<p> Estimating Cloud Cover(Lab #24)</p><p>Name______Date______</p><p>Purpose- The purpose of this lab is to better understand percentage of cloud cover and to take more accurate cloud cover observations.</p><p>Variables-</p><p>Data and Observations You will create a data chart that looks like this Per 3A</p><p>Name of Estimated Classification Right Wrong Classmate Percent Bobby Laura Jackie Nicole Bryce Kaylee Jozie Jay Kaila Sergio Taylor Stephanie Jacob</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Bobby 10 0 11 0 Laura 50 6 2 3 Jackie 20 0 9 2 Nicole 20 0 3 8 Bryce 30 1 3 7 Kaylee 30 0 6 5 Josie 30 1 6 4 Jay 20 0 6 5 Kaila 50 0 6 5 Sergio 20 4 5 2 Taylor 50 4 4 3 Stephanie 30 3 5 3 Jacob 60 6 3 2</p><p>Name of Correct Class too low Class Class Classmate Class Correct too High Bobby Isolated 0 11 0 Laura Broken Jackie Isolated Nicole Isolated Bryce Scattered Kaylee Scattered Jozie Isolated Jay Isolated Kaila Broken Sergio Isolated Taylor Broken Stephanie Scattered Jacob Broken You will create a data chart that looks like this Per 3B</p><p>Name of Estimated Classification Right Wrong Classmate Percent Alexis Melissa Lindsay Chris Ayana Carl Harold Jorge Brandon Amir Holly</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Alexis 20 2 1 5 Melissa 40 4 1 3 Lindsay Chris 20 5 3 0 Ayana 40 2 4 2 Carl 40 3 2 2 Harold 30 4 2 2 Jorge 10 0 8 0 Brandon 20 0 8 0 Amir 50 3 5 0 Holly 30 7 1 0</p><p>Name of Correct Class too low Class Class Classmate Class correct too low Alexis Melissa Lindsay Chris Ayana Carl Harold Jorge Brandon Amir Holly You will create a data chart that looks like this Per 8/9A</p><p>Name of Estimated Classification Right Wrong Classmate Percent Joe Evan Kristen Alexis Raina J.P Emily Grant Chelsea Elmanda Dan Lindsay Mike</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Joe 40 3 3 6 Evan 20 6 5 1 Kristen 50 8 2 2 Alexis 50 4 3 5 Raina 10 0 1 11 J.P 20 4 5 3 Emily 40 6 3 3 Grant 20 3 7 2 Chelsea 40 7 2 3 Elmanda 20 1 8 3 Dan 40 7 2 3 Lindsay 20 5 6 1 Mike 10 0 12 0</p><p>Name of Correct Class too low Class Class to Classmate Class Correct low Joe Evan Kristen Alexis Raina J.P Emily Grant Chelsea Elmanda Dan Lindsay Mike You will create a data chart that looks like this Per 8/9B</p><p>Name of Estimated Classification Right Wrong Classmate Percent Matt B Kristen Taylor Kim Marc Jake Matt P Jessica Nicole Ron Steve Ethan Sierra</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Matt B Kristen Taylor Kim Marc Jake Matt P Jessica Nicole Ron Steve Ethan Sierra</p><p>Name of Correct Class too low Class Class Classmate Class correct too high Matt B Kristen Taylor Kim Marc Jake Matt P Jessica Nicole Ron Steve Ethan Sierra You will create a data chart that looks like this Per 12A</p><p>Name of Estimated Classification Right Wrong Classmate Percent Brandi Danielle Kyle Ambrie Jenn Lloyd Julie Ashley Mary Wes Rashaad Roxayne</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Brandi 60 1 2 6 Danielle 50 3 2 4 Kyle 40 3 1 5 Ambrie 30 1 5 3 Jenn 60 4 4 1 Lloyd 50 8 1 0 Julie 60 6 1 2 Ashley 20 6 3 0 Mary 50 6 2 1 Wes 40 4 5 0 Rashaad 20 4 5 0 Roxayne 60 4 2 3</p><p>Name of Correct Class too low Class Class to Classmate Class correct high Brandi Danielle Kyle Ambrie Jenn Lloyd Julie Ashley Mary Wes Rashaad Roxayne You will create a data chart that looks like this Per 12B</p><p>Name of Estimated Classification Right Wrong Classmate Percent Autumn Alex Daniella Ben Diego Sabrina Tyler Tuesday Victor Megan Aimee Emily Cody</p><p>Percentage If Less Than If greater or equal to 10% Clear Isolated 25% Isolated Scattered 50% Scattered Broken 90% Broken Overcast Name of Actual Underestimates Correct Overestimates Classmate % Estimates Autumn 30 2 7 3 Alex 30 7 3 2 Daniella 40 2 2 8 Ben 30 8 3 1 Diego 60 5 3 4 Sabrina 40 0 0 12 Tyler 30 3 2 7 Tuesday 60 10 0 2 Victor 50 7 4 1 Megan 10 0 12 0 Aimee 50 7 2 3 Emily 50 7 4 1 Cody 40 9 3 0</p><p>Name of Correct Class too Low Class Class Classmate Class correct too high Autumn Alex Daniella Ben Diego Sabrina Tyler Tuesday Victor Megan Aimee Emily Cody Conclusion Questions</p><p>1. Where did the greatest errors occur?</p><p>2. Does the class have a tendency to overestimate or underestimate cloud cover?</p><p>3. What factors influenced the accuracy of the estimates?</p><p>4. Do you feel you have a talent for this or is something you have to learn? Explain…..</p><p>5. Where else might such spatial estimation skills be valuable?</p><p>6. Which cloud classifications were the easiest and most difficult to identify?</p><p>7. What strategies enable you to correctly estimate cloud cover?</p><p>8. What strategies might produce more accurate classifications?</p>