Climate Variability and Extremes Analysis

The study of climate variability and extremes analysis centres on understanding fluctuations in climate parameters and the changing behaviour of rare, high-impact events. Variability refers to deviations from the mean state of climatic variables, including temperature and precipitation, across timescales from daily to decadal. Extremes, such as heatwaves, heavy rainfall and cold snaps, are governed by both shifts in the mean climate and changes in variability. As anthropogenic greenhouse-gas emissions have altered global temperature averages, research has increasingly focused on disentangling the contributions of mean warming and enhanced variability to changes in the frequency, intensity and distribution of extreme events. Robust detection and attribution frameworks employ large ensembles of climate models, novel statistical metrics and emergent constraints to reduce projection uncertainty. These tools advance our capability to assess future risks, inform adaptation strategies and guide policy decisions across sectors such as agriculture, water management and disaster preparedness.

Research from Nature Portfolio

Recent studies have highlighted the pivotal influence of variability on extreme events. One analysis has demonstrated that daily temperature variability explains a large fraction of regional sensitivities in heat extremes, often outweighing background warming in shaping both frequency and severity. This work emphasises the need to evaluate higher moments of temperature distributions alongside mean trends to improve model fidelity and risk assessments. Another contribution has quantified how changes in mean climate and variability independently modulate monthly temperature and precipitation extremes. Using probability-ratio techniques applied to large-ensemble simulations, it was shown that temperature extremes are predominantly driven by mean warming, whereas heavy-precipitation events depend substantially on trends in variability. These findings underscore spatial heterogeneity in the drivers of extremes and point to more robust projections for temperature compared to precipitation.

Research from all publishers

Advances in statistical diagnostics have improved detection of non-stationary behaviour in climate extremes. A recent methodological toolkit offers record-based tests that identify changes in the distribution of record-breaking events without assuming stationarity, providing accessible software for climate-service applications. In parallel, attribution frameworks have been extended to separate the roles of greenhouse-gas forcing on variability versus mean state, revealing that regional changes in temperature variability, distinct from average warming, can amplify or dampen extreme-event probabilities. Additionally, comparative assessments of methods for estimating the current climate mean have underscored the advantages of local linear regression in capturing nonlinear trends, thereby refining baselines for extreme-value analyses and enhancing consistency in climate monitoring.

Climate Variability and Extremes Analysis publication trend

The graph below shows the total number of articles in climate variability and extremes analysis across all publications each year (not limited to Nature Index journals).

Technical terms

Climate variability: Fluctuations in climate attributes around a long-term average over periods ranging from days to decades.

Extreme event: A rare climate occurrence, such as a heatwave or heavy precipitation, located in the tails of a probability distribution.

Probability ratio: A metric comparing the likelihood of an event under altered climate conditions to that under a reference climate.

Emergent constraint: A statistical relationship linking model performance on present-day observations to future projections, used to narrow uncertainty.

Non-stationarity: The property of a time series whose statistical characteristics, such as mean and variance, evolve over time.

References

1. RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events. Journal of Statistical Software (2023).
2. Attribution of extremes to greenhouse gas-induced changes in regional climate variability, distinct from changes in mean climate. Environmental Research Letters (2024).
3. Estimating trends and the current climate mean in a changing climate. Climate Services (2024).
4. Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes. Communications Earth & Environment (2021).
5. Quantifying the role of variability in future intensification of heat extremes. Nature Communications (2022).