This mini lesson focuses on the 2015-2016 El Niño event and how its weather conditions triggered regional disease outbreaks throughout the world. Students will review a NASA article and watch the associated video to use as a tool to compare with maps related to 2015-2016 rainfall and elevated disease risk, and answer the questions.
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Students will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. If the Data Literacy Map Cube is used with this, students will color their models first.
This lesson plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because it is a differentiated resource, this lesson plan is appropriate for multiple grade bands.
The El Niño Implementation Sequence provides a series of lessons and activities for students to learn about a condition that sometimes occurs in the Pacific Ocean, but it is so big that it affects weather all over the world.
Students will analyze a pie chart (circle graph) showing the distribution of different parts of the Earth system's absorption and reflection of energy.
The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.
This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.
Conduct this EO Kids mini-lesson with your students to explore the phenomenon of Urban Heat Island Effect.
By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.
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.