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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?