Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.

Using an infographic, students describe differences in electromagnetic radiation that is part of a model of Earth’s energy budget by applying the defined terms of Shortwave Radiation and Longwave Radiation.

A kinesthetic activity that challenges students to participate in a model that describes the fate of solar energy as it enters the Earth system.  A good initial lesson for Earth’s energy budget, students unravel the benefits and limitations of their model.

Students move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites.  In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.

Students will analyze a graph showing the variation of energy imbalance on Earth over the year along different latitudinal zones and answer the questions that follow.

Students watch a video and answer questions on Dr. Patrick Taylor (Atmospheric Scientist, NASA Langley Research Center) as he discusses the study of clouds and Earth's energy budget by analyzing data from Low Earth Orbit satellites. 

Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.

Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.

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.