[{"command":"openDialog","selector":"#drupal-modal","settings":null,"data":"\u003Cdiv id=\u0022republish_modal_form\u0022\u003E\u003Cform class=\u0022modal-form-example-modal-form ecl-form\u0022 data-drupal-selector=\u0022modal-form-example-modal-form\u0022 action=\u0022\/en\/article\/modal\/6901\u0022 method=\u0022post\u0022 id=\u0022modal-form-example-modal-form\u0022 accept-charset=\u0022UTF-8\u0022\u003E\u003Cp\u003EHorizon articles can be republished for free under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.\u003C\/p\u003E\n \u003Cp\u003EYou must give appropriate credit. We ask you to do this by:\u003Cbr \/\u003E\n 1) Using the original journalist\u0027s byline\u003Cbr \/\u003E\n 2) Linking back to our original story\u003Cbr \/\u003E\n 3) Using the following text in the footer: This article was originally published in \u003Ca href=\u0027#\u0027\u003EHorizon, the EU Research and Innovation magazine\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003ESee our full republication guidelines \u003Ca href=\u0027\/horizon-magazine\/republish-our-stories\u0027\u003Ehere\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003EHTML for this article, including the attribution and page view counter, is below:\u003C\/p\u003E\u003Cdiv class=\u0022js-form-item form-item js-form-type-textarea form-item-body-content js-form-item-body-content ecl-form-group ecl-form-group--text-area form-no-label ecl-u-mv-m\u0022\u003E\n \n\u003Cdiv\u003E\n \u003Ctextarea data-drupal-selector=\u0022edit-body-content\u0022 aria-describedby=\u0022edit-body-content--description\u0022 id=\u0022edit-body-content\u0022 name=\u0022body_content\u0022 rows=\u00225\u0022 cols=\u002260\u0022 class=\u0022form-textarea ecl-text-area\u0022\u003E\u003Ch2\u003EManaging energy demand spikes with seasonal forecasts of heatwaves and cold spells\u003C\/h2\u003E\u003Cp\u003EResearchers already have the ability to predict what changes in climate can be expected in two to three weeks\u2019 time, or even in several months\u2019 time. Unlike weather forecasts, which look at rainfall and temperatures over the following hours and days, these climate forecasts aim to predict how conditions may change compared to what is normal for that time of year. Getting access to this information, however, is difficult as it is mostly available in a highly technical format that is unreadable to non-scientists.\u003C\/p\u003E\u003Cp\u003EThe energy industry in particular would benefit from having access to a simplified version of this information as it can help it to predict the likelihood of extreme weather events on a seasonal basis. For example, heatwaves tend to result in surges in energy usage as people crank their air conditioning up to full blast, and cold spells lead to excessive use of heating.\u003C\/p\u003E\u003Cp\u003EHeatwaves can be particularly problematic for the energy industry because they often knock out nuclear power stations too \u2013 large quantities of cold water are needed to cool down reactors, and during heatwaves and droughts, the water supply is likely too warm to use. This means that at the same time that energy demand is higher, the supply is compromised.\u003C\/p\u003E\u003Cp\u003E\u2018Both the energy supply and demand are dependent on climactic factors which may be predictable,\u2019 said Professor Alberto Troccoli of the University of East Anglia, managing director of the World Energy \u0026amp; Meteorology Council.\u003C\/p\u003E\u003Cp\u003E\u2018When you have events like heatwaves, the demand for energy goes up very quickly because there is more air-conditioning being used. The fact that you didn\u2019t predict that, and you have all this demand, means you have to source extra electricity. Because it\u2019s not ordered in advance, they\u2019ll charge you more and the prices go up.\u2019\u003C\/p\u003E\u003Cp\u003EProf. Troccoli coordinates a project called SECLI-FIRM, which is using models of how the climate behaves to understand what is likely to happen in the coming months.\u003C\/p\u003E\u003Cp\u003EUp until now, the energy industry has mainly looked at past climate variations, a practice known as climatology, to predict climate patterns in the coming months. However, this method is proving to be less and less reliable as climate change results in an increase in unexpected extreme weather events, which can affect demand. By contrast, climate models are becoming increasingly popular as they are displaying some positive results for predicting extreme temperature events, for example, this year\u2019s heatwave.\u003C\/p\u003E\u003Cp\u003E\u003Cblockquote class=\u0022tw-text-center tw-text-blue tw-font-bold tw-text-2xl lg:tw-w-1\/2 tw-border-2 tw-border-blue tw-p-12 tw-my-8 lg:tw-m-12 lg:tw--ml-16 tw-float-left\u0022\u003E\n \u003Cspan class=\u0022tw-text-5xl tw-rotate-180\u0022\u003E\u201c\u003C\/span\u003E\n \u003Cp class=\u0022tw-font-serif tw-italic\u0022\u003E\u0026#039;Both the energy supply and demand are dependent on climactic factors.\u0026#039;\u003C\/p\u003E\n \u003Cfooter\u003E\n \u003Ccite class=\u0022tw-not-italic tw-font-normal tw-text-sm tw-text-black\u0022\u003EProfessor Alberto Troccoli, University of East Anglia\u003C\/cite\u003E\n \u003C\/footer\u003E\n\u003C\/blockquote\u003E\n\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAccessible\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn addition to providing a reliable seasonal forecast, the modelling tool being developed by SECLI-FIRM aims to make seasonal climate forecast data more accessible for non-scientists \u2013 such as those working in the energy industry, but also in water supply, agriculture, wine production and olive oil, and even the insurance sector.\u003C\/p\u003E\u003Cp\u003EIt\u2019s an example of a new type of business known as climate services, which aims to turn climate science and data into usable tools and intelligence for organisations.\u003C\/p\u003E\u003Cp\u003EDr Albert Soret, from the Barcelona Supercomputing Center, said that in order to provide climate intelligence to businesses, it is vital to produce a seamless forecast that can be used for decision-making at different timescales.\u003C\/p\u003E\u003Cp\u003E\u2018At the end, we want to be able to explain a story to the (energy industry), so that they will be able to make a decision for the coming weeks and months,\u2019 he said.\u003C\/p\u003E\u003Cp\u003ESoret coordinates a project called S2S4E, which is building an online map of Europe containing forecasts that range from one week to four months ahead.\u003C\/p\u003E\u003Cp\u003EThe S2S4E map will highlight total installed power \u2013 the potential maximum power capacity \u2013 from wind and solar farms across Europe. The user will be able to point at a particular spot on the map and insert the timeframe that they want predictions for. The tool will then produce probability forecasts for rain, temperature, wind and other energy-specific variables.\u003C\/p\u003E\u003Cp\u003EThe project is based in a supercomputer centre because climate models are systems that emulate the whole Earth system, incorporating figures for sea surface temperature, snow cover and winds at any given time, and have to be run several times to get a good prediction.\u003C\/p\u003E\u003Cp\u003EDr Isadora Jimenez, who works on the S2S4E project, said: \u2018It\u2019s not something that you can calculate on your personal laptop.\u2019\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe S2S4E tool will be available by June 2019, while the SECLI-FIRM tool will come online in July 2020, though a prototype will be developed sooner.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EProbabilities\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOne of the main problems faced by both S2S4E and SECLI-FIRM is that the energy industry sometimes expects the data to be presented in the same way as weather forecasts. However, this isn\u2019t the case, as climate seasonal forecasts are based on probabilities.\u003C\/p\u003E\u003Cp\u003E\u2018If you\u2019re used to the weather forecast, you expect that someone will tell you the temperature\u2019s going to be 24 degrees with an error of plus or less one degree,\u2019 said Dr Jimenez.\u003C\/p\u003E\u003Cp\u003E\u2018In climate science we run a model a number of times, look at all the possible outcomes and results of that simulation and that gives you a probability. Climate predictions cannot tell you the weather in August is going to be 27 plus or less two degrees. They are going to tell you that you have a 70% probability of having temperatures above 24 degrees.\u2019\u003C\/p\u003E\u003Cp\u003EWith advanced information about energy shortages or surges in demand, however, companies can better organise themselves to avoid expensive fines and high energy prices. This is important because although the industry will shoulder any initial price hikes, it will ultimately be the customer who pays, according to Prof. Troccoli.\u003C\/p\u003E\u003Cp\u003E\u2018It\u2019s the users in the end that suffer,\u2019 he said. \u2018If (the extreme event) has a large enough effect when energy companies revise the energy price in six months or a year, you (the consumer) will likely see that increase.\u2019\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EThe research in this article was funded by the EU. 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