{"id":1817,"date":"2021-09-15T19:27:15","date_gmt":"2021-09-15T19:27:15","guid":{"rendered":"https:\/\/horizon.peachpuff-wolverine-566518.hostingersite.com\/?p=1817"},"modified":"2021-09-17T06:41:18","modified_gmt":"2021-09-17T06:41:18","slug":"new-forecasting-models-could-help-prevent-heat-related-deaths","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/horizon\/1817\/new-forecasting-models-could-help-prevent-heat-related-deaths\/","title":{"rendered":"New forecasting models could help prevent heat-related deaths"},"content":{"rendered":"

For parts of southern Europe, extreme heatwaves are now the rule, not the exception. New accurate and reliable weather prediction models could help regions better \u2018anticipate, prepare for, respond to and recover from\u2019 these increasingly extreme weather events.<\/strong><\/p>\n

To paraphrase a popular song from the early 2000s, \u2018it\u2019s getting hot in here\u2019 \u2013 especially in southern Europe. This summer saw the mercury hit a scorching 48.8\u00b0C in Sicily \u2013 possibly the hottest temperature ever recorded in Europe.<\/p>\n

This isn\u2019t just a fluke; temperatures have been steadily on the rise for years, the result of increasing \u2013 and largely unchecked \u2013 climate change.<\/p>\n

\u2018As average temperatures warm, extreme temperatures will also become warmer, leading to more frequent and warmer heatwaves,\u2019 said\u00a0Rachel White<\/a>, an assistant professor at the\u00a0University of British Columbia<\/a>. \u2018This is particularly concerning in regions that already experience high temperatures, such as southern Europe.\u2019<\/p>\n

Of all the natural disasters occurring in recent decades, heatwaves have caused the greatest loss of human life. And, as temperatures continue to increase,\u00a0more lives will be put at risk<\/a>.<\/p>\n

The key to saving lives is the use of accurate and reliable weather prediction models that go well beyond today\u2019s standard weekly forecasts.<\/p>\n

One such model is sub-seasonal to seasonal (S2S) forecasting.<\/p>\n

You can\u2019t predict the future, but\u2026<\/strong><\/p>\n

Falling between weather forecast models, which predict the weather over the next week or so, and climate models, which predict the average weather, or climate, over many years, S2S forecast serve as extended weather forecasts.<\/p>\n

To work, S2S models use the observed state of the atmosphere at the time the prediction starts and, based on this, simulate how the climate system will likely evolve over the next four to eight weeks. To account for the climate\u2019s natural variability, the model produces a group of different simulations based on slightly varied conditions.<\/p>\n

S2S models typically run for up to a few months. So, for example, we might use forecasts run from the beginning of June to predict the weather for the rest of the summer.<\/p>\n

Because of its ability to \u2018see into the future\u2019, S2S forecasting has the potential to accurately predict extreme weather events several weeks in advance \u2013 enough time for the impacted areas to react.<\/p>\n

Building more robust S2S models<\/strong><\/p>\n

However, despite this potential, S2S systems are a developing technology and remain in their infancy.<\/p>\n

\u2018Although promising, S2S forecast models are not sophisticated enough to forecast extreme heatwaves or to play a role in early warning systems,\u2019 said Marie Drouard, a researcher at the\u00a0Complutense University of Madrid<\/a>.<\/p>\n

Drouard, along with David Barriopedro, a researcher at the\u00a0Spanish National Research Council<\/a>, both of whom are part of the\u00a0ISSUL<\/a>\u00a0project, are working to advance the sophistication \u2013 and usefulness \u2013 of S2S models. To do so, they are turning to the power of machine learning.<\/p>\n

The benefit of using machine learning is that it allows one to analyse and make sense of huge amounts of data quickly and efficiently \u2013 which could prove to be extremely useful when it comes to predicting extreme weather events like heatwaves.<\/p>\n

\u2018We expect that, with the help of machine learning, S2S models will become sophisticated enough so that climatologists will someday use them to accurately predict heatwave frequency and intensity,\u2019 said Barriopedro.<\/p>\n

The researchers plan to test their machine-learning enhanced S2S model across southern Europe, including in Greece, Italy, the Balkans and the Iberian Peninsula.<\/p>\n

Putting the wave in heatwave<\/strong><\/p>\n

Prior research suggests that human-induced global warming causes the large-scale movement of air, known as atmospheric circulation patterns, that lead to more frequent heatwaves. \u2018This means climate change could have something of a one-two punch on heatwaves, causing not only all temperatures to be warmer, but also causing more frequent heatwaves due to changes in the atmospheric circulation patterns,\u2019 explained White.<\/p>\n

As part of the\u00a0PROTECT<\/a>\u00a0project, White, along with Donate, have demonstrated how many extreme\u00a0temperature events are associated with atmospheric circulation patterns called Rossby waves. These waves are known for both their strength and their habit of getting \u2018stuck\u2019 over, for example, Southern Europe for many days\u00a0or even weeks and causing the extreme and dangerous heatwaves like what was seen in the summer of 2021.<\/p>\n

\u2018Our research has opened the door to potentially using S2S forecasts to predict not just the surface temperatures of heatwaves, but also the atmospheric circulation conditions that cause them,\u2019 said White. \u2018This approach may be able to help improve S2S models\u2019 ability to forecast the likelihood of heatwaves over a particular region for a coming season.\u2019<\/p>\n

Research to the rescue<\/strong><\/p>\n

Although extreme heatwaves are always dangerous, due to population density, they pose a particular threat to urban areas.<\/p>\n

\u2018Urban areas must become more resilient to climate change and especially extreme heatwaves,\u2019 said Beniamino Russo, R&D project manager at the\u00a0SUEZ Group<\/a>\u00a0and scientific lead of the\u00a0RESCCUE<\/a>\u00a0project.<\/p>\n

Russo is helping create new solutions that cities can use to better anticipate, prepare for, respond to and recover from extreme weather events. These solutions, such as the “Framework for cities resilience assessment” or the “Tool and Database for the Selection of Adaptation Strategies” would\u00a0 allow city and emergency planners to predict and plan for moderate to heavy rain events, such as those that struck Germany, Belgium and the Netherlands in the summer of 2021.<\/p>\n

Researchers are now in the early stages of testing the system\u2019s applicability to extreme heatwaves, with tests taking place in Badalona, a municipality to the immediate northeast of Barcelona.<\/p>\n

To learn more about weather forecasting\u2019s role in addressing extreme heatwaves, be sure to tune into the\u00a0<\/em>European Centre for Medium-Range Weather Forecast\u2019s<\/em><\/a>\u00a0annual seminar, 13 \u2013 17 September.<\/em><\/p>\n

The research in this article was funded by the EU. <\/em><\/p>\n

More info<\/p>\n

RESCCUE<\/a>
\nPROTECT<\/a>
\nISSUL<\/a><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

For parts of southern Europe, extreme heatwaves are now the rule, not the exception. New accurate and reliable weather prediction models could help regions better \u2018anticipate, prepare for, respond to and recover from\u2019 these increasingly extreme weather events. 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