1 / 25

ATMS 451: Instruments and Observations

ATMS 451: Instruments and Observations. MWF 11:30 AM – 12:20 PM 310c ATG TuTh 10:30 AM – 12:20 PM 108 (be prepared for changes). Instructors. Joel Thornton Assoc. Professor, Atmospheric Sciences 508 ATG thornton@atmos.uw.edu Robert Wood Assoc. Professor, Atmospheric Sciences 718 ATG

rpolk
Download Presentation

ATMS 451: Instruments and Observations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ATMS 451: Instruments and Observations MWF 11:30 AM – 12:20 PM 310c ATG TuTh 10:30 AM – 12:20 PM 108 (be prepared for changes)

  2. Instructors Joel Thornton Assoc. Professor, Atmospheric Sciences 508 ATG thornton@atmos.uw.edu Robert Wood Assoc. Professor, Atmospheric Sciences 718 ATG robwood@atmos.uw.edu

  3. Course Materials and Logistics • No required textbook (I can suggest some) • Course materials on website http://www.atmos.washington.edu/~robwood/teaching/451/ • Buy a laboratory notebook from UBS • Form groups of 3-4 by Wednesday for lab work • Determine if you can host a weather station

  4. Purpose of this Course • Enable you to appreciate the relevance of good, quantitative observational data • Allow you to experience how such information is obtained, analyzed, and expressedin scientific and technical communications

  5. Topics and Related Activities 1. Analyzing and Quantifying Measurement Quality 2. Practicalities of Making Measurements 3. Concepts and Realities of Common Sensors 4. Scientific Communication: Report Writing

  6. Grading • 75% of final grade based on laboratory/analysis work • 60% based on 2 formal written reports (thermometry and weather station) • 30% on analysis “worksheets” • 10% on quality of laboratory notebook • 25% on ~ weekly quizzes based on lecture material • NOTE: You are expected to have ~7 weeks of data for the weather stations. Every week of data that is missing is a 10% deduction from your weather report grade.

  7. Relevance to Past and Future Work • Basic Science: • a connected body of agreed upon truths based on OBSERVABLE facts, classified into laws (theories) Observation ?Uncertainty? Hypothesis Experimental Test (measure) ?Uncertainty?

  8. Gravitational Lensing – Einstein Rings D.E.D 1919 – measured bend angle by sun: 2 +/- 0.3”

  9. Relevance to Past and Future Work 2. Applied Science/Engineering

  10. Price of Gold A treasure hunter is hawking a 1 kg royal crown she has found, claiming it is solid gold. Your assistant measures its density to be 15 +/- 1.5 g/cm3. The density of pure gold is 15.5 g/cm3. The price of gold is currently $51,500 per kg. What do you do?

  11. Measurement Uncertainty Issues • For multiple measurements of the same quantity, what exactly is the “best estimate” of the true value? • X x  x implies a range within which we are “confident ” the true value exists • How do we determine the value of x?

  12. Avoid Significant (Figure) Embarrassment After a series of measurements and calculations you determine the acceleration due to gravity on Earth. The answer on your calculator/computer is: g = 9.82174 m/s2, and the uncertainty estimate is 0.02847 m/s2. How do you report your result?

  13. Define what is meant by “Measurement”

  14. Measurement • determination of size, amount, or degree of some object or property by comparison to a standard unit

  15. Measurements are meant to be compared • Comparisons (two measurements or measurement vs predictions) come down to a range over which we are “confident” about our conclusions • Often, measurements are just the starting point, and some property calculated from the measurements is the point of comparison: must understand how “confidence” in measurements propagate through the calculations • It is as important to know how the estimate of confidence in the measurement is made, as it is to be given a numerical value: give clear descriptions of your approach to uncertainty analysis

  16. Define what is meant by “Uncertainty”

  17. Uncertainty • An indefiniteness in measurements of a system property, and any quantities derived from them, due to sensor limitations, problems of definition, and natural fluctuations due to the system itself. • All measurements carry uncertainty, often called “errors” – NOT a mistake, cannot be avoided! • Error = Uncertainty (for us) – cannot be known exactly, only estimated, must explain basis of estimation

  18. Sources of Measurement Uncertainty Sampling Analytical

  19. Common Types and Sources of Measurement Uncertainty

  20. Define “precision” and its relationship to “accuracy”

  21. Accuracy and Precision

  22. Distribution of N Measurements and of Means x = x/10 N = 10;blue N = 10 performed many times, distribution of means; black x

  23. Normal Error Integral 95.4% w/in 2 68% w/in 1 P(t) t

  24. Normal vs Student’s t-distribution

  25. Question Two different weathernuts living in adjacent towns (town A and B) measure the air temperature in their respective town during a brief period. Both want to claim their town was colder than the other during this time. Does either one have a valid claim? Town A T Measurements: 10.2, 11.5, 13.4, 15.1, 12.2 oC Town B T Measurements: 9.8, 10.2, 12.8, 14.6, 11.7 oC The uncertainty in any one of weathernut A’s or weathernut B’s individual measurements = 0.5 oC.

More Related