Our site provides links to various temperature models used by students for making predictions. Explore the data and see how professionals forecast weather. Explore our temperature analysis page to understand each model.
KAXA is our Local Station where weather data is recorded.
Climatology refers to the study of historical weather data over a long period. By analyzing average temperatures and weather patterns from past years, students can predict future temperatures based on what is typical for a given time of year in Algona, Iowa.
Persistence forecasting is based on the assumption that current weather conditions will continue into the near future. For example, if today’s high was 75°F, a persistence forecast might predict a similar temperature for tomorrow.
The NAM model is a weather prediction model used for short-term forecasts (up to 84 hours). It provides detailed information on weather patterns and is particularly useful for predicting temperature, precipitation, and other weather variables.
The GFS model is a global weather prediction model that offers forecasts up to 5 days in advance. It is used for both short-term and long-term weather predictions, providing a broader overview of potential weather changes.
NAM MOS involves statistical techniques to refine the raw data from the NAM model. This process adjusts the model output to correct for any biases, offering more accurate temperature and weather predictions.
Similar to NAM MOS, GFS MOS applies statistical methods to the GFS model output. This helps to enhance the accuracy of the GFS model’s forecasts by correcting systematic errors and aligning predictions more closely with observed weather patterns.
Take the google quiz to test your knowledge on the various Temperature Models: QUIZ