Many of us have learned to take weather prediction for granted in our day-to-day lives. We have an app or website that can tell us not only what the weather is currently like just about anywhere in the world, but also what it is likely to do for the next several days. While these predictions still may not be as accurate as we would like, they provide a degree of confidence in the weather that is truly impressive.
But weather prediction has far more uses than simply letting us know whether to bring an umbrella or how hot we can expect it to be for that tropical vacation we’re taking. Weather Analytics, a climate data company, estimates that the weather affects over 33% of global GDP. From individual farms to large companies to national governments, weather data is an invaluable tool.
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Weather prediction is becoming more accurate and detailed thanks to the emergence of big data. Data analytics companies are able to collect vast amounts of information and produce detailed results for a wide range of uses. IBM, recognizing the importance of weather data, bought The Weather Company in order to be able to provide its clients with accurate, specific forecasts. It uses big data and machine learning in combination with The Weather Company’s global forecasting model to analyze the effect that weather has on things like customer buying behavior. This can allow businesses to better understand to what extent weather can be blamed or credited for changes in performance, and when it may be due to other factors.
Accurate weather prediction benefits agriculture in many ways. It is part of what makes precision agriculture possible, allowing for much more efficient use of resources and improved crop yields. Precision agriculture allows farmers to monitor every foot of their fields and care for them at a very fine level of detail. Using big data analytics, they can determine when and how to plant, fertilize, and harvest every individual crop, using only the resources that each one needs.
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About 80% of water usage in the United States comes from the farming industry. With detailed weather analytics, farmers can reduce their water usage, giving the crops only as much as they need to reach the next rainfall. Weather analytics can also provide detailed information on factors such as humidity and the best crops to plant in a particular microenvironment, leading to more successful crops and less waste. Better knowledge of the weather can also improve everything from fertilizer use to optimal harvesting time to efficient transportation.
There are many other areas in which weather analytics are beneficial. They can provide many savings to airlines, for example. Airplanes often fly with the minimal amount of fuel necessary to travel safely, in order to keep their weight as low as possible, saving fuel. The weather has a significant effect on the amount of fuel needed for a trip, so accurate weather prediction allows airlines to determine the optimal amount to bring.
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Governments are also taking advantage of weather analytics. Evacuation and disaster recovery are extremely expensive, so the ability to predict and pinpoint the effect of storms and other events can save millions of dollars, and potentially many lives as well. But there are less dramatic uses of this technology as well, such as predicting how many resources will be needed to deal with winter snowfall.
It turns out that the weather affects our lives and businesses more than we might realize. As the amount of available data grows and our technology becomes even better at drawing conclusions from it, weather analytics will be able to improve both profits and quality of life in an increasing number of ways.