Recent  

Climate change has been proven to be an indisputable fact and to be occurring at a faster rate in boreal forest areas. The results of this paper show that the boreal forest coverage has shown an increasing trend in the past three decades, and the area of broad-leaved forests has increased more rapidly than that of coniferous forests. In addition, temperature rather than precipitation is the main climate factor that is driving change.

We report on the ocean carbon sink and sources of uptake uncertainty from the latest version of the Coupled Model Intercomparison Project. We show that knowledge about historical regions of uptake will provide us information about future regions of uptake change and uncertainty. We break down the uncertainty to the sources and evaluate the dependence on location and integeration scale. Our results help us make useful suggestions for both modeling community and observational campaign planning.

Planting trees cools the climate by removing CO2 from the atmosphere, but may also cool or warm the climate by altering the albedo, roughness and evapotranspiration efficiency of the surface. To quantify these biogeophysical effects, we ran regional climate models over two idealized worlds, FOREST and GRASS, respectively representing maximum and minimum tree cover over North America and Europe. We find that these effects must be taken into account to successfully mitigate climate change.

We study the impact of a rapid melting of the ice sheets on monsoon systems during the 21^st century. The impact of a partial Antarctica melting is moderate. Conversely, Greenland melting slows down the oceanic Atlantic circulation, changes winds, temperature and pressure patterns, resulting in a southward shift of the tropical rain belt over Africa and America. The seasonality, duration and intensity of rainfall events are affected, with potential severe impacts on vulnerable population.

How the structure of resource governance systems affects how they respond to change is not yet well understood. We model the stability of thousands of different governance systems, revealing that greater diversity and interdependence among actors is destabilizing, while venue shopping and advocacy organizations are stabilizing. This study suggests that complexity in governance corresponds to responsiveness to change, while providing insight into managing them to balance adaptivity and stability.

Solar Radiation Modification (SRM) entails technologies that artificially cool the climate but do not act on the cause of climate change. We assess the time of commitment to SRM if it was implemented on top of a current policy scenario to keep warming to 1.5 °C until emission cuts and Carbon Dioxide Removal (CDR) have reduced GHGs sufficiently. Here, SRM, even when combined with high CDR, would come with century-long legacies of deployment, implying centuries of costs, risks and side effects.

This work focuses on the study of daily wet-cold compound events in Greece in the period November–April. We firstly study the historic period 1980–2004 in which we validate projection models with observations. Then we compare the model results with future period 2025–2049 rcp4.5 and rcp8.5 scenarios. The aim of the study is to calculae the probability of the events and to locate the areas where those are higher and how the probabilities will change at the future.

The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon’s orbital plane and affects ocean tides. In this work we use a climate model to examine the effect of this cycle on the ocean, surface and atmosphere. The timing of anomalies is consistent with the so-called slowdown in global warming, and have implications for when global temperatures will exceed 1.5 C above pre-industrial levels. Regional anomalies have implications for seasonal climate over Europe especially.

Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meet these demands in a comprehensive way and may thus support a fully integrated impact research effort, and save resources for the climate modeling enterprise.

Climate projections and multi-model ensemble weighting are increasingly used for climate assessments. This study examines the sensitivities of model weighting and multi-model ensemble means across multiple dimensions using projections in the south central United States. Model weighting and ensemble means are sensitive to the domain and variable used. This study recommends that multiple weighting strategies be used with consideration for the needs of the research project or planning exercise.

This study endorses RCMs' added-value upon their driving GCMs in representing observed heat wave magnitudes. The future increase of heat wave magnitudes projected by GCMs is attenuated when downscaled by RCMs. Within the downscaling, uncertainties can be attributed almost equally to choice of RCMs and to the driving data associated with different GCMs. Uncertainties of GCMs in simulating heat wave magnitudes are transformed by RCMs in a complex manner, rather than simply inherited.

Equilibrium climate sensitivity (ECS) is a measure of how much long term warming should be expected in response to a change in greenhouse gas concentrations. It is generally calculated in climate models by extrapolating global average temperatures to a point of where the planet is no longer a net absorber of energy. Here we show that some climate models experience energy leaks which change as the planet warms, undermining the standard approach and biasing some existing model estimates of ECS.

Subseasonal forecasts facilitate early warning of extreme events, however, their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.

Near-term climate change projections are strongly influenced by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainties by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting the first two decades. We also show the applicability of regional constraints in attributing predictability to certain ocean regions.

The El Niño Southern Oscillation is the main driver for the natural variability of global atmospheric CO₂. It modulates the CO₂ fluxes in the tropical Pacific with anomalously CO₂ influx during El Niño and outflux during La Niña. Climate projections under the business-as-usual scenario show a reversal of this behaviour is projected by half of Earth System Models. Changes in Revelle factor and subsurface distribution of dissolved Inorganic carbon are the two leading factors for this reversal.

Quantifying the imprint of large-scale atmospheric circulation dynamics and associated carbon cycle responses is key to improve our understanding of carbon cycle dynamics. Using a statistical model that relies of spatio-temporal sea level pressure as a proxy for large-scale atmospheric circulation, we quantify the fraction of interannual variability in atmospheric CO₂ growth rate and the land CO₂ sink that are driven by atmospheric circulation variability.

ENSO is one of the dominant climatic phenomena in the equatorial Pacific. Understanding and predicting how ENSO might change in a warmer climate is both societally and scientifically important. We use thousand-year-long simulations from seven climate models to analyze ENSO in an idealized stable climate. We show that ENSO will be weaker and last shorter under the warming, while the skill of ENSO prediction will unlikely to change.