Students will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre
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Using various visualizations (i.e., images, charts, and graphs), students will explore the energy exchange that occurs when hurricanes extract heat energy from the ocean. This story map is intended to be used with students who have access to a computing device in a 1:1 or 1:2 setting.
Students analyze surface air temperature anomalies to identify change with respect to different latitudes across the world.
This story map allows students to explore the formation and impacts of ash and aerosols from volcanic eruptions around the world in a 5 E-learning cycle. They will investigate how ash and aerosols produced from volcanic eruptions are hazardous to the human ecosystem, and will analyze concentrations of aerosols from a volcanic eruption over time.
Students identify patterns and describe the relationship between chlorophyll concentration and incoming shortwave radiation.
This story map lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System.
Students identify patterns in chlorophyll concentration data to formulate their explanations of phytoplankton distribution.
Students will identify and describe the relationship between watersheds and phytoplankton distribution.
Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year. Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S
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.