NEO

Team Members: Brooke Carter, David Herring, Jeff Lockwood, Holli Riebeek, and Kevin Ward.

Meeting Room:

Pre-meeting Sharing Space

Please introduce yourself to your team members. Give a brief description of your role in facilitating the use of data in education. You can also post links, files, or images.

Add Pre-Meeting Notes here:

Session 1 - Thursday Morning
Meet your team members. Learn about the data, tools, and expertise represented on your team. Review DataSheet(s) and explore data and tools.

Team members meet each other and share their experiences and viewpoints on using data in education. Review and discuss DataSheet(s) begun by the data representative(s) for your team. Explore datasets and tools and consider how the expertise on the team can complement them. If you haven't already done so, narrow down the range of datasets the team is considering using to a manageable number.

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Target audience: Grades 8-12

Datasets: Global Land Surface Temperatures (LST) and Sea Surface Temperatures (SST)

Tools: NASA Earth Observations, ICE tool, Excel

Phenomenon: Global trends - Have educators and students walk through an example using LST and SST to examine what is happening to the global surface temperature over time.

Progression of lesson: Multiple days (1 week).
Day 1: seasonal trends; Day 2: year-to-year trends; Days 3-5: Analysis of year to year data

Possible extensions: Have teachers and students examine a local area (a particular state); have students do a more in depth analysis of the data (linear regression or statistical analysis); analysis of global trends of other datasets and examine them for correlations to the global temperatures data set (precipitation, cloud cover, outgoing longwave radiation, etc); make predictions about future temperature trends and compare their predictions to a model data for future temperature trends (in which case students would be given additional background materials to help them make their predictions OR they would extend the slope of their trend line to the future, and compare their future predictions to the model);

We would like to answer our own question: Do the data show an increase in average global temperatures over time?

It could be possible to use Hanson's dataset as a comparison for this activity. Students would then do a comparison of the skin surface temperatures from the years 2000-2005 to the global surface temperatures from those same years. Hypothesis: The magnitude of change in air temperature of the Hanson data should equal the magnitude of change in global surface temperature data.

Session 2 - Thursday Afternoon
Brainstorm data-use storylines

Brainstorm a set of possible storylines for valid investigations of the dataset(s) you have selected. Come up with at least one compelling scenario that will give users a reason to work through the technological steps necessary to perform an analysis of the data.

The Activity Outline Guide (Microsoft Word 42kB Apr9 08) provides an outline for the minimum information needed for the team's activity outline.

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What is the relevance of this case study?
It is important to monitor and know about the changes in the Earth's temperature. The IPCC has recognized that there is a definite increase in the temperature of the Earth over time due to an increase in greenhouse gases. The IPCC has also recognized that it is highly likely (90% confidence) that the increase in temperatures is a result of anthropogenic introduced CO2. This dataset gives us a new way to analyze the change in global temperatures over time. Once students have figured out how to analyze and graph the data, they can do some comparisons with past data and future data predictions. Does the satellite record correspond to the dataset that the scientists are using? Students are given an opportunity to analyze the data for themselves.

http://earthobservatory.nasa.gov/Study/GlobalWarmingQandA/
http://earthobservatory.nasa.gov/Library/GlobalWarmingUpdate/
http://earthobservatory.nasa.gov/Study/GISSTemperature/
http://earthobservatory.nasa.gov/Study/Paleoclimatology/paleoclimatology_intro.html
http://www.gfdl.noaa.gov/products/vis/gallery/

Sessions 3 and 4 - Friday Morning
Select a data-use scenario and perform a proof-of-concept check

Use the complementary expertise on the team to check that the task you are envisioning can actually be completed in an educational setting. Identify a target grade level for the activity and choose a working title.

Please limit the scope of the activity to tasks that can be accomplished by accessing existing data and tools. Discuss and agree upon the content limits of the activity as well. Consider that the major goal of these activities is to develop user familiarity with the data and tools.

Add Session 3 and 4 Notes here:

New scenario: Comparing Land Surface Temperatures (Night) and NDVI during the growing season in the arctic regions of the world.

Case study: Scientist X recognizes the relationship between night surface temperature and productivity of a particular ecosystem in Alaska.

Data Analysis Section:
Step 1: Use one year to pin down the relationship between the temperature and the growing season.
1a. Use NEO to get an average for LST[Night] for each month in 2007.
1b. Use NEO to get an average NDVI for each month in 2007.
1c. Graph the monthly LST and NDVI data in excel.
1d. Analyze the data for correlating relationships.
1e. Define in which month the growing season begins using the 2007 NDVI data.

Step 2: Examine both data sets for the beginning month of the growing season for the years 2000 - 2007, examine the data for trends between LST - Night and Leaf index.

2a. Plot the LST and NDVI data for the years 2000 - 2007 for the beginning month of the growing season.
2b. Examine the data for trends. Does the NDVI behave the same way as the LST?


Relevant questions: Are the monthly temperatures increasing over time? Do the NDVI data reflect changes you observe in the LST data?

Based on these data, make predictions about the LST and NDVI for one month prior to what you determined to be the beginning of the growing season? Plot those data and compare your predictions to the data.

What effect is this going to have on the local ecosystem?

Extensions: Choose another area in the world and examine the same datasets.

Relevant information:
Arctic climate impact assessment: http://www.acia.uaf.edu
http://earthobservatory.nasa.gov/Study/BorealThreshold/
http://earthobservatory.nasa.gov/Study/BOREASIntro/
http://earthobservatory.nasa.gov/Study/BorealMigration/
http://earthobservatory.nasa.gov/Study/GlobalGarden/index.html
http://cybele.bu.edu/greeningearth/ge.html

http://earthobservatory.nasa.gov/Library/MeasuringVegetation/

Sessions 5 and 6 - Friday Afternoon
Develop your case study storyline and outline the procedures for data access and analysis Case Study Development

Record ideas, bullet points, or actual text that will become part of the case study to introduce users to the issues and concepts of the activity. Gather links for appropriate images, diagrams, and background text.

Data Access and Analysis Procedures

Record the name and URL of all datasets and access/analysis software tools to be used. List the major tasks users will complete, then perform a deliberate walk-through of each task to capture the full sequence of procedures. Give special attention to the most difficult or least intuitive steps, and note points in the sequence where additional information will be helpful.

Add Session 5 and 6 Notes here:

References:
http://www.cababstractsplus.org/google/abstract.asp?AcNo=20043215599
http://www.cosis.net/abstracts/EGU2008/11902/EGU2008-A-11902.pdf?PHPSESSID=
http://www.arctic.noaa.gov/reportcard/essay_vanbogaert.html


NEO:
http://neo.sci.gsfc.nasa.gov

Activity Outline Guide
2008 AccessData Workshop

Team Name�"NEO

Names and affiliations of Team Members

âÃÑ¢ David Herring (NOAA Climate Change Office)
âÃÑ¢ Brooke Carter (NASA GSFC/SSAI)
âÃÑ¢ Holli Reebeek (SSAI)
âÃÑ¢ Kevin Ward (NASA GSFC/SSAI)
âÃÑ¢ Jeff Lockwood (TERC)

Working title for activity

"Investigating Temperature Change and Plant Growth in the Arctic"

Name(s) and URL(s) of dataset(s) used

http://neo.sci.gsfc.nasa.gov/Search.html

Name(s) and URL(s) of access/analysis software tool(s) used

http://neo.sci.gsfc.nasa.gov/Search.html

Target educational level for the activity (restrict to as few levels as possible)

Grades 9-12

Case Study�" A team of more than 300 leading Arctic researchers, indigenous
representatives and other experts from fifteen nations have completed its work on comprehensive report on the state of climate change in the Arctic region. The report, entitled the Arctic Climate Impact Assessment (ACIA) distilled and synthesized available scientific information, traditional knowledge, and indigenous perceptions in order to examine how climate and ultraviolet radiation have changed in the Arctic, how they are projected to change
in the future, and what the consequences of these changes will be for the Arctic and
the world.

The authors of the overview document of the ACIA identified the following ten key
findings:

1. The Arctic climate is now warming rapidly and much larger changes are
projected.
2. Arctic warming and its consequences have worldwide implications.
3. Arctic vegetation zones are projected to shift, bringing wide-ranging impacts.
4. Animal species' diversity, ranges, and distribution will change.
5. Many coastal communities and facilities face increasing exposure to storms.
6. Reduced sea ice is very likely to increase marine transport and access to resources.
7. Thawing ground will disrupt transportation, buildings, and other infrastructure.
8. Indigenous communities are facing major economic and cultural impacts.
9. Elevated ultraviolet radiation levels will affect people, plants, and animals.
10. Multiple influences interact to cause impacts to people and ecosystems.

Such findings, as well as the underlying scientific assessment, will help inform
governments as they implement and consider future policies on global climate change. It remains imperative to continue monitoring climate parameters to investigate any future changes and trends.

In this Toolbook chapter, students will investigate temperature and the degree of vegetative growth has changed over a period of 7 years in an area of Siberian tundra. How has the temperature change in this area affected the amount and vegetative growth and the timing of the growing season? What might the impact of these affects be on the biodiversity of the region?

Data Access and Analysis Procedures

Data Access

1. NEO Web site access leads users to data files. The vegetative index (NDVI) and the Land surface temperature (night) (LSTN) data files are used for 2000-07. Software is on the site and is used to compute monthly averages of both parameters.

Data Analysis

1. Use NEO to get an average for LSTN and NDVI for each month in 2007. Graph data in Excel. Use the graphs of this data to pin down the relationship between the temperature and the growing season.

2. Examine both data sets to determine the beginning month of the growing season. Plot the LST and NDVI data for the years 2000 - 2007 for the beginning month of the growing season.

3. Examine the data for trends. Does the NDVI behave the same way as the LST?

Relevant questions: Are the monthly temperatures increasing over time? Do the NDVI data reflect changes you observe in the LST data?

4. Based on these data, make predictions about the LST and NDVI for one month prior to what you determined to be the beginning of the growing season. Plot those data and compare your predictions to the data.

Relevant Questions: Has the beginning of the growing season changed over a 7-year time span? What effect is this going to have on the local ecosystem?

5. Extension: Choose another area in the world (Canadian shield area, Antarctica) and examine the same datasets.

Other investigations:
- Investigate the changes in the 8-day average LSTN and 16-day average NDVI data.
- Select two other areas of the world and compare those areas to Siberia to investigate the limits of vegetation growth. Helpful datasets for this investigation include rainfall and insulation along with LSTN and NDVI.
- Using the topography, NDVI, and LSTN datasets, choose a regional area to investigate the role topography has on vegetation growth.
- Using the Chlorophyll, Sea Surface Temperature, and Bathymetry datasets, investigate the relationship between these three variables with respect to algal blooms.

Additional information for teachers

âÃÑ¢ Arctic climate impact assessment: http://www.acia.uaf.edu
âÃÑ¢ Earth Observatory Activity: Limits to Plant Growth (http://earthobservatory.nasa.gov/Laboratory/ICE/panama/panama_ex3.ph)

âÃÑ¢ http://earthobservatory.nasa.gov/Study/BorealThreshold/

âÃÑ¢ http://earthobservatory.nasa.gov/Study/BOREASIntro/

âÃÑ¢ http://earthobservatory.nasa.gov/Study/BorealMigration/

âÃÑ¢ http://earthobservatory.nasa.gov/Study/GlobalGarden/index.html

âÃÑ¢ http://cybele.bu.edu/greeningearth/ge.html

âÃÑ¢ http://earthobservatory.nasa.gov/Library/MeasuringVegetation/

âÃÑ¢Reference paper: http://www.cababstractsplus.org/google/abstract.asp?AcNo=20043215599

âÃÑ¢ Reference paper: http://www.cosis.net/abstracts/EGU2008/11902/EGU2008-A-11902.pdf?PHPSESSID=

Session 7 - Saturday Morning
Enhance your step-by-step procedures by adding "About" sections that provide extra information; List several ideas for "Going Further" with the data or tools

Fill in any gaps in your activity outline and add sections that can help users make meaning of the data. Suggest several ideas for the "Going Further" section that challenge users to work with the data and/or tools in other investigations. These suggestions provide launching points for scientific inquiry which is facilitated by the skills learned in the activity.

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Session 8 - Final Team Breakout
Finalize your Activity outline and DataSheet, Generate PowerPoint slides for the report out session, Upload all resources to this page

Create a 2- or 3-slide ppt file for the report out session.

• Slide 1: Team name, names of team members, and a brief phrase to describe each individual's contribution
• Slide 2: Working title for your activity, names of dataset(s) and tool(s) utilized
• Slide 3: Your choice of something to illustrate your team's vision of the completed activity

Attach the file plus any other documents produced by the team to this page. Include final versions of the team's DataSheet.

Add Session 8 Notes here:

first draft of case study a 30kB Microsoft Word file uploaded May1 08 by Jeff Lockwood
 
NEO activity outline a 55kB Microsoft Word file uploaded May2 08 by Jeff Lockwood

Data Sheet for NEO Vegetation Index a 90kB Microsoft Word file uploaded May3 08 by Holli Riebeek