Data offers a crucial advantage for any kind of forecasting. One such applications where data analysis is of use is for weather forecast.
Importance Of Data In Weather
Data analytics can give us plenty of information about disasters and help in disaster readiness. They can be used to prepare for everyday conditions and catastrophic events, giving the authorities a fair advance warning for events such as tornadoes, hurricanes and tsunamis. The data needed for weather forecasting is the data like barometric pressure, wind speed, precipitation, temperature and humidity.
A team of researchers from Jain School of Engineering in India recently began developing a new Hadoop tool to help with this. According to them, providing access to random data makes this approach incredibly effective. They said that with the increasing amount of daily data its impossible to process and analyze data on a single system and thus there’s a need of Multiple Node HDFS system. Thus huge weather data can be easily processed with high end systems using Hadoop distributed file system in a very efficient manner The query tools makes the analytics much easier by providing random access to Big Data.
Weather Analytics Goes Beyond Forecasting
Weather-related applications are very generic applications of data analytics in weather. The data can also be used to solve many unconventional problems that are faced today, and not particularly thought of as solvable through the weather data.
Knowing the accurate situation of the weather is an important element for individuals and organisations. Many businesses are directly or indirectly linked with weather conditions. For instance, agriculture relies on perfect weather forecasting for when to plant, irrigate and harvest. With weather forecasting, your organization can work more accurately without any disturbance. Construction, airport control authorities are some of the other places where weather plays an important role.
Current Data Plays A Crucial Role For Weather Predictions
Also, it is essential to have the correct data for an accurate decision-making. The data has to be taken with respect to the location and taking into considering the time at which it is noted. Today, all the devices are IoT-enabled with gyrometer, barometers and all sorts of sensors in it. So location from the latitude longitude standpoint as well as from the elevation standpoint is very well available. Therefore, mobile phones proved to be a revolution in the analytics weather industry. So mobile really changed the industry.
Himanshu Goyal of The Weather Company said at Cypher 2018, “After few milliseconds, 60 percent of data goes irrelevant”. In case of using weather data, the data has to be used within minutes itself because nobody wants to know what had happened in the past. What is happening now and will happen in the future is more important. So data has to fall in and fall out quickly and recycle quickly, within minutes, in order to come up with a meaningful information.
It’s Not Just Natural Disasters, Weather Data Comes Handy For Many Events
- Predicting floods: Collecting data like the surrounding road condition and the rainfall of the area that year, floods can be predicted using weather analytics using models.
2. Sports: In sports matches like cricket, weather like rainfall can lead to pausing the game in between. There are applications which give you accurate time to play any sport in the climate that you wish to play. You can tell the app what weather you want to play the sport in. The app will within 3 days, within the current climate, what is the best time that you have to play the sport in the climate that you want.
3. Predict asthma attacks: Weather data can be used to improve medical outcomes like asthma. Asthma inhalers have sensors in them which can gather data to ensure that they are property used by the patients. It collects data such as temperature, humidity, air-quality, and presence of dust and other allergens. This information can predict where asthma can be triggers, helping with asthma patients.
4. Predict car sales: Weather analytics can be used to even figure out car sales based out of weather. In rainy people feel very timid and want to get out of the house and hence end up buying a car.
It is important to keep in mind that analytics is an important tool in weather and that every business must understand how it impacts the business and its customers. It is important for businesses to identify the right amount of data, because in a business like weather forecasting, even a data of of a couple of hours ago is stale.
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Found a way to Data Science and AI though her fascination for Technology. Likes to read, watch football and has an enourmous amount affection for Astrophysics.