Ocean heat content (OHC) is an essential climate variable and is highly correlated with thermosteric sea level rise (TSL). In this study, ocean-thermal-expansion-based artificial neural network models were developed and validated to estimate TSL and, subsequently, OHC at 17 depths from the surface to 700 m. These models can accurately predict TSL and OHC for the given input data on sea surface temperature and sea surface salinity from any source.

Flows in the ocean are driven either by atmospheric forces or by small-scale internal disturbances that are inherently chaotic. We use computer simulation results to show that these chaotic oceanic disturbances can attain spatial scales large enough to alter the motion of Earth's pole of rotation. Given their size and unpredictable nature, the chaotic signals are a source of uncertainty when interpreting observed year-to-year polar motion changes in terms of other processes in the Earth system.

Utilizing the urban microclimate model PALM-4U, we show that temperature anomalies of ± 5 K at a depth of 2 m in the soil can impact atmospheric potential air temperatures within idealized domains. The impact depends on the season, time of day, land cover, and lateral boundary conditions of the domain. The magnitude of change depends mostly on seasonality and the time of day, ranging from 0.1 to 0.4 K. Land cover influences the absolute temperature but has a smaller impact on the magnitude.

Policy makers use global hydrological models to develop water management strategies and policies. However, it would be better if these models provided information at higher resolution. We present a first-of-its-kind, truly global hyper-resolution model and show that hyper-resolution brings about better estimates of river discharge, and this is especially true for smaller catchments. Our results also suggest that future hyper-resolution models need to include more detailed land cover information.

Current trends in CO₂ emissions increase the probability of an overshoot scenario in which temperatures exceed the targets of the Paris Agreement and are brought back afterwards with a net-negative emission strategy. This work analyses how the climate after the overshoot would differ from the climate before, linking large scale non-reversibility mechanisms to changes in regional climates and identifying those regions more impacted by changes in temperature and precipitation extremes.

The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.

We investigate the multiple equilibria window (MEW) of the Atlantic Meridional Overturning Circulation (AMOC) within a box model. We find that increasing the total carbon content of the system widens the MEW of the AMOC. The important mechanisms at play are the balance between the source and sink of carbon and the sensitivity of the AMOC to freshwater forcing over the Atlantic Ocean. Our results suggest that changes in the marine carbon cycle can influence AMOC stability in future climates.

Tropical rainforests risk tipping to savanna under future climate change. By analysing ecosystem root zone dynamics using hydroclimate data from Earth system models, we project the tipping risks for these rainforests. Our findings suggest that although some transition risks may be inevitable, most can still be mitigated by adapting to less severe climate change scenarios. Limiting global surface temperatures to meet the Paris Agreement targets is critical to preserving these ecosystems.

Climate models have transitioned to a superrotating atmospheric state under a broad range of warm climates. Such a transition would change global weather patterns should it occur. Here we simulate this transition using an idealized climate model and look for any early warnings of the superrotating state before it happens. We find several early warning indicators that we attribute to an oscillating pattern in the windfield fluctuations.

The El Niño–Southern Oscillation (ENSO) is a gigantic natural orchestra playing with the temperature of Pacific waters and influencing air temperature and rainfall worldwide. Naturally, the “loudness” or amplitude of ENSO has effects on climate; however, consonance of its various tones, or phases of different ENSO oscillatory components, can exert causal effects on rainfall in some areas in China. In different regions, different aspects of ENSO dynamics can predict rainfall amounts.

On 1 January 2020, international shipping vessels were required to substantially reduce the amount of particulate they emit to improve air quality. In this work we demonstrate how this regulatory change contributed to the anomalous warming observed in recent months using climate model simulations that include such a change. Future policies should also perhaps consider their impact on climate, and climate modelers should promptly include those changes in future modeling efforts.

Our study in eastern Siberia investigated how fires affect permafrost thaw depth in larch forests. We found that fire induces deeper thaw, yet this process was mediated by topography and vegetation. By combining field and satellite data, we estimated summer thaw depth across an entire fire scar. This research provides insights into post-fire permafrost dynamics and the use of satellite data for mapping fire-induced permafrost thaw.