Articles | Volume 15, issue 8
https://doi.org/10.5194/amt-15-2607-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-2607-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Apr 2022
Research article |
| 29 Apr 2022
| 29 Apr 2022
Considerations for improving data quality of thermo-hygrometer sensors on board unmanned aerial systems for planetary boundary layer research
School of Electrical and Computer Engineering, The University of Oklahoma, Norman, Oklahoma 73019, United States
Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma, Norman, Oklahoma 73072, United States
Advanced Radar Research Center, The University of Oklahoma, Norman, Oklahoma 73019, United States
Phillip B. Chilson
School of Meteorology, The University of Oklahoma, Norman, Oklahoma 73072, United States
Advanced Radar Research Center, The University of Oklahoma, Norman, Oklahoma 73019, United States
Center for Autonomous Sensing and Sampling, The University of Oklahoma, Norman, Oklahoma 73072, United States
Jorge L. Salazar-Cerreño
School of Electrical and Computer Engineering, The University of Oklahoma, Norman, Oklahoma 73019, United States
Advanced Radar Research Center, The University of Oklahoma, Norman, Oklahoma 73019, United States
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Atmos. Meas. Tech., 15, 5581–5597, https://doi.org/10.5194/amt-15-5581-2022, https://doi.org/10.5194/amt-15-5581-2022, 2022
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The quality control of sub-hourly rain gauge data is a challenging task due to the high variability and low spatial consistency of the data. We developed an innovative approach to the quality control of telemetric rain gauge data focused on assessing the reliability of individual observations. Our scheme employs weather radar data to detect erroneous rain gauge measurements and to assess the data reliability. The scheme is used operationally by the Polish meteorological and hydrological service.
Gina Jozef, John Cassano, Sandro Dahlke, and Gijs de Boer
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During the MOSAiC expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 uncrewed aircraft system. These data were used to identify the best method for atmospheric boundary layer height detection by comparing visually identified subjective boundary layer height to that identified by several objective automated detection methods. The results show a bulk Richardson number-based approach gives the best estimate of boundary layer height.
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This study evaluates how a classically defined variable, air parcel buoyancy, can be used to interpret transitions in the atmospheric boundary layer (ABL). To capture the high-resolution variations, remotely piloted aircraft systems are used to collect data in two field campaigns. This paper finds that buoyancy has distinct evolutions prior to low-level jet and convective initiation cases. Additionally, buoyancy mixes well to act as an ABL height indicator comparable to other methods.
Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li
Atmos. Meas. Tech., 15, 757–773, https://doi.org/10.5194/amt-15-757-2022, https://doi.org/10.5194/amt-15-757-2022, 2022
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Our research has determined the possible relationship between Weibull natural wind mesoscale parameter c and shape factor k with height under the conditions of a desert steppe terrain in northern China, which has great potential in wind power generation. We have gained an enhanced understanding of the seasonal changes in the surface roughness of the desert grassland and the changes in the incoming wind direction.
Xinhua Zhou, Tian Gao, Eugene S. Takle, Xiaojie Zhen, Andrew E. Suyker, Tala Awada, Jane Okalebo, and Jiaojun Zhu
Atmos. Meas. Tech., 15, 95–115, https://doi.org/10.5194/amt-15-95-2022, https://doi.org/10.5194/amt-15-95-2022, 2022
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Air temperature from sonic temperature and air moisture has been used without an exact equation. We present an exact equation of such air temperature for closed-path eddy-covariance flux measurements. Air temperature from this equation is equivalent to sonic temperature in its accuracy and frequency response. It is a choice for advanced flux topics because, with it, thermodynamic variables in the flux measurements can be temporally synchronized and spatially matched at measurement scales.
Haoyu Jiang
Atmos. Meas. Tech., 15, 1–9, https://doi.org/10.5194/amt-15-1-2022, https://doi.org/10.5194/amt-15-1-2022, 2022
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Sea surface wind and waves are important ocean parameters that can be continuously observed by meteorological buoys. Meteorological buoys are sparse in the ocean due to their high cost of deployment and maintenance. In contrast, low-cost compact wave buoys are suited for deployment in large numbers. Although wave buoys are not designed for wind measurement, we found that deep learning can estimate wind from wave measurements accurately, making wave buoys a good-quality data source for sea wind.
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021, https://doi.org/10.5194/amt-14-7835-2021, 2021
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Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.
Maryam Ilyas, Douglas Nychka, Chris Brierley, and Serge Guillas
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Instrumental temperature records are fundamental to climate science. There are spatial gaps in the distribution of these measurements across the globe. This lack of spatial coverage introduces coverage error. In this research, a methodology is developed and used to quantify the coverage errors. It results in a data product that, for the first time, provides a full description of both the spatial coverage uncertainties along with the uncertainties in the modeling of these spatial gaps.
Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Longjiang Li, Suqin Wu, Kefei Zhang, Xiaoming Wang, Wang Li, Zhen Shen, Dantong Zhu, Qimin He, and Moufeng Wan
Atmos. Meas. Tech., 14, 6379–6394, https://doi.org/10.5194/amt-14-6379-2021, https://doi.org/10.5194/amt-14-6379-2021, 2021
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The zenith hydrostatic delay (ZHD) derived from blind models are of low accuracy, especially in mid- and high-latitude regions. To address this issue, the ratio of the ZHD to zenith total delay (ZTD) is firstly investigated; then, based on the relationship between the ZHD and ZTD, a new ZHD model was developed using the back propagation artificial neural network (BP-ANN) method which took the ZTD as an input variable. The model outperforms blind models.
Grant W. Petty
Atmos. Meas. Tech., 14, 1959–1976, https://doi.org/10.5194/amt-14-1959-2021, https://doi.org/10.5194/amt-14-1959-2021, 2021
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Aircraft measurements of turbulent fluxes of matter and energy are important in field investigations of the interaction of the Earth's surface and the atmosphere. Because these measurements are of randomly fluctuating quantities, averages must be taken over longer flight tracks to reduce uncertainty. This paper investigates the relationship between track length and measurement error using a computer model simulation of a marine environment and compares the results with published theory.
Yadong Wang, Lin Tang, Pao-Liang Chang, and Yu-Shuang Tang
Atmos. Meas. Tech., 14, 185–197, https://doi.org/10.5194/amt-14-185-2021, https://doi.org/10.5194/amt-14-185-2021, 2021
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The motivation of this work is to develop a precipitation separation approach that can be implemented on those radars with fast scanning schemes. In these schemes, the higher tilt radar data are not available, which poses a challenge for the traditional approaches. This approach uses artificial intelligence, which integrates polarimetric radar variables. The quantitative precipitation estimation will benefit from the output of this algorithm.
Loiy Al-Ghussain and Sean C. C. Bailey
Atmos. Meas. Tech., 14, 173–184, https://doi.org/10.5194/amt-14-173-2021, https://doi.org/10.5194/amt-14-173-2021, 2021
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Unmanned aerial vehicles equipped with multi-hole probes are an effective approach to measure the wind vector with high spatial and temporal resolution. However, the aircraft motion must be removed from the measured signal first, a process often introducing bias due to small errors in the relative orientation of coordinates. We present an approach that has successfully been applied in post-processing, which was found to minimize the influence of aircraft motion on wind measurements.
Alessandro Fassò, Michael Sommer, and Christoph von Rohden
Atmos. Meas. Tech., 13, 6445–6458, https://doi.org/10.5194/amt-13-6445-2020, https://doi.org/10.5194/amt-13-6445-2020, 2020
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Modern radiosonde balloons fly from ground level up to the lower stratosphere and take temperature measurements. What is the uncertainty of interpolated values in the resulting atmospheric temperature profiles? To answer this question, we introduce a general statistical–mathematical model for the computation of interpolation uncertainty. Analysing more than 51 million measurements, we provide some understanding of the consequences of filling missing data with interpolated ones.
Jussi Leinonen and Alexis Berne
Atmos. Meas. Tech., 13, 2949–2964, https://doi.org/10.5194/amt-13-2949-2020, https://doi.org/10.5194/amt-13-2949-2020, 2020
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The appearance of snowflakes provides a signature of the atmospheric processes that created them. To get this information from large numbers of snowflake images, automated analysis using computer image recognition is needed. In this work, we use a neural network that learns the structure of the snowflake images to divide a snowflake dataset into classes corresponding to different sizes and structures. Unlike with most comparable methods, only minimal input from a human expert is needed.
Amber Ross, Craig D. Smith, and Alan Barr
Atmos. Meas. Tech., 13, 2979–2994, https://doi.org/10.5194/amt-13-2979-2020, https://doi.org/10.5194/amt-13-2979-2020, 2020
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The raw data derived from most automated accumulating precipitation gauges often suffer from non-precipitation-related fluctuations in the measurement of the gauge bucket weights from which the precipitation amount is determined. This noise can be caused by electrical interference, mechanical noise, and evaporation. This paper presents an automated filtering technique that builds on the principle of iteratively balancing noise to produce a clean precipitation time series.
Soo-Hyun Kim, Hye-Yeong Chun, Jung-Hoon Kim, Robert D. Sharman, and Matt Strahan
Atmos. Meas. Tech., 13, 1373–1385, https://doi.org/10.5194/amt-13-1373-2020, https://doi.org/10.5194/amt-13-1373-2020, 2020
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We retrieve the eddy dissipation rate (EDR) from the derived equivalent vertical gust included in the Aircraft Meteorological Data Relay data for more reliable and consistent observations of aviation turbulence globally with the single preferred EDR metric. We convert the DEVG to the EDR using two methods (lognormal mapping scheme and best-fit curve between EDR and DEVG), and the DEVG-derived EDRs are evaluated against in situ EDR data reported by US-operated carriers.
Nicholas Hamilton
Atmos. Meas. Tech., 13, 1019–1032, https://doi.org/10.5194/amt-13-1019-2020, https://doi.org/10.5194/amt-13-1019-2020, 2020
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The identification of atmospheric conditions within a multivariable atmospheric data set is an important step in validating emerging and existing models used to simulate wind plant flows and operational strategies. The total variation approach developed here offers a method founded in tested mathematical metrics and can be used to identify and characterize periods corresponding to quiescent conditions or specific events of interest for study or wind energy development.
Dafina Kikaj, Janja Vaupotič, and Scott D. Chambers
Atmos. Meas. Tech., 12, 4455–4477, https://doi.org/10.5194/amt-12-4455-2019, https://doi.org/10.5194/amt-12-4455-2019, 2019
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A new method was developed to identify persistent temperature inversion events in a subalpine basin using a radon-based method (RBM). By comparing with an existing pseudo-vertical temperature gradient method, the RBM was shown to be more reliable and seasonally independent. The RBM has the potential to increase the understanding of meteorological controls on air pollution episodes in complex terrain beyond the capability of contemporary atmospheric stability classification tools.
Jens Faber, Michael Gerding, Andreas Schneider, Andreas Dörnbrack, Henrike Wilms, Johannes Wagner, and Franz-Josef Lübken
Atmos. Meas. Tech., 12, 4191–4210, https://doi.org/10.5194/amt-12-4191-2019, https://doi.org/10.5194/amt-12-4191-2019, 2019
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Atmospheric measurements on rising balloons can be compromised by the balloon's wake. The aim of this study is to provide a tool for assessing the likelihood of encountering the balloon's wake at the position of the gondola. This includes an uncertainty analysis of the calculation and a retrieval of vertical winds. We find an average wake encounter probability of 28 % for a standard radiosonde. Additionally, we evaluate the influence of wake from smaller objects on turbulence measurements.
Maosi Chen, Zhibin Sun, John M. Davis, Yan-An Liu, Chelsea A. Corr, and Wei Gao
Atmos. Meas. Tech., 12, 935–953, https://doi.org/10.5194/amt-12-935-2019, https://doi.org/10.5194/amt-12-935-2019, 2019
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Combining a new dynamic uncertainty estimation method with Gaussian process regression (GP), we provide a generic and robust solution to estimate the underlying mean and uncertainty functions of time series with variable mean, noise, sampling density, and length of gaps. The GP solution was applied and validated on three UV-MFRSR Vo time series at three ground sites with improved accuracy of the smoothed time series in terms of aerosol optical depth compared with two other smoothing methods.
Christoph Schlager, Gottfried Kirchengast, and Juergen Fuchsberger
Atmos. Meas. Tech., 11, 5607–5627, https://doi.org/10.5194/amt-11-5607-2018, https://doi.org/10.5194/amt-11-5607-2018, 2018
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In this work we further developed and evaluated an operational weather diagnostic application, the WegenerNet Wind Product Generator (WPG), and applied it to the WegenerNet Johnsbachtal (JBT), a dense meteorological station network located in a mountainous Alpine region. The WPG automatically generates gridded high-resolution wind fields in near-real time with a temporal resolution of 30 min and a spatial resolution of 100 m x 100 m.
Kaisa Lakkala, Antti Arola, Julian Gröbner, Sergio Fabian León-Luis, Alberto Redondas, Stelios Kazadzis, Tomi Karppinen, Juha Matti Karhu, Luca Egli, Anu Heikkilä, Tapani Koskela, Antonio Serrano, and José Manuel Vilaplana
Atmos. Meas. Tech., 11, 5167–5180, https://doi.org/10.5194/amt-11-5167-2018, https://doi.org/10.5194/amt-11-5167-2018, 2018
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The performance of the cosine error correction method for correcting spectral UV measurements of the Brewer spectroradiometer was studied. The correction depends on the sky radiation distribution, which can change during one spectral scan. The results showed that the correction varied between 4 and 14 %, and that the relative differences between the reference and the Brewer diminished by 10 %. The method is applicable to other instruments as long as the required input parameters are available.
Jason Kelley and Chad Higgins
Atmos. Meas. Tech., 11, 2151–2158, https://doi.org/10.5194/amt-11-2151-2018, https://doi.org/10.5194/amt-11-2151-2018, 2018
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Measuring fluxes of energy and trace gases using the surface renewal (SR) method can be economical and robust, but it requires computationally intensive calculations. Several new algorithms were written to perform the required calculations more efficiently and rapidly, and were tested with field data and computationally rigorous SR methods. These efficient algorithms facilitate expanded use of SR in atmospheric experiments, for applied monitoring, and in novel field implementations.
Viswanathan Bringi, Merhala Thurai, and Darrel Baumgardner
Atmos. Meas. Tech., 11, 1377–1384, https://doi.org/10.5194/amt-11-1377-2018, https://doi.org/10.5194/amt-11-1377-2018, 2018
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Raindrop fall velocities are important for rain rate estimation, soil erosion studies and in numerical modelling of rain formation in clouds. The assumption that the fall velocity is uniquely related to drop size is made inherently based on laboratory measurements under still air conditions from nearly 68 years ago. There have been very few measurements of drop fall speeds in natural rain under both still and turbulent wind conditions. We report on fall speed measurements in natural rain shafts.
Marta Wacławczyk, Yong-Feng Ma, Jacek M. Kopeć, and Szymon P. Malinowski
Atmos. Meas. Tech., 10, 4573–4585, https://doi.org/10.5194/amt-10-4573-2017, https://doi.org/10.5194/amt-10-4573-2017, 2017
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We propose two novel methods to estimate turbulent kinetic energy dissipation rate applicable to airborne measurements. In this way we increase robustness of the dissipation rate retrieval and extend its applicability to a wider range of data sets. The new approaches relate the predicted form of the dissipation spectrum to the mean of zero crossings of the measured velocity fluctuations. The methods are easy to implement numerically, and estimates remain unaffected by certain measurement errors.
Sabine Wüst, Verena Wendt, Ricarda Linz, and Michael Bittner
Atmos. Meas. Tech., 10, 3453–3462, https://doi.org/10.5194/amt-10-3453-2017, https://doi.org/10.5194/amt-10-3453-2017, 2017
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Cubic splines with equidistant spline sampling points are a common method in atmospheric science for the approximation of background conditions by means of filtering superimposed fluctuations from a data series. However, splines can generate considerable artificial oscillations in the background and the residuals. We introduce a repeating spline approach which is able to significantly reduce this phenomenon and to apply it to TIMED-SABER vertical temperature profiles from 2010 to 2014.
Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes
Atmos. Meas. Tech., 10, 1557–1574, https://doi.org/10.5194/amt-10-1557-2017, https://doi.org/10.5194/amt-10-1557-2017, 2017
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The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.
Christophe Praz, Yves-Alain Roulet, and Alexis Berne
Atmos. Meas. Tech., 10, 1335–1357, https://doi.org/10.5194/amt-10-1335-2017, https://doi.org/10.5194/amt-10-1335-2017, 2017
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The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling snowflakes and ice crystals. A method is proposed to automatically classify these pictures into six classes of snowflakes as well to estimate the degree of riming and to detect whether or not the particles are melting. Multinomial logistic regression is used with a manually classified
reference set. The evaluation demonstrates the good and reliable performance of the proposed technique.
Zhaopeng Luan, Yongxiang Han, Tianliang Zhao, Feng Liu, Chong Liu, Mark J. Rood, Xinghua Yang, Qing He, and Huichao Lu
Atmos. Meas. Tech., 10, 273–279, https://doi.org/10.5194/amt-10-273-2017, https://doi.org/10.5194/amt-10-273-2017, 2017
Zofia Baldysz, Grzegorz Nykiel, Andrzej Araszkiewicz, Mariusz Figurski, and Karolina Szafranek
Atmos. Meas. Tech., 9, 4861–4877, https://doi.org/10.5194/amt-9-4861-2016, https://doi.org/10.5194/amt-9-4861-2016, 2016
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In this paper two official processing strategies of GPS observations were analysed. The main purpose was to assess differences in long-term (linear trends) and short-term (oscillations) changes between these two sets of data. Investigation was based on 18-year and 16-year time series and showed that, despite the general consistency, for selected stations a change of processing strategy may have caused significant differences (compared to the uncertainties) in estimated linear trend values.
Jussi Tiira, Dmitri N. Moisseev, Annakaisa von Lerber, Davide Ori, Ali Tokay, Larry F. Bliven, and Walter Petersen
Atmos. Meas. Tech., 9, 4825–4841, https://doi.org/10.5194/amt-9-4825-2016, https://doi.org/10.5194/amt-9-4825-2016, 2016
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In this study winter measurements collected in Southern Finland are used to document microphysical properties of falling snow. It is shown that a new video imager can be used for such studies. Snow properties do vary between winters.
Gutemberg Borges França, Manoel Valdonel de Almeida, and Alessana C. Rosette
Atmos. Meas. Tech., 9, 2335–2344, https://doi.org/10.5194/amt-9-2335-2016, https://doi.org/10.5194/amt-9-2335-2016, 2016
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This paper presents a novel model, based on neural network techniques, to produce short-term and locally specific forecasts of significant instability for flights in the terminal area of Rio de Janeiro's airport, Brazil. Twelve years of data were used for neural network training/validation and test. The test showed that the proposed model can grab the physical content inside the data set, and its performance is encouraging for the first and second hours to nowcast significant instability events.
Jacek M. Kopeć, Kamil Kwiatkowski, Siebren de Haan, and Szymon P. Malinowski
Atmos. Meas. Tech., 9, 2253–2265, https://doi.org/10.5194/amt-9-2253-2016, https://doi.org/10.5194/amt-9-2253-2016, 2016
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This paper is presenting a feasibility study focused on methods of estimating the turbulence intensity based on a class of navigational messages routinely broadcast by the commercial aircraft (known as ADS-B and Mode-S). Using this kind of information could have potentially significant impact on aviation safety. Three methods have been investigated.
Jörg Burdanowitz, Christian Klepp, and Stephan Bakan
Atmos. Meas. Tech., 9, 1637–1652, https://doi.org/10.5194/amt-9-1637-2016, https://doi.org/10.5194/amt-9-1637-2016, 2016
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We develop a new automatic algorithm to distinguish oceanic precipitation into rain, snow and mixed phase using optical disdrometers deployed on board research vessels. In combination, air temperature, relative humidity and the maximum precipitation particle diameter outperform human observer data and yield highest skill to predict the precipitation phase. This knowledge allows deriving accurate rain and snowfall rates with dense global ocean sampling, which enables satellite sensor validation.
Cited articles
Barbieri, L., Kral, S. T., Bailey, S. C. C., Frazier, A. E., Jacob, J. D., Reuder, J., Brus, D., Chilson, P. B., Crick, C., Detweiler, C., Doddi, A., Elston, J., Foroutan, H., González-Rocha, J., Greene, B. R., Guzman, M. I., Houston, A. L., Islam, A., Kemppinen, O., Lawrence, D., Pillar-Little, E. A., Ross, S. D., Sama, M. P., Schmale, D. G., Schuyler, T. J., Shankar, A., Smith, S. W., Waugh, S., Dixon, C., Borenstein, S., and de Boer, G.: Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign, Sensors, 19, 2179, https://doi.org/10.3390/s19092179, 2019. a, b
Bell, T. M., Greene, B. R., Klein, P. M., Carney, M., and Chilson, P. B.: Confronting the boundary layer data gap: evaluating new and existing methodologies of probing the lower atmosphere, Atmos. Meas. Tech., 13, 3855–3872, https://doi.org/10.5194/amt-13-3855-2020, 2020. a, b
Chilson, P. B., Bell, T. M., Brewster, K. A., Britto Hupsel de Azevedo, G., Carr, F. H., Carson, K., Doyle, W., Fiebrich, C. A., Greene, B. R., Grimsley, J. L., Kanneganti, S. T., Martin, J., Moore, A., Palmer, R. D., Pillar-Little, E. A., Salazar-Cerreno, J. L., Segales, A. R., Weber, M. E., Yeary, M., and Droegemeier, K. K.: Moving towards a Network of Autonomous UAS Atmospheric Profiling Stations for Observations in the Earth’s Lower Atmosphere: The 3D Mesonet Concept, Sensors, 19, 2720, https://doi.org/10.3390/s19122720, 2019. a
Dantzig, J. A.: Improved transient response of thermocouple sensors, Rev. Sci. Instrum., 56, 723–725, https://doi.org/10.1063/1.1138214, 1985. a, b
Das, S. and Suganthan, P.: Differential Evolution: A Survey of the
State-of-the-Art, IEEE T. Evolut. Comput., 15, 4–31, 2011. a
Davidson, P.: Turbulence An Introduction for Scientists and Engineers, Oxford University Press, https://doi.org/10.1093/acprof:oso/9780198722588.001.0001, 2015. a
de Boer, G., Diehl, C., Jacob, J., Houston, A., Smith, S. W., Chilson, P., Schmale, D. G., Intrieri, J., Pinto, J., Elston, J., Brus, D., Kemppinen, O., Clark, A., Lawrence, D., Bailey, S. C. C., Sama, M. P., Frazier, A., Crick, C., Natalie, V., Pillar-Little, E., Klein, P., Waugh, S., Lundquist, J. K., Barbieri, L., Kral, S. T., Jensen, A. A., Dixon, C., Borenstein, S., Hesselius, D., Human, K., Hall, P., Argrow, B., Thornberry, T., Wright, R., and Kelly, J. T.: Development of Community, Capabilities, and Understanding through Unmanned Aircraft-Based Atmospheric Research: The LAPSE-RATE Campaign, B. Am. Meteorol. Soc., 101, E684–E699,
https://doi.org/10.1175/BAMS-D-19-0050.1, 2020. a
Farahani, H., Wagiran, R., and Hamidon, M. N.: Humidity Sensors Principle, Mechanism, and Fabrication Technologies: A Comprehensive Review, Sensors, 14,
7881–7939, https://doi.org/10.3390/s140507881, 2014. a, b, c
Fatoorehchi, H., Alidadi, M., Rach, R., and Shojaeian, A.: Theoretical and
Experimental Investigation of Thermal Dynamics of Steinhart–Hart Negative
Temperature Coefficient Thermistors, J. Heat Transf., 141, 072003,
https://doi.org/10.1115/1.4043676, 2019. a, b
Geerts, B., Raymond, D., Barth, M., Detwiler, A., Klein, P., Lee, W.-C.,
Markowski, P., and Mullendore, G.: Community Workshop on Developing
Requirements for In Situ and Remote Sensing Capabilities in Convective and
Turbulent Environments (C-RITE), Tech. rep., UCAR/NCAR Earth Observing
Laboratory, https://doi.org/10.5065/D6DB80KR, 2017. a
Gibbs, J. A., Fedorovich, E., Maronga, B., Wainwright, C., and Dröse, M.: Comparison of Direct and Spectral Methods for Evaluation of the Temperature Structure Parameter in Numerically Simulated Convective Boundary Layer Flows,
Mon. Weather Rev., 144, 2205–2214, https://doi.org/10.1175/MWR-D-15-0390.1, 2016. a, b
Greene, B. R., Segales, A. R., Waugh, S., Duthoit, S., and Chilson, P. B.: Considerations for temperature sensor placement on rotary-wing unmanned aircraft systems, Atmos. Meas. Tech., 11, 5519–5530, https://doi.org/10.5194/amt-11-5519-2018, 2018. a, b, c
Greene, B. R., Segales, A. R., Bell, T. M., Pillar-Little, E. A., and Chilson, P. B.: Environmental and Sensor Integration Influences on Temperature Measurements by Rotary-Wing Unmanned Aircraft Systems, Sensors, 19, 1470, https://doi.org/10.3390/s19061470, 2019. a, b, c, d
Greene, B. R., Bell, T. M., Pillar-Little, E. A., Segales, A. R., Britto
Hupsel de Azevedo, G., Doyle, W., Tripp, D. D., Kanneganti, S. T., and
Chilson, P. B.: University of Oklahoma CopterSonde Files from LAPSE-RATE, Zenodo [data set], https://doi.org/10.5281/zenodo.3737087, 2020. a
Hardesty, R. M. and Hoff, R. M.: Thermodynamic Profiling Technologies Workshop Report to the National Science Foundation and the National Weather Service, Tech. Rep. NCAR/TN-488+STR, National Center for Atmospheric Research, https://doi.org/10.5065/D6SQ8XCF, 2012. a
Houston, A. L. and Keeler, J. M.: The Impact of Sensor Response and Airspeed on the Representation of the Convective Boundary Layer and Airmass Boundaries by Small Unmanned Aircraft Systems, J. Atmos. Ocean. Tech., 35, 1687–1699, https://doi.org/10.1175/JTECH-D-18-0019.1, 2018. a, b, c, d
Islam, A., Houston, A., Shankar, A., and Detweiler, C.: Design and Evaluation
of Sensor Housing for Boundary Layer Profiling Using Multirotors, Sensors
(Basel), 19, 2481, https://doi.org/10.3390/s19112481, 2019. a, b
Jacob, J. D., Chilson, P. B., Houston, A. L., and Smith, S. W.: Considerations for Atmospheric Measurements with Small Unmanned Aircraft Systems, Atmosphere, 9, 252, https://doi.org/10.3390/atmos9070252, 2018. a, b
Kaimal, J. C., Wyngaard, J. C., Haugen, D. A., Cote, O. R., Izumi, Y., Caughey, S. J., and Readings, C. J.: Turbulence Structure in the Convective Boundary Layer, J. Atmos. Sci., 33, 2152–2169, 1976. a
Koch, S. E., Fengler, M., Chilson, P. B., Elmore, K. L., Argrow, B., Andra,
Jr., D. L., and Lindley, T.: On the Use of Unmanned Aircraft for Sampling
Mesoscale Phenomena in the Preconvective Boundary Layer, J. Atmos. Ocean.
Tech., 35, 2265–2288, https://doi.org/10.1175/JTECH-D-18-0101.1, 2018. a
Kohsiek, W.: Measuring CT2, CQ2, and CTQ in the Unstable Surface Layer, and
Relations to the Vertical Fluxes of Heat and Moisture, Bound.-Lay.
Meteorol., 24, 89–107, https://doi.org/10.1007/BF00121802, 1982. a
Kolmogorov, A. N.: The local structure of turbulence in incompressible viscous fluid for very large Reynolds numbers, Proc. R. Soc. Lond. A, 434, 9–13, 1941. a
Kral, S., Reuder, J., Vihma, T., Suomi, I., O'Connor, E., Kouznetsov, R., Wrenger, B., Rautenberg, A., Urbancic, G., Jonassen, M., Båserud, L., Maronga, B., Mayer, S., Lorenz, T., Holtslag, A., Steeneveld, G.-J., Seidl, A., Müller, M., Lindenberg, C., Langohr, C., Voss, H., Bange, J., Hundhausen, M., Hilsheimer, P., and Schygulla, M.: Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR) – The Hailuoto 2017 Campaign, Atmosphere, 9, 268, https://doi.org/10.3390/atmos9070268, 2018. a, b
Li, Y., Zhang, Z., Hao, X., and Yin, W.: A Measurement System for Time Constant of Thermocouple Sensor Based on High Temperature Furnace, Appl. Sci., 8, 2585, https://doi.org/10.3390/app8122585, 2018. a
Lorenz, E.: Predictability: does the flap of a butterfly's wing in Brazil set off a tornado in Texas?, in: 139th Annual Meeting of the American Association for the Advancement of Science, 29 December 1972, Cambridge, Massachusetts, USA, Appendix 1, p. 181, https://eapsweb.mit.edu/sites/default/files/Butterfly_1972.pdf (last access: 27 April 2022), 1972. a
Mahesh, A., Walden, V. P., and Warren, S. G.: Radiosonde Temperature Measurements in Strong Inversions: Correction for Thermal Lag Based on an Experiment at the South Pole, J. Atmos. Ocean. Tech., 14, 45–53, https://doi.org/10.1175/1520-0426(1997)014<0045:RTMISI>2.0.CO;2, 1997. a
McRae, G. J.: A Simple Procedure for Calculating Atmospheric Water Vapor
Concentration, JAPCA J. Air Waste Ma., 30, 394–394, https://doi.org/10.1080/00022470.1980.10464362, 1980. a
Momoh, O. D., Sadiku, M. N., and Musa, S. M.: Finite difference analysis of time-dependent spherical problems, in: 2013 Proceedings of IEEE
Southeastcon, 4–7 April 2013, Jacksonville, Florida, USA, 1–4, https://doi.org/10.1109/SECON.2013.6567468, 2013. a, b
National Academies of Sciences, Engineering, and Medicine: The Future of Atmospheric Boundary Layer Observing, Understanding, and Modeling: Proceedings of a Workshop, The National Academies Press, Washington, DC, USA, https://doi.org/10.17226/25138, 2018. a
National Research Council: Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks, Natl. Acad. Press, Washington, D.C.,
https://doi.org/10.17226/12540, 2009. a
Petty, G.: A First Course in Atmospheric Thermodynamics, Sundog Publishing, ISBN 978-0-9729033-2-5, 2008. a
Pillar-Little, E. A., Greene, B. R., Lappin, F. M., Bell, T. M., Segales, A. R., de Azevedo, G. B. H., Doyle, W., Kanneganti, S. T., Tripp, D. D., and Chilson, P. B.: Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO, using the CopterSonde 2 remotely piloted aircraft system in support of the LAPSE-RATE field campaign, Earth Syst. Sci. Data, 13, 269–280, https://doi.org/10.5194/essd-13-269-2021, 2021. a
Pletcher, R., Anderson, D., Tannehill, J., Munipalli, R., and Shankar, V.:
Computational Fluid Mechanics and Heat Transfer, 3rd edn., CRC Press,
https://doi.org/10.1201/9781351124027, 2013. a, b
Reuder, J., Brisset, P., Jonassen, M., Müller, M., and Mayer, S.: The Small Unmanned Meteorological Observer SUMO: A new tool for atmospheric boundary layer research, Meteorol. Z., 18, 141–147,
https://doi.org/10.1127/0941-2948/2009/0363, 2009. a
Saddoughi, S. G. and Veeravalli, S. V.: Local isotropy in turbulent boundary
layers at high Reynolds number, J. Fluid Mech., 268, 333–372,
https://doi.org/10.1017/S0022112094001370, 1994. a
Segales, A. R., Greene, B. R., Bell, T. M., Doyle, W., Martin, J. J.,
Pillar-Little, E. A., and Chilson, P. B.: The CopterSonde: an insight into
the development of a smart unmanned aircraft system for atmospheric boundary
layer research, Atmospheric Measurement Techniques, 13, 2833–2848,
https://doi.org/10.5194/amt-13-2833-2020, 2020. a, b, c, d
Steinhart, J. S. and Hart, S. R.: Calibration curves for thermistors, Deep Sea Research and Oceanographic Abstracts, 15, 497–503, https://doi.org/10.1016/0011-7471(68)90057-0, 1968. a
Tatarski, V. I. and Silverman, R. A.: Wave Propagation in a Turbulent Medium, Phys. Today, 14, 46, https://doi.org/10.1063/1.3057286, 1961.
a
Tsilingiris, P.: Thermophysical and transport properties of humid air at temperature range between 0 and 100 ∘C, Energ. Convers. Manage., 49, 1098–1110, https://doi.org/10.1016/j.enconman.2007.09.015, 2008. a
Waugh, S. M.: The “U-Tube”: An Improved Aspirated Temperature System for Mobile Meteorological Observations, Especially in Severe Weather, J. Atmos. Ocean. Tech, 38, 1477–1489, https://doi.org/10.1175/JTECH-D-21-0008.1, 2021. a
Wildmann, N., Hofsäß, M., Weimer, F., Joos, A., and Bange, J.: MASC – a small Remotely Piloted Aircraft (RPA) for wind energy research, Adv. Sci. Res., 11, 55–61, https://doi.org/10.5194/asr-11-55-2014, 2014a. a
Short summary
The mitigation of undesired contamination, sensor characterization, and signal conditioning and restoration is crucial to improve the reliability of the weather unmanned aerial system (UAS) deliverables. This study presents an overview of the general considerations and procedures to compensate for slow sensor response and other sources of error for temperature and humidity measurements collected using a UAS.
The mitigation of undesired contamination, sensor characterization, and signal conditioning and...
