Utilizing big data in weather forecasting techniques

Abstract

Today, several parts of the society leverage Big Data to transform unstructured data into actionable information. In the field of weather forecasting, results from Big Data analytics can provide weather forecasters with valuable insights regarding past, present, and future weather patterns. The purpose of this review is to explore the use of big data in building sustainable weather forecasting. A total of 12 peer-reviewed articles were examined. The findings suggest that the use of Big Data in weather forecasting is partly motivated by the fact that an abundance of remote sensing and satellite devices are continually monitoring the weather system and collecting huge amounts of atmosphere data all over the world. With more data available, meteorologists are now able to predict weather in much better ways than ever and with more accuracy. However, problems related to Big Data itself (volume, variety, velocity, veracity and value), the complexity of hardware and software involved, data detection challenges, architecture and algorithm, and issues with estimating statistical significance impact the use of Big Data in predicting the weather. Additional research is recommended to help meteorologists to overcome the challenges linked to using Big Data tools, applications, and technologies in forecasting.