New Compound Extreme Event Indicators for Detecting and Tracking Weather and Climate Extremes under Climate Change

Weather and climate extreme indicators are useful tools in the assessment and quantification of climate change induced alterations of key climate variables and extreme events. However, capturing both the main change aspects and the total extremity of such extreme events remains a challenging task.

Climate change can affect multiple characteristics of weather and climate extremes. Most indices, such as annual maximum temperature or number of hot days, focus on only one aspect of extreme events. While annual maximum temperature aims at describing the magnitude, the number of hot days is used for assessing the frequency of an extreme. The consideration of only one characteristic is a common limitation of such metrics. Since the total severity of extremes is the result of a combination of frequency, duration, magnitude and areal extent changes, however, the extremity is more than the sum of these parts and compound indices are hence required to fully capture the overall change.

Here we introduce Threshold-Exceedance-Amount (TEA) indicators as a new class of metrics that capture changes in event frequency, duration, magnitude, and spatial extent both in isolation and in total. Using a high-percentile-based threshold in a key climate variable that describes extreme magnitudes, the TEA metrics work in a cascaded manner up to expressing the total extremity of events, optionally also as an amplification vs. a suitable reference period.

Besides a detailed definition, we also show example applications for heat and heavy precipitation extremes (using daily maximum temperature and precipitation amount as key variables), from local- to country-scale regions in Austria to resolving and covering the entire European land region. We discuss amplifications and climate change detection vs. the 1961-1990 reference period and natural variability.

The TEA indicators are applicable for different types of extremes also beyond temperature and precipitation, making them a useful and versatile tool for the climate change-related investigation of extreme events and their impacts on natural and socio-economic systems, while also helping to fulfill the need for compound indices.