International Journal of Microwave Engineering and Technology
Remote Sensing Technologies for Weather Forecasting: Techniques, Uses, andAssessment
Research Professor, Department of Commerce and Management and Humanities & Social Sciences, Srinivas University, Mangalore, Karnataka, India
Abstract
Remote sensing has become an important tool for modern weather forecasting since it lets us see the Earth's atmosphere and surface all the time and on a huge scale. Remote sensing uses satellites and sensors to collect data in real time on important weather variables like temperature, humidity, cloud cover, precipitation patterns, and atmospheric motion. These numbers are used in numerical weather prediction models to make forecasts more accurate and timely. Advanced remote sensing technology, such as multispectral and microwave sensors, make it easier to find extreme weather phenomena including cyclones, thunderstorms, and droughts. Also, combining with machine learning methods has greatly improved the ability to make predictions and lowered the level of uncertainty in weather forecasts. In addition, study looks at how remote sensing helps with climate monitoring, agricultural planning, safety in aviation, and catastrophe risk reduction—all of which depend on reliable meteorological data for public safety and decision-making. This paper talks about the basic ideas behind remote sensing, how it is used in meteorology, and how it might help make short- and long-term weather forecasts better. It also talks about problems that need to be solved right now, like data resolution, processing limits, and the need for better global coverage. In general, remote sensing is still very important for improving weather prediction systems, helping with disaster management, and studying climate.
Keywords - Remote Sensing, Predicting the Weather, Data from satellites, Weather Forecasting with Numbers, Monitoring the atmosphere, Climate Analysis
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