the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data collected using small uncrewed aircraft system during the TRacking Aerosol Convection Interactions ExpeRiment (TRACER)
Gijs de Boer
Petra Klein
Jonathan Hamilton
Michelle Spencer
Radiance Calmer
Antonio R. Segales
Michael Rhodes
Tyler M. Bell
Justin Buchli
Kelsey Britt
Elizabeth Asher
Isaac Medina
Brian Butterworth
Leia Otterstatter
Madison Ritsch
Bryony Puxley
Angelina Miller
Arianna Jordan
Ceu Gomez-Faulk
Elizabeth Smith
Steve Borenstein
Troy Thornberry
Brian Argrow
Elizabeth Pillar-Little
Abstract. The main goal of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) project was to further understand the role that regional circulations and aerosol loading play in the convective cloud life cycle across the greater Houston, Texas area. To accomplish this goal, the United States Department of Energy and research partners collaborated to deploy atmospheric observing systems across the region. Cloud and precipitation radars, radiosondes, and air quality sensors captured atmospheric and cloud characteristics. A dense lower atmospheric dataset was developed using ground-based remote sensors, a tethersonde, and uncrewed aerial systems (UAS). TRACER-UAS is a subproject that deployed two UAS platforms to gather high-resolution observations in the lower atmosphere between 1 June and 30 September 2022. The University of Oklahoma CopterSonde and the University of Colorado Boulder RAAVEN (Robust Autonomous Aerial Vehicle – Endurant Nimble) were flown at two coastal locations between the Gulf of Mexico and Houston. The University of Colorado RAAVEN gathered measurements of atmospheric thermodynamic state, winds and turbulence, and aerosol size distribution. Meanwhile, the University of Oklahoma CopterSonde system operated on a regular basis to resolve the vertical structure of the thermodynamic and kinematic state. Together, a complementary dataset of over 200 flight hours across 61 days was generated, and data from each platform proved to be in strong agreement. In this paper, the platforms and respective data collection and processing are described. The dataset described herein provides information on boundary layer evolution, the sea breeze circulation, conditions prior to and nearby deep convection, and the vertical structure and evolution of aerosols.
- Preprint
(10605 KB) - Metadata XML
- BibTeX
- EndNote
Francesca Lappin et al.
Status: open (until 13 Dec 2023)
-
RC1: 'Comment on essd-2023-371', Anonymous Referee #1, 25 Oct 2023
reply
General comments:
This paper provides 200 flight hours of data during the TRACE-UAS to support the project goal – further understanding the role that regional circulations and aerosol loading play in the convective cloud life cycle across the greater Houston, Texas area. The authors presented a very useful payload for the atmospheric study and flight conditions. The meteorological data is of high quality. However, the aerosol data are very limited, and the data quality is still unknown. The paper heavily focused on the met data discussion, which is great but missing the connection to support half of the project goal.
Specific comments:
Introduction: this session highlighted the observational gap in aerosol and gas phase measurements but didn’t mention the importance of the combined datasets. I also recommend including why it is essential to understand thermodynamic and kinematic data and their linkages to the aerosol properties/distribution in the region.
P5, line 99-100, what is the aerosol collection efficiency of the platform? Does the flight orientation affect the aerosol collection? How do you validate the aerosol data accuracy with the platform?
P5, line 105 -106, It will be helpful to provide a summary of the measurement accuracy or uncertainty in this manuscript other than referring to the previous study.
Table1. It will be useful to include more information about the flight conditions, such as flight hours with SBF or the altitude range for the profiling flight. I think those have been included in the following sessions.
How many POPS flights do you have?
P8, line 175, What is the accuracy of the derived quantities? What is the time resolution of the re-sampled data? 1 Hz or 10 Hz?
Table 2. What are the sources of errors for these measurements?
Line 273 -274, What information can we gain from these 46 profiles?
Line 283 -285, Do you have the comparison of the vertical wind data?
Line 294, How do you know it is due to the spatial difference, not the sensor uncertainty or discrepancy between sensors?
Appendix A1 needs to include more information and explain the variable names. For example, what is the POPS_LDM?
Citation: https://doi.org/10.5194/essd-2023-371-RC1
Francesca Lappin et al.
Data sets
TRACER-UAS CopterSonde and RAAVEN data Francesca Lappin and Gijs de Boer https://adc.arm.gov/essd/tracer-uas/
Francesca Lappin et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
259 | 51 | 10 | 320 | 4 | 10 |
- HTML: 259
- PDF: 51
- XML: 10
- Total: 320
- BibTeX: 4
- EndNote: 10
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1