Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2017, and then answer the following questions.
Educational Resources - Search Tool
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.
These six graphs show Ocean Chlorophyll Concentrations from 1998 - 2018 in a variety of locations: East Bering Sea, Gulf of Alaska, California Coast, Southeastern US/Gulf of Mexico, Northeastern US and the Scotian Shelf, and the Hawaiian Islands.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.ās famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nationās capital.
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
Students collect and analyze temperature data to explore what governs how much energy is reflected.
Students review the NASA video showing biosphere data over the North Atlantic Ocean as a time series animation displaying a decade of phytoplankton blooms and answer questions.
The activities in this guide will help students understand variations in environmental parameters by examining connections among different phenomena measured on local, regional and global scales.
To help students articulate and integrate their existing knowledge about the air, water, soil, and living things by viewing them as interacting parts of a system
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.