Recent  

Observing clouds and their properties is not straightforward, however, these are important for reducing climate models uncertainties. Ground-based observations are spatially limited while satellite data are accompanied by various artefacts. In this paper, we use corrected observational and state-of-the-art reanalysis cloud data to show that the recent evolution of total cloud cover on a global scale is linked to the Eastern Pacific and the Central Pacific El Niño–Southern Oscillation.

We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyzed the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performances between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines their roles in assessing the performance of DGVM simulations.

The deployment of bioenergy crops for capturing carbon from the atmosphere facilitates global warming mitigation via generating negative CO₂ emissions. Here, we explored the consequences of large-scale energy crops deployment on the land carbon cycle. The land-use change for energy crops leads to carbon emissions and loss of future potential increase in carbon uptake by natural ecosystems. This impact should be taken into account by the modelling teams and accounted for in mitigation policies.

The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. Including the biogeochemical coupling, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.

Climate change has multiple effects on Baltic Sea species, communities, and ecosystem functioning. Effects on species distribution, eutrophication and trophic interactions are expected. We review these effects, identify knowledge gaps and draw conclusions based on recent field, experimental and modelling research. An extensive summary table is compiled to highlight the multifaceted impacts of climate change driven processes in the Baltic Sea.

Gaining a complete understanding of extreme weather, from its physical drivers to its impacts on society, is important in supporting future risk reduction and adaptation measures. Here, we provide a review of the available scientific literature, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean region.

Uncertainty within climate model projections on interannual timescales are largely affected by natural climate variability. Emulators are valuable tools for approximating climate model runs, allowing for easy exploration of such uncertainty spaces. This study takes a first step at building a spatially resolved, monthly temperature emulator that takes local yearly temperatures as the sole input, thus providing monthly temperature distributions which are of critical value to impact assessments.

Reconstruction and explanation of past climate evolution using proxy records is the essence of paleoclimatology. In this study, we use dimensional analysis and concepts of similarity to recognize theoretical limits of such forensic inquiries.

Adding SO2 to the stratosphere could temporarily cool the planet by reflecting more sunlight back to the space. However, adding SO2 at different latitude(s) and season(s) lead to significant differences in regional surface climate. This study shows that, to cool the planet by 1–1.5 °C, there are likely 6-8 choices of injection latitude(s) and season(s) that lead to meaningfully different distributions of climate impacts.

Having descended through the water column, microplankton in ocean sediments represent the ocean surface environment and used as an archive of past surface ocean conditions. Here we define ocean bottom provinces based on the surface origin locations of these microplankton in an eddying ocean model. We find that these provinces can be detected in global datasets of sedimentary microplankton assemblages, which has implications for palaeoclimate reconstructions that use these microplankton.