2017 was a crazy year for weather. Between monster hurricanes, devastating wildfires spread by howling Santa Ana winds and bone-chilling snowstorms, we\u2019ve seen it all. And these extreme weather events did not stop when the calendar hit 2018. Winter Storm Grayson just tore up the East Coast, bringing snow from Florida up to Maine, along with hurricane force winds, snow, and coastal flooding.\nSevere weather isn\u2019t going anywhere. So what are the best ways to deal with it in the new year? Let\u2019s look through the four weather trends that us meteorologists at Earth Networks expect to play out this year and how they help people mitigate business risks due to weather.\n1. Massive amounts of weather data\nOne trend we\u2019ve watched over the last few years is the amount of weather data accessible to meteorologists, organizational decision-makers, and every day people alike. Over the past few years we\u2019ve seen a sharp increase in the sheer amount of data we create as a planet. Think about this: nearly 90% of the world\u2019s data was created in the last two years. That\u2019s impressive.\nAnd it\u2019s not just the amount of data that\u2019s important for weather; it\u2019s the accessibility. In today\u2019s digital age, you can access weather data from your TV, radio, smart phone, tablet, smart home application, car, and more. Which is great because research from Domo shows that forecast requests are up 22% from last year.\nIn 2018, we expect to see even more weather data available; both free and paid. Not only will these aforementioned technology categories show weather data, but they will collect them as well. Internet of Things (IoT) devices like phones and cars are collecting weather data themselves. 2018 is going to be an exciting year for weather data collection.\n2. Weather data modeling and machine learning\nWe are seeing a growing trend of businesses realizing value from their weather data investments and we expect this trend to accelerate as a result. This, in part, will be thanks to weather data modeling and machine learning. Conventional computer modeling relies on programmers determining the rules and facts to guide the system\u2019s output. Machine-learning systems, on the other hand, derive their own rules after combing through large amounts of data.\nBoth will become increasingly important for weather data as a solution in 2018. Not only will these make sharing weather data easier, but they\u2019ll help predict the weather too. Don\u2019t worry \u2013 us meteorologists aren\u2019t going anywhere (yet!) but computer modeling and machine-learning are trends that are here to stay.\nFor example, did you know that the United States National Oceanic and Atmospheric Administration (NOAA) already uses artificial intelligence (AI) in their forecasting endeavors? By combining AI techniques along with the physical understanding of the environment (this is where us meteorologists come in!) NOAA can improve the prediction skill for multiple types of severe weather like thunderstorms, tornadoes, and hurricanes.\n3. Using climate data records in decision making\nA question that business-owners will start asking themselves in 2018 is: \u201cHow is climate change going to affect my business?\u201d Of course, the answer to this question varies depending on things like industry, location, and size. And one of the best ways for CIOs to gauge the answer is through climate data records.\nFederal, state, and local government and private sectors can use climate data records to help make decisions in 2018 that will prepare them for their climate 5, 10, and even 50 years from now. By looking into the trends and patterns of the past we can more accurately predict future weather patterns. NOAA\u2019s Climate Data Record Program is applying modern data analysis methods to historical global satellite data. This type of information allows businesses, resource managers, decision makers, and the public better understand and responsibly adapt to climate changes and variability as well as develop strategies to minimize risks and mitigate possible impacts on society.\n4. Implementing more customizable tools\nWeather data is not one-size-fits-all. There are dozens of different data points out there and some of them just aren\u2019t important for specific regions and\/or operations. For example, an oil company with rigs in the Gulf of Mexico cares a lot more about hurricanes than a ski mountain in Colorado. Here\u2019s another example: A utility company cares about thunderstorms in multiple locations while a professional sports team cares about storms near their one location. There are literally thousands of use cases for weather data.\nSince weather data is not one-size-fits-all, neither are weather tools. That\u2019s why customization is so important. Tools that allow governments and organizations to select locations, conditions, and warnings that matter to them most will be both convenient to use and time-saving. These types of tools are especially useful when they allow users to input their own data into the tool as well. Imagine a utility company seeing live storm data and their own power grid on the same application to trigger alerts on specific threats at the intersection points. That\u2019s what customizable weather tools can do.\nBe prepared\nNo matter what Mother Nature decides to throw at you this year, the key of all four of these trends is to be prepared. Weather-related decision making is going to be critical to operations all around the world this year. The worst thing a CIO or any other decision-maker at an organization or government can do is underestimate the power of accurate weather data and warnings. Make one of your new year\u2019s resolutions the resolution to get your business weather-ready.