Global predictability of temperature extremes

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Global predictability of temperature extremes
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Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world's population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.

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she waves and cold waves are responsible for 75 per cent of all weather-related death in high income countries in 2 thousand 315 thousand people died in a heat wave in France and he would later that year in India 900 people die for the red cross the crescent this is a big problem in Bangladesh Bangladesh Red Crescent responded to a deadly cold we've only a few months ago and he lives are becoming more frequent and intense due to climate change but
why is this happening is it because we don't know what to do to respond here is the cold wave now burstiness we provide water in cooling centers for call these be provide blankets and for
the homeless is evolving very effective though if we know what to do why do people still suffer can we figure out when to do it and that's the question we looked at in this research here we analyzed all the places in the world where there is a distinct season for he it you can take action to prepare in advance of parties most Odesta
topics that have this the analogy in dark green we also researched whether we can forecast individual heat wave of and the results are amazing
in dark red are all the places where weather forecasts can skillfully predicts he waited 10 days before they happen if we combine these 2 maps you can do it in black all the places where we could take the low prepared factions as well as short-term forecasts based action to prepare for individual he that you look at a map of global population
you could think of 5 billion people live in his region colored in black but cold waves
the results are broadly similar we have clear sionality in the extra topics and with the short term predictability in much of the world however if you remember that from present in the Dutch coldly if you can see that in Bangladesh the models do not have good predictability for Bayes factors can use these maps to identify areas for further research work best in weather stations in
combination similarity he we have 5 billion people live in regions that could prepare for cold wave both for this reason the cold season happens as well as using short-term forecasts and warnings for individual we have to we can prepared his capacity around the world and make really action plans to ensure that we do take action and so much of the world to prepare for he based and called the


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