To accurately predict changes in weather, a meteorologist would benefit from tracking a variety of weather-based data, including:
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Temperature: Current, historical, and forecasted temperatures help in understanding weather patterns and trends.
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Humidity: Relative humidity levels indicate the amount of moisture in the air, which plays a critical role in precipitation and storm formation.
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Barometric Pressure: Changes in air pressure can signal incoming weather systems. A falling pressure often indicates stormy weather, while rising pressure can signify clearing conditions.
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Wind Speed and Direction: Wind patterns influence weather systems and play a crucial role in temperature and precipitation movements.
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Precipitation Data: Tracking rain, snow, sleet, and other forms of precipitation helps in predicting weather events and their intensity.
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Cloud Cover: The type, height, and coverage of clouds can indicate upcoming weather changes, including storms.
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Radar Data: Doppler radar provides real-time information on precipitation and storm developments, vital for severe weather warnings.
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Satellite Imagery: Satellites provide large-scale observations of weather systems and cloud cover, helping track storm systems and monitor ongoing weather events.
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Severe Weather Alerts: Monitoring watches and warnings from local and national meteorological organizations helps prepare for extreme weather.
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Oceanic Data: Information on ocean temperatures (such as Sea Surface Temperature, SST), currents, and anomalies (like El Niño and La Niña) can greatly influence weather patterns.
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Climate Data: Historical weather patterns and long-term climate data aid in understanding trends and variations over time.
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Soil Moisture: Especially important for forecasting local weather impacts such as fog formation, localized storms, and drought conditions.
By combining these data types, meteorologists can create models to forecast weather more accurately and make informed predictions about imminent weather changes.