Download Name - HannibalPhysics

Name ______________________
Investigating Climate Change in 2050 & 2099 in CA & NY
Introduction: Climate and land cover data has been collected for many decades in the United States
and provides a baseline to compare future data with to look for changes in levels of precipitation,
temperature, and land cover. NASA and other agencies are constantly monitoring many variables
associated with Climate Change. Satellite image analysis can distinguish types and health of vegetation
based on how light interacts with the plant materials.
Scientists have proposed a number of different models of how the climate may change in the future.
Each model is based in part on how people choose to use energy resources, pursue economic
development, and how population changes across the world. Each of the models is referred to as a
scenario and each point to change that impacts the environment, but to differing degrees. Read more
about the scenarios at http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf (pages 9 &10).
The data represented by this Google Earth model show changes in precipitation and temperature
predicted for the years 2050 and 2099 by the most probable IPCC scenario (A2) for the future. By
studying the zones of temperature and precipitation that current types of vegetation are observed to be
well established in, predictions can be made for shifts in the zones modeled by the scenarios.
Understanding the impacts of climate change on vegetation helps predict the impacts on local, regional,
and much larger scale ecosystems.
Driving questions: 1.) How will the modeled 2050 and 2099 changes in precipitation and temperature
change the locations and extent of the land cover vegetation zones in the future? 2.) How might the
changes in California and New York impact agriculture? 3.) How do the projected impacts of climate
change differ between California and New York?
California:
Open STORE Data, double click
to launch
and
Part One: Explore the Terrain
Google Earth allows users to draw a terrain path across an area and see the profile with numeric
elevation data. A terrain path through the five CA weather stations is shown on the map. Highlight the
path in the contents list at the left, right click on the highlighted name, and choose Show Elevation
Profile. A profile window will appear below the map.
Determine the elevations of the five weather stations using the Elevation Profile tool. Record data in
Table A.
Data Table A
Weather Station
Name
San Jose
Mount
Hamilton
Elevation (ft)
January Lowest
Temp (F)
July Highest
Temp (F)
Annual Average
Temp (F)
Avg. Annual
Precipitation (in)
Predominating
Type of Land
Cover
Part Two:
Explore Temperature and Precipitation Layers





January Lowest Temperature
July Highest Temperature
Annual Average Temperature
Annual Average Precipitation
Predominant Type of Land Cover
Modesto
Sonora
Twin Lakes
Toggle layers on and off using the check boxes.
Expand/collapse layer info using + and - boxes
Part Three:
Exploring and Characterizing Land Cover Zone Attributes
Using the data available for CURRENT land cover areas, determine the ranges of temperature and
precipitation that characterize the zones. Record your observations in Data Table B below.
Land Cover
Type
Deciduous
Forest
Shrub Scrub
Mixed Forest
Grassland
Herbaceous
January Avg
Daily Lowest
Temp (F)
July Avg Daily
Highest Temp
(F)
Average Annual
Precipitation (in)
Elevation Lowend Range (ft)
Elevation Highend Range (ft)
Evergreen
Forest
Cultivated
Crops
Emergent
Herbaceous
Wetlands
Woody
Wetlands
1. Looking at the cultivated crop zone within the study area, what appears to be the range:
a) High, low, and average of temperatures?
b) Range of average annual precipitation?
2. Looking at the lower boundary edges of the evergreen zone, what general range of maximum
temperatures occurs at the lower boundary? Does precipitation have any relationship to the boundary
location?
3. Looking at the CURRENT predominant land cover types, what types are NOT observed within the CA
study area? Explain why.
Part Four:
Exploring California’s future in 2050 and 2099
Use the projected data to characterize the extent of climate variable change within the study area.
Organize the data in the data tables below.
 CAUTION!
The “single values” data sets are HUGE and may be rather challenging to work with…
Data Table C: 2050 Projections
Weather Station
Mount
San Jose
Name
Hamilton
Elevation (ft)
January Average
Temp (F)
July Average
Temp (F)
July Highest
Temp (F)
Shifted Ranges
Avg. Annual
Precipitation (in)
Modesto
Sonora
Twin Lakes
Change between
current and the
year 2050 July
average
temperature
Data Table D: 2099 Projections
Weather Station
Mount
San Jose
Name
Hamilton
Modesto
Sonora
Twin Lakes
Elevation (ft)
January Average
Temp (F)
July Average
Temp (F)
July Highest
Temp (F)
Shifted Ranges
Avg. Annual
Precipitation (in)
Change between
current and the
year 2099 July
average
temperature
Part Four Continued:
Concept Web or Graphic Organizer
Identify the key concepts that have a connection to the
”big picture” of climate change. From your key concepts,
connect related ideas, impacts, and other aspects that you
know about to construct a mind web or graphic organizer to
help you better understand relationships and connections.
Use any style of web or graphic organizer that you like, but
make sure that your ideas consider everything you believe
connects to climate change, NOT just what the maps in this
lesson have revealed.
Climate
Change
New York:
Open STORE Data, double click
NY
4
3to launch
and
New York
Part One: Explore the Terrain
Google Earth allows users to draw a terrain path across an area and see the profile with numeric
elevation data. You will construct a terrain path through the five NY weather stations shown on the map.
 Click on the path icon on the top tool bar
 Enter the path name in the “untitled” field at the top of
the pop-up menu.
*IMPORTANT* DRAW the path before closing the menu!
 Move your cursor to the shore of Lake Erie just west of
Buffalo and click once. The click once on each weather
station to make a profile path. After the last station click
OK on the pop-up menu.
 Highlight the path in the contents list at the left, right click on
the highlighted name, and choose Show Elevation Profile. A profile window will appear below the
map.
Determine the elevations of the weather stations using the Elevation Profile tool. Record data in Table E.
Data Table E:
Weather Station
Name
Buffalo
Warsaw
Avon
Geneva
Tully
Elevation (ft)
January Lowest
Temp (F)
July Highest
Temp (F)
Annual Average
Temp (F)
Avg. Annual
Precipitation (in)
Predominating
Type(s) of Land
Cover
Part Two:
Explore Temperature and Precipitation Layers
Toggle layers on and off using the check boxes.
 January Lowest Temperature
 July Highest Temperature
Expand/collapse layer info using + and - boxes
 Annual Average Temperature
 Annual Average Precipitation
 Predominant Type of Land Cover
Part Three:
Exploring and Characterizing Land Cover Location Attributes
Using the data available for CURRENT land cover areas, determine the ranges of temperature and
precipitation that characterize where the type of land cover grows. Record your observations in Data
Table F below. HINT- Toggle each land cover type on and off individually to see where they grow!
Data Table F
January Avg July Avg Daily Average Annual
Elevation Low- Elevation HighLand Cover
Daily Lowest Highest Temp Precipitation (in)
end Range (ft) end Range (ft)
Type
Temp (F)
(F)
Deciduous
Forest
Shrub Scrub
Mixed Forest
Grassland
Herbaceous
Evergreen
Forest
Cultivated
Crops
Emergent
Herbaceous
Wetlands
Woody
Wetlands
Hay Pasture
1. Looking at the cultivated crop zone within the study area, what appears to be the
range:
a) High, low, and average of temperatures?
b) Range of average annual precipitation?
2. Looking at the various land cover types in NY, are there any distinct zones for a given
type of vegetation? Explain
3. Why might the evergreens have the locations they do in New York?
4. What land cover types would you expect to find in the Adirondacks? Why?
Part Four:
Exploring New York’s future in 2050 and 2099
Use the projected data to characterize the extent of climate variable change within the study area.
Organize the data in the data tables below.
 CAUTION!
The “single values” data sets are HUGE and may be rather challenging to work with…
Data Table G: 2050 Projections
Weather Station
Buffalo
Warsaw
Name
Elevation (ft)
January Average
Temp (F)
July Average
Temp (F)
July Highest
Temp (F)
Avon
Geneva
Tully
Shifted Ranges
Avg. Annual
Precipitation (in)
Change between
current and the
year 2050 July
average
temperature
Data Table H: 2099 Projections
Weather Station
Buffalo
Warsaw
Name
Avon
Geneva
Tully
Elevation (ft)
January Average
Temp (F)
July Average
Temp (F)
July Highest
Temp (F)
Shifted Ranges
Avg. Annual
Precipitation (in)
Change between
current and the
year 2099 July
average
temperature
Part Four Continued:
Concept Web or Graphic Organizer
Revisit your graphic organizer and add or edit to include
any new ideas or understandings about climate change
and relationships related to it.
Conclusion:
Putting It All Together:
1.) How will the modeled 2050 and 2099 changes in precipitation and temperature change the locations
and extent of the land cover vegetation zones in the future?
California:
New York:
2.) How might the changes in California and New York impact agriculture?
3.) How do the projected impacts of climate change differ between California and New York?
4.) Describe the difference that elevation change may make in terms of vegetation zone shift.
5.) What do you want or need to know more about to better understand the impacts of climate change?