Saturday February 1st. Click for larger version.
Week 15 4 May
Tuesday Student Presentations on Case Studies:
Sean
Mikhail
Em
Courtney
Friday 3 pm Student Presentations on Case Studies:
Sam F
Stormi
Matt
Chris
Sam T.
Sunday 11 pm: Assignment 4 report due.
Week 14: 27 April
Class evaluation site, please do so as soon as you can.
Here's the link for our class.
We will continue to work on assignment 4.
Here are the soundings for the month from the Reno National Weather Service.
You can start writing the report by discussing the 'Methods/Instruments' section.
Here's a reminder of report contents.
Thursday's Class:
Preparation:
Bring questions to class about the report and presentation.
We will look at the measured and modeled downwelling IR radiation the UNR weather station.
UNR and DRI weather station data.
We will then look at sunphotometer data.
Here's an example of how AERONET sunphotometer data is used to evaluate satellite retrievals of AOD in Asia.
We will look at how to improve the relationship between the SPS30 and BAM measurements (time average the SPS 30 number distributions, calculate volume distributions with variable contributions from each, assume a density, sum to get PM2.5, PM10).
Whiteboard notes for Thursday.
Tuesday's Class:
Preparation:
Prepare the lapse rate between the DRI and UNR weather station data, to help explain the mixing state of the atmosphere during events.
We will also look at the time series for solar and infrared radiation and temperature and dew point temperature.
We will prepare a model for the clear sky downwelling infrared radiation
and then calculate the 'cloud cover' from the difference of the measured and modeled clear sky radiation, as discussed in this paper.
UNR and DRI weather station data.
We will then look at sunphotometer data.
We will look at how to improve the relationship between the SPS30 and BAM measurements (time average the SPS 30 number distributions, calculate volume distributions with variable contributions from each, assume a density, sum to get PM2.5, PM10).
Raman spectroscopy webinar by Hamamatsu (free, May 6th).
Valley fever from dust storms now and in the future.
Aerosol devastation on species following massive meteor impacts.
Fireworks related aerosol pollution in India and estimated health impacts.
Mexico City aerosol 2009 paper.
Mexico City and Queretaro 2019 paper.
Per capita air pollution paper.
Reno winter time air pollution paper.
Our sunphotometer analysis website (air mass and Rayleigh optical depth calculator based on Perl language, here's the source code).
Sun photometer theory.
Infrared radiation model for clear skies, and calculation of cloud effect.
Role of infrared radiation on snow conditions for ski slopes.
Week 13: 20 April
Here's the link for our class.
We will continue to work on assignment 4.
Here are the soundings for the month from the Reno National Weather Service.
You can start writing the report by discussing the 'Methods/Instruments' section.
Here's a reminder of report contents.
Thursday's Class:
Preparation:
Be prepared to update and discuss what you've done on your case study so far.
We will time average the SPS30 and sonic data to the time grids of the BAM data for direct comparision over the month.
Here is what we need. Input file with BAM time intervals. Output file with BAM time intervals in a format useful for DAVERAGE in Excel. Fortran program used to convert between input and output. Useful editor for various languages.
We added the DRI weather station data to the UNR Weather station data and time aligned it for the purpose of calculating the lapse rate. The height difference of the two stations is 143 meters.
Sam presented a discussion of the TEOM instrument, another real time measure of PM2.5 and PM10.
Whiteboard notes for Thursday.
Tuesday's Class:
Preparation:
We will look at diel analysis data for meteorology, and discuss it. Be sure your graphs are all caught up.
Following that, we will discuss aerosol column remote sensing with sunphotometers in general, and specifically with our Cimel and MFRSR instruments.
We may time average the SPS30 and sonic data to the time grids of the BAM data for direct comparision over the month.
Here is what we need. Input file with BAM time intervals. Output file with BAM time intervals in a format useful for DAVERAGE in Excel. Fortran program used to convert between input and output. Useful editor for various languages.
Whiteboard notes for Tuesday.
Atmospheric pressure tides description.
Atmospheric pressure tides technical description.
Pressure tide whiteboard notes, and how to calculate.
UNR Weather Station Data February 2020.
Santiago Chile anomalous air pollution events. ACP site link.
Mexico City aerosol 2009 paper.
Mexico City and Queretaro 2019 paper.
Per capita air pollution paper.
Reno winter time air pollution paper.
Our sunphotometer analysis website (air mass and Rayleigh optical depth calculator based on Perl language, here's the source code).
Sun photometer theory.
Week 12: 13 April
Here's the link for our class.
We will continue to work on assignment 4.
Here are the soundings for the month from the Reno National Weather Service.
You can start writing the report by discussing the 'Methods/Instruments' section.
Here's a reminder of report contents.
Thursday's Class:
Preparation:
Some students still need to talk about what day and/or time they would like to use for their case study.
Stormi will present on an instrument and discuss R programming language. [example code].
Courtney will discuss Python for data averaging, graphical display, and windrose generation [examples: windrose code, example wind data. Assignment 4 example.]
Students can prepare by installing Python from the homework page.
We will do diel analysis for the SPS30 and sonic anemometer data.
We may time average the SPS30 and sonic data to the time grids of the BAM data for direct comparision over the month.
Here is what we need. Input file with BAM time intervals. Output file with BAM time intervals in a format useful for DAVERAGE in Excel. Fortran program used to convert between input and output.
Here are the data sets for January 2020, and for March 2020. We may discuss these.
Results:
We did the diel analysis for the SPS30 and sonic anemometer data.
Comparison of diel BAM and SPS30 revealed a correspondence of PM2.5, but that BAM PMcoarse is well in excess of the SPS30 data.
Courtney presented Python analysis of the February data set.
Stormi presented R analysis of the Feb data set, and photographs from the Perlan project in El Calafate Argentina.
Here is the whiteboard for today.
Tuesday's Class:
Preparation:
We will do
diel analysis of meteorological and PM data (typical 24 hour average data) for the various sensors.
We may do wind rose analysis using the Python code given in the homework page. Install Python and run it on the example data.
Students can talk about what day they would like to use for their case study and why.
We will look at the UNR weather station data for 8 Feb 2020, linked in the related information below. There is a surprise.
Results:
Some students discussed their case study.
We looked at the UNR weather station data, and especially at the downwelling IR during the 8th of Feb, perhaps associated with the dust event.
The hysplit back trajectories for the case on the 8th of Feb (actually between 02z and 03z on the 9th in UTC) to further elucidate the behavior of the atmosphere/land surface for this event.
Used a scatter plot of wind speed and PM2.5 to investigate their relationship.
Performed the diel average for the BAM data using the DAVERAGE function in Excel.
Applications of air trajectory analysis review article.
Dynamics of cold fronts.
UNR weather station data for Feb 7-9 for the Feb 8 case study:
Solar Radiation.
Wind Speed
Wind Direction
Air Temperature
Pressure
Downwelling infrared radiation.
Mexico City aerosol 2009 paper.
Mexico City and Queretaro 2019 paper.
Per capita air pollution paper.
Reno winter time air pollution paper.
Week 11: 6 April
Here's the link for our class.
We will continue to work on assignment 4.
Here are the soundings for the month from the Reno National Weather Service.
You can start writing the report by discussing the 'Methods/Instruments' section.
Here's a reminder of report contents.
Tuesday's Class:
Preparation:
Review notes from last Thursday's class.
Add time series analysis.
We will do
diel analysis of meteorological and PM data (typical 24 hour average data) for the various sensors.
We may do wind rose analysis using the Python code given in the homework page. Install Python and run it on the example data.
We may do hysplit back trajectory analysis for the case study at 18:16 LST on February 8th.
Air pollution and COVID-19 mortality.
Air pollution and meteorology in Russia: similar to our case study.
Results:
Discussed cities as living organisms.
Discussed the paper mentioned above on the air quality in Moscow.
Did a time series for Feb 8 winds.
Prepared scatter plots and histograms of the PM2.5 and PMCoarse for the SPS30 and BAM instruments.
Whiteboard notes for today.
Thursday's Class:
Preparation:
Be sure graphs are caught up and edited for publication quality.
Note any questions you have about the analysis we've accomplished to date.
Reflect on analysis that will help understand this month and the case study on the 8th of February.
Sam F will discuss her use of hysplit back and forward trajectory analysis.
Results:
Reviewed the histogram results and scatter plots of PM2.5 and PMCoarse from the SPS30 and BAM. The PM2.5 measurements sort of agree, SPS30 misses most of the PMCoarse.
Prepared scatter/bubble plots as time series of wind direction and wind speed as the bubble diameter, and another with the SPS30 PM2.5 as the bubble diameter, to diagnose the 8 February 2020 case.
Sam F presented a great discussion on hysplit.
We did the back trajectory analysis for 18:00 LST on February 8 2020, finding that northerly winds brought in dust likely from the Honey Lake area.
Prepare for next week by finding your own case study, and prepare analysis for it.
Here are the results of the backtrajectory analysis: 18:00 LST gif image, multiple trajectories at different times around 18:00 LST gif image and Google Earth image and KMZ file.
Whiteboard notes from Thursday's class.
Airborne virus behaviour.
Sampling virus.
Cyclone model.
Light scattering by windblown dust.
Corona virus biology.
Week 10: 30 March
Here's the link for our class.
We will continue to work on assignment 4.
You can start writing the report by discussing the 'Methods/Instruments' section.
Here's a reminder of report contents.
Tuesday's Class:
Preparation:
Everyone should have the sonic anemometer data and the SPS30 particle sensor data in their spreadsheet.
The two data sets should now be time aligned.
Also any data with a NaN in the sonic data should be removed from the SPS30 data as well.
We will talk about the BAM1020 PM2.5 and PM10 sensor and add its data to the spreadsheet as well.
If you are having trouble getting the spreadsheet time aligned let me know.
Your spreadsheet should look like this by now. (Some of the SPS30 data has been trimmed). Note that there are equal numbers of rows for both the sonic and SPS30 data.
When time aligned, both the sonic and SPS30 data have the same number of rows, and the same time column for each row.
Summary:
Talked a lot about how the BAM works, and did an example of mass concentration, bringing in the role of radioactive C14.
Read in the data from the BAM instrument and removed one row of data with a value of 985 ug/m3 that was associated with no sample pump flow ('bad data').
Made a time series graph of the PM2.5 and PM10 from the SPS30 for the entire month. Then copied and pasted that into a new sheet and looked at just the 8th of Feb case study.
Whiteboard notes during class. and as a png file.
Thursday's Class:
Preparation:
Make sure your spreadsheet is caught up to where we left off on Tuesday.
Begin to look at the SPS30 data to see what time (besides 18:16 LST on the 8th of Feb) that you would like to use for your case study.
Summary:
Talked about historical temperature data for London and surrounds for studying the urban heat island effect.
Discussed the case study and how to work from the broad overview perspective to a more refined perspective.
Looked at time series data for the sonic anemometer and BAM PM2.5 and PMCoarse data.
Talked about meteorological patterns in the data.
Whiteboard notes during class.
NOTE: Please reach out to me if you are having issues. We could hold office hours online and work them out. Thanks everyone for making this work.
Airborne virus behaviour.
Sampling virus.
Cyclone model.
Light scattering by windblown dust.
Isotope carbon 14 in the atmosphere.
Beta decay.
Articles describing aerosol and health.
Dissertation (see Figure 6).
Journal article (see Figure 2).
Week 9: 23 March
WE WILL USE VIDEO CONFERENCING FOR CLASS.
BE SURE TO USE THE 'SSO' LOGIN WITH THE APP, AS SHOWN HERE.
Here's the specific link for our class.
You can use your browser or download and use the app, (or both).
We will work on assignment 4 for rest of the semester.
Tuesday's Class:
Got oriented with online communication (went pretty well).
Discussed aerosol sources, types, transport, and optical properties.
Discussed the sonic anemometer theory of operation and advantages.
Read in the sonic anemometer data to Excel. Formed a 'date and time column'. Calculated wind speed and direction (See section 5 of the assignment).
Thursday's Class:
In preparation, have the sonic data read in and processed as discussed on the Tuesday class.
We will work next with the SPS30 instrument and data, the low cost air quality sensor data. We will read it into Excel and time align to the sonic data (deal with any missing data and/or low quality data).
NOTE: Please reach out to me if you are having issues. We could hold office hours online and work them out. Thanks everyone for making this work.
Light scattering by windblown dust.
Week 8: 9 March
Finish working on assignment 3, detection of light using LEDs and photodiodes, and introduction to op Amps as transimpedance amplifiers.
A new sketch is available to time average the photodiode signal to obtain the response time.
The draft of assignment 4 has been posted. Read it and see which group/direction you would like to join for atmospheric measurements and interpretations.
BPW34 photodiode data sheet.
Discussion of operational amplifiers.
Week 7: 2 March
Finish assignment 1 presentations. Talk about water vapor detection.
Begin working on assignment 3, detection of light using LEDs and photodiodes, and introduction to op Amps as transimpedance amplifiers.
Raman scattering strength from water vapor.
BPW34 photodiode data sheet.
European Aerosol Research Lidar Network.
Discussion of operational amplifiers.
Week 6: 24 February
Students should be working on their instrument presentations for Assignment 1. Presentations will start on February 25.
National Center for Atmospheric Science Seminar/Webinar Turbulence in complex terrain: insights from the Perdigão field campaign by Professor Julie Lundquist
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Raman scattering strength from water vapor.
BPW34 photodiode data sheet.
Electronic version of the projects manual we use in class.
Expresspcb software for drawing circuit diagrams.
Use the Classic Software link.
Remove the Expresspcb folder in the documents directory and replace it with this one to get the custom components like Teensy.
Add the Arduino custom component to Express Schematic by unzipping this file and placing the contents in the custom components library.
Add the analog pressure sensor custom component to Express Schematic by unzipping this file and placing the contents in the custom components library.
The Teensy pinout diagram is here.
Week 5: 17 February
Work on parts 5 and 6 of assignment 2, pressure sensor and digital infrared sensor.
Tuesday we will go through use of the Expresspcb software to make circuit schematics.
Students should be working on their instrument presentations for Assignment 1. Presentations will start on February 27.
Electronic version of the projects manual we use in class.
Expresspcb software for drawing circuit diagrams.
Use the Classic Software link.
Remove the Expresspcb folder in the documents directory and replace it with this one to get the custom components like Teensy.
Add the Arduino custom component to Express Schematic by unzipping this file and placing the contents in the custom components library.
Add the analog pressure sensor custom component to Express Schematic by unzipping this file and placing the contents in the custom components library.
The Teensy pinout diagram is here.
Week 4: 10 February
Work on parts 3 and 4 of assignment 2.
Presentations on these sensors
TMP36
Thermistor
Students should be working on their instrument presentations for Assignment 1. Presentations will start on February 27.
Electronic version of the projects manual we use in class.
Expresspcb software for drawing circuit diagrams.
Use the Classic Software link.
Remove the Expresspcb folder in the documents directory and replace it with this one to get the custom components like Teensy.
The Teensy pinout diagram is here.
Week 3: 3 February
Finish working on assignment 2 in class, and begin assignment 3.
Tuesday: Discussed report writing, using Endnote Online for reference management, figure preparation, equations, and report structure, and started part 2 of Assignment 2.
UNR weather station graphs of the last 7 days
Electronic version of the projects manual we use in class.
Can we beat the O3 smog problem? A tale of two cities.
Atmospheric Science Talk Friday February 7th at 2 pm
Location: SLH 3
Saturday February 1st. Click for larger version.
Week 2: 27 January
Continue working on assignment 2 in class.
If you haven't done so, choose an instrument for presenting for assignment 1.
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Week 1: 20 January
Thursday:
Begin to work with light detection using a photoresistor using LEDs as lights. Demonstrated time varying signals with measurements using the oscilloscopes and the Arduino. Used a low pass filter (capacitor) to change the response time of the LED circuit. Briefly introduced the voltage divider as a simple way to measure a variable resistor. Tuesday:
Measurements include the value and the uncertainty - room temperature example. Introductions, assignments, and started Arduino for assignment 2 with breadboarding and meter use. Click image for larger version.
Introductions and orientation.
Places to learn about what is going on in this class:
Daily Notes (here).
Calendar.
The first two assignments have been posted. Assignment 1. Assignment 2.
Syllabus.
Webcampus.
Meteorological data to ponder (thanks to Chris for sharing).
Example of Small Business Innovation Research Request for Proposals with Meteorological Components.
Keep a lab notebook to record what you do and help in lab report writing.
a. Make a table of contents at the back.
b. Number the pages so you can add entries to the table of content.
Discussion of lab notebooking from CU.First we will look at microcontrollers to acquire atmospheric data (Arduino as an implementation).
We will work with analog to digital conversion with the Arduino.
Here's the notes, click image for larger version.
We will with work with electronics,
looking at the internal resistance of our digital volt meters,
doing bread boarding, discussion of circuits, and started with the Arduino/Teensy microcontrollers.Click on image for larger version.
ALL WILL WORK TOGETHER FOR A COMMON PURPOSE: To study the atmosphere from many perspectives!
HOME STUDY THE FOLLOWING:
Useful Presentations Collected from Others.
Microcontroller fundamentals.
What is Arduino, view 1?
What is Arduino, view 2?
Spark fun intro to Arduino.
Spark fun data collection with high altitude balloons.
Maker and Arduino philosophy.
Meaurement uncertainty and local backup.
