These data are excerpted from IPCC Scenario A2, showing expected temperature and precipitation changes in
different regions on our planet. NOTE:
California can expect a small increase in
rainfall and greater than average warming
with a mean increase of about 3 oC.
Europe is projected to experience both
higher temperatures and less precipitation.
Polar areas are the most affected, with
much warmer winter and summer
temperatures and elevated precipitation.
Sea levels are expected to rise
significantly with increased warming,
perhaps as much as 25 inches over the
next century.
Human populations in low-lying coastal
areas will be the most heavily affected by
both severe tidal flooding and
disappearance of coastal land.
Worldwide, the number of individuals at
rish for flooding events is expected to
double by the year 2050.
Asian countries are expected to have the
greatest numbers of exposed individuals.
Users Guide to Climatology Data in Google Earth
General Information
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Data sets presented in Google Earth are in “layers”.
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Each data set or “layer” can be seen alone or superimposed on another layer.
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Some layers can be superimposed on others, but some types of data obscure other layers.
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For best results, turn on only those layers you need to collect information. When finished, turn
one layer off before viewing another.
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Data layers that you will use include:
5 weather stations
California Study Area boundary
current land cover
current temperature and precipitation
2050 projected precipitation
2099 projected precipitation
2050 projected temperature
2099 projected temperature
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When you open Google earth, the California Study Area is outlined and 5 weather stations can
be seen on the map.
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Zoom in until this area fills your screen. The “zoom in/out” feature of Google Earth is in the
upper right corner of the map and appears when you scroll over that area.
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Note that the current tolerance ranges for all the vegetation types is found on page 1 of your lab
report. You will need to transfer this information to Data Tables 1 and 2.
To find the current predominant vegetation types:
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Open the file titled “actual data showing recent predominating types of land cover”.
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Click on the “legend” box and then the box for each vegetation type. You can click on each one
individually and visualize them as they appear.
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Fill in the information about the 3 most common types of vegetation near each of the weather
stations. Transfer this information to Data Tables 1 and 2.
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Close the legend and vegetation data layers.
To find current temperatures and precipitation:
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Important note: There are many different precipitation and temperature statistics, so be careful
to select the correct data. The biologically important values are: annual precipitation,
average January daily low (coldest average nighttime temperature, indicative of whether plants
will freeze) and average July daily high (average warmest days, indicative of whether plants
will experience photorespiration, wilting or sunburn effects)
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Click on the button for one of the weather stations.
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Record the annual precipitation (AnnPrecip) in Data Table 1.
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Record the average January daily low temperature (JanAvgLow) and average July daily high
temperature (JulAvgHigh), placing the information in Data Table 2.
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Repeat for other weather stations.
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Note the units: inches/year and oF.
To find Projected 2050 Precipitation values:
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Click the “Precipitation Data Projected Values 2050" button.
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Click the “fixed ranges box, then click open the “legend” and “Annual Precipitation_2050"
layers.
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Record the precipitation range for each weather station in Data Table 1.
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Turn off the precipitation legend and data by unclicking the boxes.
To find Projected 2050 temperature values:
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Click on the “Temperature Data Projected Values 2050" button.
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Click both the “fixed ranges” and “July average daily highest temperature” box, NOT the “July
Highest temperature” box.
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Click on the “legend” box and boxes for each temperature range shown, displaying all at once.
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Record the temperatures for each weather station in Data Table 2.
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Turn off the temperature data layers by un-clicking the boxes.