Future Temperature Extremes Will Be More Harmful: A New Critical Factor for Improved Forecasts

Abstract

There is increasing evidence that extreme weather events such as frequent and intense cold spells and heat waves cause unprecedented deaths and diseases in both developed and developing countries. Thus, they require extensive and immediate research to limit the risks involved. Average temperatures in Europe in June–July 2019 were the hottest ever measured and attributed to climate change. The problem, however, of a thorough study of natural climate change is the lack of experimental data from the long past, where anthropogenic activity was then very limited. Today, this problem can be successfully resolved using, inter alia, biological indicators that have provided reliable environmental information for thousands of years in the past. The present study used high-resolution quantitative reconstruction data derived from biological records of Lake Silvaplana sediments covering the period 1181–1945. The purpose of this study was to determine whether a slight temperature change in the past could trigger current or future intense temperature change or changes. Modern analytical tools were used for this purpose, which eventually showed that temperature fluctuations were persistent. That is, they exhibit long memory with scaling behavior, which means that an increase (decrease) in temperature in the past was always followed by another increase (decrease) in the future with multiple amplitudes. Therefore, the increase in the frequency, intensity, and duration of extreme temperature events due to climate change will be more pronounced than expected. This will affect human well-being and mortality more than that estimated in today’s modeling scenarios. The scaling property detected here can be used for more accurate monthly to decadal forecasting of extreme temperature events. Thus, it is possible to develop improved early warning systems that will reduce the public health risk at local, national, and international levels.