Students examine the two time series images to determine the differences between seasonal ice melt over water versus land.

Students observe seasonal images of Monthly Leaf Area, looking for any changes that are occurring throughout the year.

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 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.

In this mini lesson, students explore the relationship of chlorophyll and solar radiation by analyzing line graphs from the North Atlantic during 2016-2018.

An environmental planner tries to minimize the environmental impacts of housing, industrial, and transportation-related construction projects. Environmental planners help project managers navigate the environmental permitting process where they review a site to investigate potential environmental effects. This includes the effects of natural disasters.

Charles Gatebe is a climate scientist who studies reflected sunlight to improve our understanding of the composition of the atmosphere and surface properties, including land and ocean, and impact on Earth's radiation budget and climate. Learn about how he conducts experiments and uses data from around the world.

Students will analyze surface temperature and solar radiation data to construct explanations about the relationship of seasons and temperature to the amount of solar energy received on Earth’s surface.

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.

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