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

Hands-on demonstration of the El Niño Effect, trade winds, and upwelling provided by NASA's Jet Propulsion Lab.

Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.

Students collect and analyze temperature data to explore what governs how much energy is reflected. 

The Earth System Poster activity walks learners through global patterns and illuminates how each of the spheres is interconnected across the world. We will divide into small groups to look at maps of different parts of the earth system that have been observed by NASA satellites.

An urban heat island is a phenomenon that is best described when a city experiences much warmer temperatures than in nearby rural areas. The sun’s heat and light reach the city and the country in the same way. The difference in temperature between urban and less-developed rural areas has to do with how well the surfaces in each environment absorb and hold heat.

This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change. 

What is El Nino or ENSO?

Hurricanes are the most powerful weather event on Earth. NASA’s expertise in space and scientific exploration contributes to essential services provided to the American people by other federal agencies, such as hurricane weather forecasting.

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.