Projects

Overview

Students are presented the option of four datasets to use as the main focus for the semester project. Each dataset has a relevant “instrument mentor” that can helpful for questions about the dataset and instruments along the way, but projects are to be designed by students. Project design includes coming up with research questions and/or hypotheses, considering how the dataset(s) can be applied to those questions/hypotheses, and planning the method to do so. With the exception of the flux tower data, all datasets come from the BLISSFUL campaign. This will allow for students to complete projects from similar periods to their peers. At the end of the semester, presentation of findings should be then relevant to peer projects, increasing student learning outcomes!

Papers

Groups should compile the results of their projects into AMS-style articles for submission at the end of the term. The AMS has released a new (Sept. 2021) LaTeX version of their template. You can find an overleaf version here . The word version is here . You can also find the full template details on their page under ‘Manuscript Submission’. Reading these details (and following some additional links therein) will provide information about margins, fonts, etc., but using the templates should include those requirements already.

Papers should not be excessively long; please no more than approximately 15 pages (with figures; references do not count toward this total). 

One deviation from AMS STYLE — Author contribution: please add a section “Author contribution” before the acknowledgements in which the contributions of all co-authors are briefly described. Example: “AA and BB designed the experiments and CC carried them out. DD developed the model code and performed the simulations. AA prepared the manuscript with contributions from all co-authors.” We recommend using the CRediT contributor roles taxonomy (Links to an external site.).
(This section and its description is directly taken from AMT style).

Presentations

General Information

For the semester-end presentations, groups are asked to deliver a multi-part series of talks to present their projects. Each student is expected to deliver a maximum 4-minute in length “lightning” talk on their project, which makes up an individual component of a cohesive multi-part series. These talks should be developed in coordination across groups such that group members do not repeat information. The content of each talk within the multi-part group series is up to each group to determine, but time limits are to be strictly enforced and 3 minute Q&A periods will be reserved until after the final presentation in each group series. 

This approach is somewhat similar to a typical group presentation, but the subtle difference here is that each student will be held independently responsible for their own presentation. Only a fraction of the presentation grade will be dependent on the overall group series. This approach also opens up the presentation to more creative flexibility in organization and topic than typical Introduction, Method, Result order if students so choose. It is possible to use individual presentations to instead focus on topics such as results placed in scientific context, broader impacts of results, or other foci if students or groups choose to do so. However, do remember the talks should be developed in coordination to make up a cohesive series! 

Submission

Students are expected to submit their presentations by noon on the day of the presentations so all presentations can be loaded onto one main computer for streamlined transitions. Submit via Canvas; formats are limited to google slide (share link okay — check permissions!), ppt, pdf. 

Resources

Developing a ‘group presentation’ isn’t all that common in our work, but developing a presentation that fits within a larger cohesive storyline is. Take, for example, the ongoing NSSL Lab Review process! The entire idea for the review presentations is for individual scientists to share their little parts of the NSSL picture as part of the larger picture in a coordinated and cohesive way. It may seem like a relatively short presentation for each speaker, but this process has taken months to plan and organize with so many moving pieces! NSSL is a big group! Check out this example to see how individual parts that at first seem unrelated (TORUS field analysis of tornadic storms and climate studies) come together in a connected storyline. Feel free to click around  if you want to see what else NSSL is up to. 

More Resources:
AGU Storytelling 
Lightning Talks: Science Talks in 5 Minutes or Less  – Nature
How to Give A Great Scientific Talk  – Nature
Three Tips for Giving a Great Research Talk  – Science
Tips for How to Give Research Presentations– June Gruber, Ph.D.
Presentation Zen – Garr Reynolds
Guide to Making a Pecha Kucha Presentation – Felix Jung (we are not using the Pecha Kucha framework, but there are enough similarities between lighting talks and PK for this guide to be useful)

Progress Reports

As you would do for a funded project, you are asked to submit a report of your progress. You are provided a template which asks you specific questions about your project to which you are expected to respond in brief but informative professionally written paragraphs. Lists, bullets, or other styles may be also useful, but you should still be using written sentences in these responses. Remember you are in theory responding to your funder! There is no specific limit requirement, but this is not supposed to be an incredibly long document. NOAA actually uses a form for these reports as of 2020 instead of requesting a single document! Think 1 or 2 paragraphs per question unless there is a lot of detail needed for a particular reason. 

Note: While not required, groups are welcome to submit any updated project writing they have for review by project mentors at this stage! 

Progress Report Templates

Overleaf template viewable here.
Word template downloadable here.
An example progress report from the same VORTEX-SE project that was shown as an example proposal. 

Proposals

Project groups should work together to identify a research question (or questions) to form the basis of a proposal. This proposal should focus directly on the dataset which was assigned to your group, but you are of course free to bring in additional datasets as needed.

Page limit:

5 pages (includes figures/excludes references & title page)

Sections required:

  1. Statement of Problem
  2. Background and Literature Review)
  3. Proposed Research Questions, Methods and Work Plan
  4. Timeline, Milestones, and Delegation Across Team
  5. References

Proposal templates: 

Overleaf LaTeX Template available here .
MS Word Template available here.

Elizabeth is sharing a funded proposal she wrote as a postdoc to NOAA to do some VORTEX-SE work. This project is in its final stages now. The format of this proposal is generally similar to the format you are following, though yours is of course much shorter, and omits some sections. Remember to stay on top of data management for your team, and work early! 

Available Datasets

Blackbrush Flux Tower

Instrument mentors

Petra Klein/Sonia Wharton (LLNL)

Motivation

  • To learn about the instrumentation used on flux towers
  • To expand your knowledge about eddy-covariance measurements, flux calculations, and QA of eddy-covaraince data
  • To analyze and interpret flux-tower data
  • To study the surface energy balance (SEB) in a desert environment 
  • Potential to investigate seasonal changes of the SEB
Caption: Photograph taken in March 2021 showing the Blackbrush flux tower and sensors

The Blackbrush site and instrumentation are described in detail in the Blackbrush tower description document.

This tower was installed by my collaborator Dr. Sonia Wharton from Lawrence Livermore National Laboratory and she has offered us to use the data for a class project. This description also provides some example plots of data measured at the sites.

Details about the instruments and eddy-covariance software used for processing of the data can be found in the user manual. Don’t get scared by this document! You are not expected to install the tower and the data that you will be working with are already processed by the Campbell scientific software. If you decide to choose this project it is however important to review all the data processing steps which are described in the appendices and compare them to what will be discussed in the flux measurement lectures.

The project also allows for a potential comparison with flux data from the ARM Southern Great Plains (SGP) site. Information about the ARM flux measurements can be found in the ARM Eddy Covariance Handbook.

Chem Tuffwing UAS Case (BLISSFUL)

Instrument Mentor

Liz Pillar-Little

Link to UAS Data: https://data.nssl.noaa.gov/thredds/catalog/FRDD/CLAMPS/campaigns/BLISSFUL/co2_plane/catalog.html (Links to an external site.)

Link to Surface CO2 Flux: https://data.nssl.noaa.gov/thredds/catalog/FRDD/CLAMPS/campaigns/BLISSFUL/surface_co2/catalog.html

Schematic demonstrating the feedback loop between evapotranspiration and atmospheric temperature. CO2 is often exchanged with the atmosphere during photosynthetic and respiratory processes.

Motivation

  • Drought exacerbates evapotranspiration demand, supporting a vapor pressure deficit!
  • Higher atmospheric [CO2] can enhance water loss and carbon drawdown; for example: N. Hemisphere greening with global warming
  • How can we better understand sources and sinks in a changing climate?
  • References: Teuling et al. 2018; Belchmeri et. Al. 2021; Bajgain et. al. 2018; Dai et. al. 2018
The Chem TuffWing
  • 2 NDIR CO2 sensors 
  • 2 Capacitive sensors (T and RH)
  • Barometer (altitude/pressure)
  • GPS
Figure showing morning, afternoon, and evening CO2 profile flights collected by the Chem Tuffwing platform from three different days. It asks: Can you identify the layers? Processes? What CO2 might you expect the profiles to approach? RH and T profiles are also available for these cases.

Things to look at or consider

  • How does [CO2] in the column relate to flux at the surface?
  • Does the ABL [CO2] vary dramatically between seasons? What is the magnitude of this change verus what is observed in the ASL?
  • What is the relationship between RH and [CO2] gradients?

Other data available

  • Comparison CO2 data – seasonal variations
    • May-June 2019 (morning transitions)
    • Sept-Oct 2019 (morning transitions)
  • Thermodynamic Data
    • Same sensors as CopterSonde, collected in a similar manner
    • CopterSonde Profiles from BLISSFUL also available 
  • Carbon Flux (see link above), Mesonet, and CO2 tower data for ground comparisons 

CopterSonde UAS flights (BLISSFUL)

Instrument Mentor

Tyler Bell

Link to data: https://data.nssl.noaa.gov/thredds/catalog/FRDD/CLAMPS/campaigns/BLISSFUL/coptersonde/catalog.html

Profiles of mixing ratio and temperature as measured by the coptersonde.

Motivation

  • CopterSondes provide parcel scale thermodynamic and kinematic observations.
  • More studies need done to determine how to interpret these high resolution data

Measured Quantities

  • IMU Data (roll, pitch, yaw, etc)
  • GPS Coordinates
  • Temperature
  • Relative Humidity
  • Wind Speed and Direction (based on IMU data)
  • Pressure

Potential things to look at

  • CopterSonde flights in the stable boundary layer leading up to fog formation
  • Morning/Evening transitions
  • Synthesizing with other instruments (e.g. lidar stares)

Extra datasets available

  • Washington Mesonet Station
  • Occasional radiosondes
  • Doppler lidar

CLAMPS Profiles (BLISSFUL)

Instrument mentor

Elizabeth Smith

Motivation

The boundary layer is one of the most under-observed parts of the atmosphere. Through near-continuous observation of the boundary layer with stat-of-the-art platforms like CLAMPS, we have the opportunity to learn more than ever before about its structure and evolution. Moreover, deployments like BLISSFUL often sample ‘target-of-opportunity’ cases of interesting phenomena from frontal passages, to bores, to convection initiation, and more. 

CLAMPS2 full BLISSFUL period observations

Available data

As discussed in class, the CLAMPS platform provides high temporal resolution boundary layer profiles of temperature, moisture, and wind. CLAMPS1 and CLAMPS2 both deployed to the Kessler Atmospheric and Ecological Field Station for the BLISSFUL campaign, located approximately 300m apart. CLAMP2 deployed slightly earlier (27 May) than CLAMPS1 (3 June), and both systems remained deployed until 8 July 2021. Unless undergoing testing, calibration, demonstration, or operating under a special experimental phase, CLAMPS1’s Doppler lidar stayed in a continuous vertical stare mode (observing vertical velocity) while CLAMPS2’s Doppler lidar conducted near-continuous PPI scans at 70 degrees elevation. The Doppler lidar always completes a single stare between each PPI. These PPIs provide data for VAD analysis providing horizontal wind profiles. Both systems provide thermodynamic retrievals, though CLAMPS2’s MWR cable suffered a cow attack at the beginning of the campaign. Thus, at present CLAMPS1 has MWR+AERI data available to the retrievals, while CLAMPS2 only has AERI data. MWR data might be retrievable from CLAMPS2 MWR’s onboard computer with the newly arrived repair cable! Note also that CLAMPS2 was deployed quite near the Washington OK Mesonet station! Learn more about CLAMPS and data access at https://apps.nssl.noaa.gov/CLAMPS/

Project Potential

These observations are available for students to use as the focus of their projects. They can be used in full to analyze the entire time period or in part to focus on a specific event or short time window. High resolution profiles like these can help us see details about boundary layer structure and evolution, sample passages of boundaries and other phenomena, and even make inferences about turbulence and higher order processes. The possibilities are broad, and can be adjusted to meet project group interests. Pairing these observations with additional observed or simulation datasets can be quite powerful. See for example Smith et al. (2019) or Bell et al. (2020). Of course, with flexibility comes risk of too much to do in too little time! Be sure to think about what exactly you might want to do with a dataset like this one!