Winter can be a magical time of year, with the crisp air and the beautiful sight of snowflakes covering the ground. However, snowstorms can also cause havoc for travel, infrastructure, and personal safety.

Being able to predict when a snowstorm is coming and how severe it will be is critical for planning and decision making. Forecasters use a variety of tools and techniques to forecast snowstorms, including computer models, satellite imagery, and ground observations.

Computer Models

Computer models are used to simulate atmospheric conditions and predict how they will evolve over time.

By inputting data on temperature, pressure, wind, and moisture, forecasters can create a model of the atmosphere and simulate how it will react to different conditions. These models are run multiple times with slight variations in the input data to create a range of possible scenarios.

The most important computer model used for snowstorm forecasting is the Global Forecast System (GFS), which is run by the National Oceanic and Atmospheric Administration (NOAA).

The GFS provides a forecast for the entire world and produces hourly forecasts up to 10 days in advance. This model is used by many weather websites and apps to provide forecasts to the public.

Satellite Imagery

Satellite imagery provides a unique perspective on the atmosphere by allowing forecasters to see the movement and development of weather systems from above.

Satellites can detect changes in temperature, humidity, and wind which can help forecasters predict where storms will form and how they will move. They can also provide valuable information on cloud cover, which can have a significant impact on snowfall amounts.

The most commonly used satellite for snowstorm forecasting is the Geostationary Operational Environmental Satellite (GOES). The GOES provides a constant view of the weather over the United States and can detect changes in weather patterns in real-time.

The data from the GOES satellite is used in conjunction with computer models to create a more accurate picture of the atmosphere.

Ground Observations

Ground observations provide data on current conditions that can be used to validate computer models and satellite data. Automated weather stations and weather balloons provide data on temperature, humidity, wind speed, and direction.

This information is used to create a more accurate model of the atmosphere and to make adjustments to the computer models and satellite data.

Forecasters also rely on reports from spotters and citizen scientists who provide information on snowfall amounts and other weather conditions in their area.

This information is particularly valuable in areas where automated weather stations are not available.

Using Multiple Sources

Forecasters use a variety of tools and techniques to predict snowstorms, and each source has its strengths and weaknesses. By using multiple sources of data, forecasters can create a more accurate prediction of the weather.

This is known as ensemble forecasting and involves running multiple computer models and combining the results to create a range of possible scenarios.

Ensemble forecasting is particularly useful for predicting extreme weather events, such as blizzards, which can be difficult to predict accurately.

By combining multiple sources of data, forecasters can identify areas of agreement and areas of uncertainty and make more informed decisions.

Challenges of Snowstorm Forecasting

Despite the advances in technology and forecasting techniques, predicting snowstorms remains a difficult task.

The atmosphere is a chaotic system, and small changes in temperature, pressure, or wind can have a significant impact on the development and movement of a storm.

Another challenge of snowstorm forecasting is the wide range of possible snowfall amounts within a storm. Snowfall amounts can vary significantly within a short distance due to changes in temperature, moisture, and wind.

This makes it difficult to provide accurate snowfall forecasts, particularly in areas with complex terrain.

Conclusion

Forecasting snowstorms is a critical task that requires the use of multiple sources of data and advanced forecasting techniques.

By using computer models, satellite imagery, and ground observations, forecasters can create a more accurate prediction of the weather. However, predicting snowstorms remains a difficult task due to the chaotic nature of the atmosphere and the wide range of possible snowfall amounts within a storm.