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1 Junhong (June) Wang New York State Mesonet Dept. of Atmospheric and Environmental Sciences University at Albany, SUNY, Albany, NY Copyright of Junhong (June) Wang

Junhong (June) Wang · 2020-01-23 · 5 Observations •Sensors •Systems •Networks Data QA &QC •Calibration •Monitoring •Correction Analysis & products •VAD •Visualization

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Page 1: Junhong (June) Wang · 2020-01-23 · 5 Observations •Sensors •Systems •Networks Data QA &QC •Calibration •Monitoring •Correction Analysis & products •VAD •Visualization

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Junhong (June) Wang

New York State MesonetDept. of Atmospheric and Environmental Sciences

University at Albany, SUNY, Albany, NY

Copyright of Junhong (June) Wang

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Basic Information

Copyright of Junhong (June) Wang

Class # AATM section (10297); AENV section (10296)

Room/Time ES B13; T Th 10:15AM – 11:35AM

Pre-reqs AMAT 113 or 119 and APHY 105 or 140 or 141 and AATM 210

Instructor Junhong (June) Wang, LC-SB32, 442-6389, [email protected]

Office hours: Tues 2:00pm – 4:00pm; also, after class or by appointment.

TA Scott Feldman, ES234, [email protected], Office hours: M&W 1-2pm

Textbooks Required:

Introduction to Error Analysis: The Study of Uncertainties in Physical

Measurements, (2nd Ed.), John R. Taylor (Required)

References:

Meteorological measurements and instrumentation, R.Giles Harrison

ISBN:9781118745809

(https://onlinelibrary.wiley.com/doi/book/10.1002/9781118745793)

Meteorological Measurement Systems, Fred V. Brock and Scott J.

Richardson

Contents Chapters 1 –7 of Introduction to Error Analysis

Selected chapters of Meteorological Measurements and Instrumentation

Other special topics, and lab & field hands-on experiments

http://www.atmos.albany.edu/daes/atmclasses/env327/ENV327syllabus_S20

20_details.pdf

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Measurement

the assignment of numbers to objects or events

level of measurement (magnitude)

Dimensions (units)

Uncertainty

(Error)

An observation is an act that results in the estimation of the value of a feature property, and involves application of a specified procedure, such as a sensor, instrument, algorithm or process chain.

Copyright of Junhong (June) Wang

What is Measurement (and its components)?

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Measurement Chain

Copyright of Junhong (June) Wang

Page 5: Junhong (June) Wang · 2020-01-23 · 5 Observations •Sensors •Systems •Networks Data QA &QC •Calibration •Monitoring •Correction Analysis & products •VAD •Visualization

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Observations

• Sensors• Systems• Networks

Data QA &QC

• Calibration

• Monitoring

• Correction

Analysis & products

• VAD

• Visualization

• Merging

Applications

• NWS

• Emergency M.

• Agriculture

• Energy

• …

Goals of NYSM

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https://youtu.be/pPgWtdgIDt0

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Objectives1. To acquire a basic understanding of the techniques used to

properly analyze and interpret measurements (i.e. Data);

2. To understand and explain the fundamental principles of instruments in atmospheric and environmental measurements.

Critical Thinking Advanced Writing

Information Literacy

Copyright of Junhong (June) Wang

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Objectives (Learning outcomes)

1. To acquire information: to describe the error analysis techniques and physical principles of instruments

2. To learn how to use information and knowledge in new situations: applicable to future work, other disciplinary and daily life.

3. To develop life long learning skills: to connect observations, data and applications together.

“Measurement is every thing”

“No measurement is perfect”

Copyright of Junhong (June) Wang

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Text Books & Reading Materials

1. Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements, (2nd Ed.), John R. Taylor

2. Meteorological measurements and instrumentation, R.Giles Harrison ISBN:9781118745809

3. Meteorological Measurement Systems, Fred V. Brock and Scott J. Richardson

4. Lectures in pdf files on class web page

5. “Guide to Meteorological Instruments and Methods of Observation” (https://library.wmo.int/doc_num.php?explnum_id=4147)

Copyright of Junhong (June) Wang

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Error analysis of measurements

1. 1/23 Introduction (L#1)

2. 1/28 Chapter1: Preliminary description of error analysis

(L#2)

3. 1/30 Chapter 2: How to report and use uncertainties (L#3,

HW#1)

4. 2/4 Chapter 3: Propagation of uncertainties (L#4, HW#2)

5. 2/6 Team project #1: Make measurements and report

(TP#1)

6. 2/11 Chapter 4: Statistical analysis of random

uncertainties (L#5)

7. 2/13 Chapter 5&6: The normal distribution & Rejection of

data (L#6 HW#3)

8. 2/18 Team Project #2 (TP#2 Data)

9. 2/20 Review & HWs (Review)

10.2/25 Mid-term (TA)

Copyright of Junhong (June) Wang

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Measurements (techniques, applications & hands-on)

Copyright of Junhong (June) Wang

1. 2/27 Overview (L#8)

2. 3/3 Pressure & Temperature & Humidity (L#9)

3. 3/5 Team project #3 (HW#4)

4. 3/10 Wind: Anemometry (L#10)

5. 3/12 Precipitation measurement (L#11 Scott Feldman)

6. 3/24 Team project #4: final research project (L#12)

7. 3/26 Clouds & radiation (L#13)

8. 3/31 Atmospheric sounding systems (#L14)

9. 4/2 Team Project/Lab #4 (Radiosonde launch)

10. 4/7 Radar meteorology (Jerry Brotzge, L#15)

11. 4/9 “Measurements for renewable energy” (Dr. Jeff Freedman???, L#16)

12. 4/14 “Water Treatment Processes” (Dr. John D. Paccione???, NYS Department

of Health L#17_1 & L#17_2)

13. 4/16 Air quality (Dr. Jim Schwab???, ASRC, L#18)

14. 4/21 Mesonet (Jerry Brotzge, L#19)

15. 4/23 Mesonet site visit

16. 4/28 Measurements & Observations for short-term weather forecasts (Scott

Feldman, L#20)

17. 4/30 Team presentation

18. 5/5 Team presentation

19. 5/6 Reading day (Research paper due)

20.5/12 Final exam (01:00-03:00pm)

https://www.albany.edu/registrar/registrar_assets/Spring_2020_Final_Examination_

Schedule.pdf )

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>88: A85-88: A-82-85: B+79-82: B76-79: B-73-76: C+70-73: C67-70: C-64-67: D+61-64: D58-61: D-<58: E

Grading: Letter grade (A-E) format

• Homework (15%)

• Mid-term exam (25%)

• Team Research Project & Presentation (15%)

• Final research paper (20%)

• Final Exam (25%)

Copyright of Junhong (June) Wang