This module contains five activities, in increasing complexity, that focus on understanding how to interpret and manipulate sea level data, using real data from NOAA.

Students first need to understand how to access and interpret sea surface height and tide data. To understand how to interpret these data, students will review and practice computing mean values. Along the way, they will learn how different factors, such as storms, affect tide levels and how to measure them. The goal is for students to become experienced with these kinds of data and the tools for accessing them so that, by the end of the module, they can continue to explore data sets driven by their own inquiry.

In this activity, students use the GLOBE Student Data Archive and visualizations to explore changes in regional and seasonal temperature patterns.

In this activity, students review techniques used by scientists as they analyze a 50-year temperature time series dataset. The exercise helps students understand that data typically has considerable variability from year to year and to predict trends, one needs to consider long-term data.

This lesson explores El NiÃo by looking at sea surface temperature, sea surface height, and wind vectors in order to seek out any correlations there may be among these three variables using the My NASA Data Live Access Server. The lesson guides the students through data representing the strong El NiÃo from 1997 to 1998. In this way, students will model the methods of researchers who bring their expertise to study integrated science questions.

In this activity, students work in groups, plotting carbon dioxide concentrations over time on overheads and estimating the rate of change over five years. Stacked together, the overheads for the whole class show an increase on carbon dioxide over five years and annual variation driven by photosynthesis. This exercise enables students to practice basic quantitative skills and understand how important sampling intervals can be when studying changes over time. A goal is to see how small sample size may give incomplete picture of data.

In this lesson, students examine and interpret varied observational datasets and are asked to determine whether the data supports or does not support the statement: climate change is occurring in Colorado.

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 reconstruct past climates using lake varves as a proxy to interpret long-term climate patterns. Students use data from sediment cores to understand annual sediment deposition and how it relates to weather and climate patterns.

In this activity, students investigate how scientists monitor changes in Earth's glaciers, ice caps, and ice sheets. The activity is linked to 2009 PBS Nova program entitled Extreme Ice.

In this activity, students research various topics about ocean health, e.g. overfishing, habitat destruction, invasive species, climate change, pollution, and ocean acidification. An optional extension activity has them creating an aquatic biosphere in a bottle experiment in which they can manipulate variables.

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