the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterizing Thermodynamic Observations from Unshielded Multirotor Drone Sensors
Abstract. Multirotor drones (also known as small Uncrewed Aerial Systems [sUAS] or small Uncrewed Aerial Vehicles [sUAV]) are being increasingly used in atmospheric research to make measurements of the lower atmosphere, and their use is poised to increase in the future. New opportunities are now emerging for drone atmospheric sensing around smaller instrument footprints and lower sensor weights, such as ride-along applications and drone swarms, which necessitate characterizing the performance of unshielded sensors mounted to drones. In this work, we characterize the accuracy of thermodynamic measurements, specifically temperature and water vapor mixing ratio, based on the sensor position onboard multirotor drones. To assess the influence of the drone mechanics on the measurements, ninety-eight drone flights with eight distinct thermodynamic sensor positions were performed next to an instrumented flux tower and a tethersonde carrying identical sensors, where the tower and tethersonde measurements are assumed as truth. The flights were at least nine minutes in length, and nine of the flights were conducted at night. At the best position, absolute daytime temperature errors were between -0.83 K and +0.61 K at the 95 % confidence interval, while nighttime temperature errors were smaller, ranging from -0.28 K and +0.48 K. Water vapor mixing ratio errors are within -0.22 g kg-1 and +0.66 g kg-1. We conclude that measurements in field campaigns are more accurate when sensors are placed away from the main body of the drone and are sufficiently aspirated, such as a position near, but not directly under, a spinning propeller.
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RC1: 'Comment on egusphere-2024-2425', Anonymous Referee #1, 28 Jan 2025
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Review of manuscript “Characterizing Thermodynamic Observations from Unshielded Multirotor Drone Sensors” by S. W. Freeman
In the manuscript “Characterizing Thermodynamic Observations from Unshielded Multirotor Drone Sensors” by S. W. Freeman et al., the authors used observations from a tethersonde and from an instrumented flux tower to investigate the accuracy of temperature and humidity observations derived from instrumented UAS and how the errors varied as a function of sensor position on the UAS as well as a function of radiative regime. The following suggestions should be addressed.
Specific Comments:
Line 88–90: In panels (a) and (d) of Figure 1, it is difficult to distinguish the UAS and sensor, respectively, from the background in the photograph. I recommend including a better photograph in both of these instances to enhance legibility.
Line 135–136: Vague; please quantify how this was determined.
Line 139–140: Please quantify how similar the measurements were in this instance.
Line 169–170: More details should be provided about where and how the iMet XQ sensor was installed on the tower.
Line 182–183: Justification is needed as to why the sensors were rotated daily, rather than after each flight.
Line 198: How were the wind gusts determined?
Line 211–212: More detailed are needed about the data filtering and data quality control here to clarify how the authors determined data that were considered to be invalid.
Line 518–519: The drone data and tethersonde data should presently be ready for review rather than being added upon the article’s acceptance.
Technical Corrections:
Line 73: Missing period.
Line 242: The symbol μ is missing from the parentheses.
Line 280: Extra space.
Line 442: Extra space.
Line 460: “Nevertheless” is one word.
Citation: https://doi.org/10.5194/egusphere-2024-2425-RC1 -
RC2: 'Comment on egusphere-2024-2425', Anonymous Referee #2, 18 Mar 2025
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General Comments
The paper discusses test results from an experiment using a drone with thermodynamic sensors mounted in various locations. The drone is flown next to a tethersonde and an instrumented flux tower. The work builds on prior work of a similar nature which is discussed. The experiments are described, but some of the information should be consolidated in one place. Data quality control is performed and discussed. The relevance of the work is to correct for biases in field experiments using drone-based measurements, which is an important topic. Shortcomings are discussed and ideas for future work are presented. Overall the work is solid, the paper well-written, but some reorganization is recommended. Specifics are provided below.
Specific Comments
On page 2 (lines 55 -59) the authors discuss absolute temperature measurements versus temporal changes and gradients. At this point the difference between the two is not clear, because as a drone flies temperature changes occur (due to e.g. clouds passing or turbulence) and gradients (spatial changes) in temperature and humidity exist and these are measured. In section 3.4 (pages 18 and 19), the authors clarify the difference. It appears that they are talking about absolute and relative measurements. Using those terms on page 2 instead of absolute and temporal changes, would probably make more sense to the reader. The same should happen on lines 298 and 299. Also, technically the term “gradient” is associated with a spatial change and since those are not explored in the paper, I would recommend using “temporal change” instead of “temporal gradient” throughout the document. E.g. lines 398, 477.
On page 2, the sentence spanning lines 61 and 62, states that the “accuracy of thermodynamic measurements made from multiple sensor positions aboard a multirotor while in flight, during both day and night, has not yet been investigated”. I take it the authors mean that the “both day and night” item has not yet been investigated, because Kimball et al and others certainly investigated the other items mentioned in this sentence. Please clarify that specifically the night-time measurements are new and relevant, because they allow the investigation of the effects from solar radiation.
On page 4, lines 97 through 102, the authors discuss the justification for comparing water vapor mixing ratio instead of RH. Please clarify this statement: “…. RH depends not only on accurate temperature measurements but also on the assumption that the temperatures of the drone and the comparison sensor are the same”. If you use the temperature of the RH sensor, both for the drone and the tethersonde/flux tower, to convert RH to water vapor mixing ratio doesn’t that provide an independent representative measure of water vapor on each platform? Please elaborate.
Close-up pictures of the various sensor locations on the drone would be helpful. The relative locations of the sensors are shown in Figure 1, but the specifics of how the sensors are mounted and where they are positioned relative to the support structures on the drone are unclear. E.g. TopShelf and BotShelf are on platforms mounted below the main electronics (lines 123 and 124). What do these platforms look like and where are they relative to the body of the drone? Is there any chance of shading by the drone parts?
In section 2.2 the tethersonde tests are described, but no dates are given. They are elsewhere in the manuscript, but the really should be included in this section as well. Please put all specifics (dates, location, sensor specifics, mounting platform details, etc.) about the experiments in this section for easy reference for your audience. On line 128 a surface weather station is referenced which had not been mentioned or described before., Please give some specifics about what this looks like, how tall is the tower/platform, what sensors are included, is it portable or permanent etc. The drone’s position is mentioned in line 141, but specifics are not given i.e. distance from the base of the tethersonde or latitude/longitude, height above the surface. This information should also be included. Make sure the same information is included in section 2.3 where the flux tower experiments are described.
In section 2.2 the authors state that “this mean altitude does not substantially affect the thermodynamic errors measured” (lines 138 and 139) without explaining why. On page 10 (section 2.5) they do explain this very well. It is recommended that the explanation in section 2.5 either be moved to section 2.2 or a statement be added to section 2.2 referring the reader to an explanation in section 2.5.
On lines 154 and 155, the authors state that “while the tethersonde may also have errors in the temperature measurements arising from solar radiation, these should be similar to those on the drone”. This is where the exact placement of the sensors comes into play. The issue of solar angle relative to the location of the sensors and the possibility of them being shaded by components from the drone or facing directly into the sun, is not addressed. This should be included in the analysis.
On line 180/181 the authors mention that the flux tower measurements were used primarily to validate the tethersonde measurements, but do not explain how. Thhis has the reader wondering which specific sensors were validated, if the tethersonde was deployed next to the flux tower, and when these experiments took place. Again, this is explained later in the document, but really belongs in this section.
In Figure 3, the authors present box plots and frequency distributions which are very insightful. However, because the distributions are not normal, the statistics of mean and standard deviation are not appropriate, instead median and IQR (inter-quartile range) should be used to quantify the center and spread of the distributions. Please replace (or at the very least add) these in the figures and text. Also the sample size (N) is given for most datasets, but not for the flux tower data. This should be included somewhere on page 12 as well in possibly table 2 (add N for all the experiments shown). N is also not given for the nighttime measurements; on line 304 the authors say there were 1.5 total flight hours, but how many individual temperature observations were there? Please add.
In lines 268 and 269, the authors state that “random instrument errors are typically symmetric around zero after being corrected for any mean bias”. I assume this is a general statement and not something pertaining just to your dataset? If that is the case, it makes more sense to mention this at the start of your results section so the reader is aware when reading the rest of this section. A good place would be page 10, line 217.
For the temperature range given on line 296 it is unclear whether the -1.34 K refers to the lowest 2.5th percentile in Figure 3b-i or something else. Similarly, is 1.88 K the highest 97.5th percentile in Figure 3 b-i? Please clarify.
In lines 333 and 334 the colder means of the positions with the most aspiration (CWProp, CCWProp, and BotLeg) are used to demonstrate that forced aspiration can reduce the bias induced by the drone’s heating. The means of these 3 location are 0.08, 0.13, and 0.05 respectively (see Figure 5). What about the low mean (0.07) of position Top? That is the second lowest value and disproves the above statement. Also, the mean of 0.13 (CCWProp) is one of the highest mean values, so this further negates the above argument. Please explain or address.
In line 355 it states that the RH sensor measures the temperature that the RH is based on. Add that that was the temperature used to calculate the water vapor mixing ratio. This will strengthen your statement.
Is the temperature range given on line 431 for the TopShelf location (i.e. Figure 8h) or something else? Please clarify and add the TopShelf range if this is something else. Also at the end of the sentence on line 443 you could state that: “because the temperature difference errors for OverBat range between x and y”. Then provide the values for x and y from Fig8e.
Technical Corrections
Caption of Figure 1: no hyphen needed in in-flight. Just use in flight.
On line 134 add the words “the drone” after maneuver.
Line 178: Add “resistance” after the word platinum.
On the last line of the caption of Figure 3, the symbol for ‘mu’ (mean error) is missing from the parentheses.
Line 295: Add ‘that’ after the word demonstrate.
Line 460: nevertheless is one word.
Line 497 onboard is two words: on board.
Citation: https://doi.org/10.5194/egusphere-2024-2425-RC2
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