Extreme Value Analysis of Precipitation Events

Extreme Value Analysis (EVA) of precipitation seeks to characterise the statistical behaviour of rare, high‐intensity rainfall events by focusing on the tail of the precipitation distribution. This field combines parametric methods, which assume a specific form for the tail (for example using the Generalized Extreme Value distribution), with non‐parametric and semi‐parametric approaches that make fewer assumptions about underlying processes. Recent advances have embraced non‐asymptotic frameworks that include all events rather than only block maxima or threshold exceedances, leading to smoother spatial representations and reduced uncertainty. Convection‐permitting climate models and high‐resolution global precipitation products are increasingly exploited to capture sub‐daily extremes and longer return periods. Such analyses are critical for understanding how climate change will affect the frequency and intensity of severe rainfall, informing flood risk management, infrastructure design and water resource planning across diverse climatic and orographic settings.

Research from Nature Portfolio

Recent studies have introduced a superstatistical distribution to model annual maximum daily precipitation on a global scale. This framework derives an exact closed‐form distribution under the hypothesis of stochastic independence and then allows its parameters to vary year to year according to empirical probability laws. When tested against more than twenty thousand sites worldwide, the superstatistical distribution provides more robust estimates of extreme quantiles than the classical Generalized Extreme Value approach, particularly for design‐relevant high return periods. By tending to overestimate the largest quantiles, it offers a conservative and safer option for hydraulic and infrastructural design.

Extreme Value Analysis of Precipitation Events publication trend

The graph below shows the total number of articles in extreme value analysis of precipitation events across all publications each year (not limited to Nature Index journals).

Technical terms

Extreme Value Analysis (EVA): The statistical study of the tail behaviour of distributions to characterise the frequency and magnitude of rare events.

Return period (or return level): The average interval of time between events exceeding a specified magnitude in a stationary climate.

Generalized Extreme Value (GEV) distribution: A three‐parameter family used to model block maxima (e.g. annual maxima) under classical extreme value theory.

Peak-Over-Threshold (POT) method: An approach that models exceedances above a high threshold using the Generalized Pareto distribution.

Metastatistical Extreme Value (MEV) distribution: A non-asymptotic framework that uses all available precipitation events to derive return levels, yielding smoother spatial patterns.

Superstatistical distribution: A model that integrates year-to-year variability in distribution parameters, offering closed-form expressions for extremes while accounting for non-stationarity.

References

1. Superstatistical distribution of daily precipitation extremes: A worldwide assessment. Scientific Reports (2018).
2. Frequency Rather Than Intensity Drives Projected Changes of Rainfall Events in Brazil. Earth's Future (2024).
3. A Method to Assess and Explain Changes in Sub‐Daily Precipitation Return Levels From Convection‐Permitting Simulations. Water Resources Research (2024).