The atmospheric and surface conditions that exist during the occurrence of daytime low-level clouds (LLCs) and their influence on solar radiation were investigated in West Africa. These LLCs are linked to horizontal transport of cold moist air from the ocean, surface heating and evaporation during the rainy season. In the dry season they are mostly linked to converging air at the surface and subsequent upward movement. Their occurrence lead to a strong reduction of the incoming solar radiation.

In 2016, northern France experienced an unprecedented wheat crop loss. This crop loss was likely due to an extremely warm December 2015 and abnormally high precipitation during the following spring season. Using stochastic weather generators we investigate how severe the metrological conditions leading to the crop loss could be in current climate conditions. We find that December temperatures were close to the plausible maximum but that considerably wetter springs would be possible.