This is a sequence of 5 classroom activities focusing on the El NiÃo climate variability. The activities increase in complexity and student-directedness. The focus of the activities is on accessing and manipulating real data to help students understand El NiÃo as an interaction of Earth systems.

In this activity, students analyze data maps of sea surface temperature anomalies for a 14-year interval and create an ENSO time line in a case study format. Based on their findings, students determine the recurrence interval of the ENSO system.

In this activity, students are introduced to tree rings by examining a cross section of a tree, also known as a 'tree cookie.' They discover how tree age can be determined by studying the rings and how ring thickness can be used to deduce times of optimal growing conditions. Next, they investigate simulated tree rings applying the scientific method to explore how climatic conditions varied over time.

In this activity, students work with climate data from the tropical Pacific Ocean to understand how sea-surface temperature and atmospheric pressure affect precipitation in the tropical Pacific in a case study format.

This Earth Exploration Toolbook chapter is a detailed computer-based exploration in which students learn how various climatic conditions impact the formations of sediment layers on the ocean floor. They analyze sediment core data from the Ross Ice Shelf in Antarctica for evidence of climate changes over time. In addition, they interact with various tools and animations throughout the activity, in particular the Paleontological Stratigraphic Interval Construction and Analysis Tool (PSICAT) that is used to construct a climate change model of a sediment core from core images.

In this activity, students graph and analyze methane data, extracted from an ice core, to examine how atmospheric methane has changed over the past 109,000 years in a case study format. Calculating the rate of change of modern methane concentrations, they compare the radiative forcing of methane and carbon dioxide and make predictions about the future, based on what they have learned from the data and man's role in that future.