How to stop being surprised by unprecedented weather

Abstract

We see unprecedented weather causing widespread impacts across the world. In this perspective, we provide an overview of methods that help anticipate unprecedented weather hazards that can contribute to stop being surprised. We then discuss disaster management and climate adaptation practices, their gaps, and how the methods to anticipate unprecedented weather may help build resilience. We stimulate thinking about transformative adaptation as a foundation for long-term resilience to unprecedented weather, supported by incremental adaptation through upgrading existing infrastructure, and reactive adaptation through short-term early action and disaster response. Because in the end, we should take responsibility to build resilience rather than being surprised by unprecedented weather.

Fig. 1. An overview of the categories of approaches that exist to identify unprecedented weather.

The thermometer icon was made by justicon; tree rings and oral history icons made by Freepik and flood icon made by Konkapp and obtained from www.flaticon.com.

Fig. 2. Examples of historical weather events which are unsurpassed.

In Durham (UK), the two warmest Junes on record occurred in 1826 and 1846, and are >1.5 °C warmer than any other June in the post-1850 period (a). The grey lines indicate times when only monthly data are available, whereas daily data are available for the period shown by the black line. For Oxford (UK), the wettest month on record remains September 1774, around 15% wetter than any other month (b); recently, September 2024 became the second-wettest on the 250+ year record.

a Annual daily maximum air temperature at Eindhoven, 1951–2023 (95% CI) with the effects of global mean surface temperature (smoothed) linearly subtracted from the position parameter, for the preindustrial (in green) and current climate (in orange). The observed record temperature of 40.4 °C in 2019, is shown by the red horizontal line (Data is from the KNMI observational network, station number 370). b Reconstructed temperature data for summertime (June–July–August) mean temperature anomalies over the Netherlands (3.75–6.75 °E, 51.25–53.75 °N) from 1500 to 2003 (Data taken from KNMI Climate Explorer, as in Luterbacher et al.,). c Maximum temperature during the three hottest days of the July 2019 heatwave as simulated by the convection permitting climate model HCLIM43 for the current climate (right half) and under +2 K warmer scenario (left half). The small circles in the right half show observations from Dutch Meteorological stations. The large circle is centred around the city of Eindhoven. d Annual daily maximum air temperature at the nearest grid point to Eindhoven in ERA5 (blue dots) and in a bias-adjusted 16-member regional climate model ensemble (black dots). The regional climate model RACMO was nested in the global climate model EC-Earth3; historic forcing until 2014, SSP5-8.5 forcing from 2015. Grey shading shows an estimated normal distribution (mean plus 1 and 2 standard deviations) based on the model ensemble.

Fig. 3. The conceptual adaptation pyramid illustrates how three layers of adaptation contribute to resilience to unprecedented weather.

a An unstable pyramid: with little transformative actions, we increase our reliance on incremental adaptation and place a lot of emphasis on handling unprecedented weather through early warning, early action and disaster response. b A stable pyramid: with more emphasis on transformative actions, we may be able to prevent limits to incremental adaptation, and have to place less emphasis on reactive actions.

Fig. 4. Expected impacts and cascading effects of unprecedented heat.

This mindmap, based on Klok and Kluck , illustrates how unprecedented heat affects various sectors. On the left, unprecedented heat is positioned centrally, with various colours representing pressures on sectors such as the environment, living conditions, water availability, infrastructure and healthcare. On the right, the same mindmap is reorganised to illustrate that multiple pressures have cascading impacts on the city’s healthcare.