In this Earth Exploration Toolbook chapter, students select, explore, and analyze satellite imagery. They do so in the context of a case study of the origins of atmospheric carbon monoxide and aerosols, tiny solid airborne particles such as smoke from forest fires and dust from desert wind storms. They use the software tool ImageJ to animate a year of monthly images of aerosol data and then compare the animation to one created for monthly images of carbon monoxide data. Students select, explore, and analyze satellite imagery using NASA Earth Observatory (NEO) satellite data and NEO Image Composite Explorer (ICE) tool to investigate seasonal and geographic patterns and variations in concentration of CO and aerosols in the atmosphere.
C-Learn is a simplified version of the C-ROADS simulator. Its primary purpose is to help users understand the long-term climate effects (CO2 concentrations, global temperature, sea level rise) of various customized actions to reduce fossil fuel CO2 emissions, reduce deforestation, and grow more trees. Students can ask multiple, customized what-if questions and understand why the system reacts as it does.
This video illustrates how atmospheric particles, or aerosols (such as black carbon, sulfates, dust, fog), can affect the energy balance of Earth regionally, and the implications for surface temperature warming and cooling.
This video addresses two ways in which black carbon contributes to global warming - when in the atmosphere, it absorbs sunlight and generates heat, warming the air; when deposited on snow and ice, it changes the albedo of the surface. The video is effective in communicating about a problem frequently underrepresented in discussions of climate change and also public health.
Students use real satellite data to determine 1) where the greatest concentrations of aerosols are located during the course of a year in the tropical Atlantic region and 2) their source of origin. This is an inquiry-style lesson where students pull real aerosol data and attempt to identify trends among data sets.
This image depicts a representative subset of the atmospheric processes related to aerosol lifecycles, cloud lifecycles, and aerosol-cloud-precipitation interactions that must be understood to improve future climate predictions.