We analyze drivers of hot temperature extremes, focusing on both atmospheric and land-surface factors. Using observation-based data and an analogue-based approach, we find that geopotential height at 500 hPa is the most significant driver worldwide at daily and weekly timescales. Surface net radiation and evaporative fraction play relevant roles at the daily scale and wind at the weekly timescale. The driver influence varies by region, related to differences in climate regimes and land cover.

Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the Land Use Model Intercomparison Project (LUMIP) and the Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that LUC-induced carbon emissions contribute to a BGC warming of 0.21 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasize the need for improved representations of LUC processes.

A new offline model (LSM_Nlateral_Off) was developed to simulate the lateral transfer of nitrogen from land to oceans through the river network, incorporating the decomposition of DON (dissolved organic N) and PON (particulate organic N) and denitrification of DIN (dissolved inorganic N) during fluvial transport. Evaluations using observational data indicate that the model reproduces observed rates and seasonal variations in water discharge and N flow well.

Land-use change projections are vital for impact studies. This study compares updated land-use model projections, including CO₂ fertilization among other upgrades, from the MAgPIE and IMAGE models under three scenarios, highlighting differences, uncertainty hotspots, and harmonization effects. Key findings include reduced bioenergy crop demand projections and differences in grassland area allocation and sizes, with socioeconomic–climate scenarios' largest effect on variance starting in 2030.

Our study uses a global climate model to investigate how groundwater and floodplains influence today's climate. We found that these continental water sources, often overlooked in climate models, can influence precipitation, temperature, and land surface hydrology. This research contributes to a better understanding of the dynamics of the Earth system and highlights the importance of considering interactions between hydrology and the atmosphere.

In recent decades, we have witnessed abnormally hot summers and frequent weather extremes globally. These are clear signs of global warming and climate change. A constant increase in atmospheric carbon dioxide (CO₂) is a major driver of these changes. We propose an algorithm for near-real-time detection of terrestrial areas with CO₂ sources and sinks. This algorithm could aid in developing new methods of natural CO₂ reduction and exploring ecosystem responses to disturbances.

Large-scale modes of variability are present in the climate system. These modes are known to have influences on each other but are usually viewed as linear influences. The nonlinear connections among a set of key climate indices are explored here using tools from information theory, which allow us to characterize the causality between indices. It was found that quadratic nonlinear dependencies between climate indices are present at low frequencies, reflecting the complex nature of their dynamics.

An obstacle in studying climate extremes is the lack of robust statistics. We use a rare event algorithm to gather robust statistics on extreme Arctic sea ice lows with probabilities below 0.1 % and to study drivers of events with amplitudes larger than observed in 2012. The work highlights that the most extreme sea ice reductions result from the combined effects of preconditioning and weather variability, emphasizing the need for thoughtful ensemble design when turning to real applications.

Stratospheric aerosol injection (SAI) could be used alongside mitigation to reduce global warming. Previous studies suggest that more atmospheric CO₂ is taken up when SAI is deployed. Here, we look at the entire SAI deployment from start to after termination. We show how the initial CO₂ uptake benefit, and hence lower mitigation burden, is reduced in later stages of SAI, where the reduction in natural CO₂ uptake turns into an additional mitigation burden. 

Land cover and land management changes (LCLMCs) can alter climate even in intact areas, causing carbon changes in remote areas. This study is the first to assess these effects, finding they substantially alter global carbon dynamics, changing terrestrial stocks by up to dozens of gigatonnes. These results are vital for scientific and policy assessments, given the expected role of LCLMCs in achieving the Paris Agreement's goal to limit global warming below 1.5 °C.

Projecting future precipitation is essential for preparing for climate change, but current climate models still have large uncertainties, especially over land. This study presents a new method to improve precipitation projections by identifying which models best capture key climate patterns. By giving more weight to models that better represent these patterns, our approach leads to more reliable future precipitation projections over land.

We investigate the probabilities of triggering climate tipping points under various emission scenarios and how they are altered by additional carbon emissions from the tipping of the Amazon and permafrost. We find that there is a high risk for triggering climate tipping points under a scenario comparable to current policies. However, the additional warming and hence the additional risk of triggering other climate tipping points from the tipping of the Amazon and permafrost remain small.

We present a high-resolution paleogeographic reconstruction of the Baltic Sea for the Holocene period by combining eustatic sea-level change, glacio-isostatic movement, and sediment dynamics. In the northeastern part, morphological change is dominated by regression caused by post-glacial rebound that outpaces the eustatic sea level rise, whereas a transgression, together with active sediment erosion/deposition, constantly shapes the coastal morphology in the southeastern part.

Social tipping dynamics have received recent attention as a potential mechanism for effective climate actions – yet how such tipping dynamics could unfold remains largely unquantified. We explore how social tipping processes can develop by enabling necessary conditions (exemplified by climate change concern) and increased perceptions of localized impacts (sea level rise). The likelihood of social tipping varies regionally, mostly along areas with the highest exposure to persistent risks.