In addition to its primary mission of observing space weather, the Deep Space Climate Observatory (DSCOVR) satellite is carrying two instruments that are important to climate science: the NISTAR radiometer and the EPIC camera.
Like a prehistoric fly trapped in amber during dinosaurs' days, airborne relics of Earth's earlier climate can end up trapped in glacial ice for eons. How do climate scientists turn those tiny relics into a story about Earth's ancient climate?
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.
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.
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.
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.