Students explore the spatial patterns observed in meteorological data and learn how this information is used to predict weather and understand climate behavior.

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.  

Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animations of the monthly mapped data showing incoming and outgoing shortwave radiation from Earth’s surface.

This mini lesson engages students by watching a NASA video related to seasonal chlorophyll concentration as it relates to net radiation using NASA's Aqua satellite. Students will examine the model and answer the questions.

Students watch videos and review articles related to ozone as a pollutant at ground level, and how ozone impacts environment, then provide their understanding in groups.

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.

In this activity, learners will explore an additional tool used to observe the Sun’s atmosphere, called a coronagraph. Learners will create a flipbook of a coronagraph showing a coronal mass ejection.

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.