Articles | Volume 15, issue 7
https://doi.org/10.5194/amt-15-2277-2022
© 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-15-2277-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characteristics of the derived energy dissipation rate using the 1 Hz commercial aircraft quick access recorder (QAR) data
Soo-Hyun Kim
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
Jeonghoe Kim
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
School of Earth and Environmental Sciences, Seoul National University,
Seoul, South Korea
Hye-Yeong Chun
Department of Atmospheric Sciences, Yonsei University, Seoul, South
Korea
Related authors
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
Short summary
Short summary
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.
Ji-Hee Yoo, Hye-Yeong Chun, and Min-Jee Kang
Atmos. Chem. Phys., 23, 10869–10881, https://doi.org/10.5194/acp-23-10869-2023, https://doi.org/10.5194/acp-23-10869-2023, 2023
Short summary
Short summary
The January 2021 sudden stratospheric warming was preceded by unusual double westerly jets with polar stratospheric and subtropical mesospheric cores. This wind structure promotes anomalous dissipation of tropospheric planetary waves between the two maxima, leading to unusually strong shear instability. Shear instability generates the westward-propagating planetary waves with zonal wavenumber 2 in situ, thereby splitting the polar vortex just before the onset.
Sung-Ho Suh, Woonseon Jung, Hong-Il Kim, Eun-Ho Choi, and Jung-Hoon Kim
EGUsphere, https://doi.org/10.5194/egusphere-2023-947, https://doi.org/10.5194/egusphere-2023-947, 2023
Preprint archived
Short summary
Short summary
This study performed the Statistical analysis of the correlation between solid hydrometeor and radar spectrum width according to wind speed that can occur the atmospheric disturbances such as turbulence and wind shear. These features were clearly shown in the Growth Zones where dendrite and needle-like snowflakes are dominant, respectively. This study will help in the field of i) aviation safety, ii) hydrometeor classification, and iii) knowledge about the mechanism of lightning.
Min-Jee Kang and Hye-Yeong Chun
Atmos. Chem. Phys., 21, 9839–9857, https://doi.org/10.5194/acp-21-9839-2021, https://doi.org/10.5194/acp-21-9839-2021, 2021
Short summary
Short summary
In winter 2019/20, the westerly quasi-biennial oscillation (QBO) phase was disrupted again by easterly winds. It is found that strong Rossby waves from the Southern Hemisphere weaken the jet core in early stages, and strong mixed Rossby–gravity waves reverse the wind in later stages. Inertia–gravity waves and small-scale convective gravity waves also provide negative forcing. These strong waves are attributed to an anomalous wind profile, barotropic instability, and slightly strong convection.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, Jung-Hoon Kim, YongHee Lee, and GyuWon Lee
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-100, https://doi.org/10.5194/acp-2021-100, 2021
Preprint withdrawn
Short summary
Short summary
This study examines a strong downslope wind event during ICE-POP 2018 using Doppler lidars, and observations. 3D winds can be well retrieved by
WISSDOM. This is first time to document the mechanisms of strong wind in observational aspect under fine weather. The PGF causing by adiabatic warming and channeling effect are key factors to dominate the strong wind. The values of this study are improving our understanding of the strong wind and increase the predictability of the weather forecast.
Min-Jee Kang, Hye-Yeong Chun, and Rolando R. Garcia
Atmos. Chem. Phys., 20, 14669–14693, https://doi.org/10.5194/acp-20-14669-2020, https://doi.org/10.5194/acp-20-14669-2020, 2020
Short summary
Short summary
In winter 2015/16, the descent of the westerly quasi-biennial oscillation (QBO) jet was interrupted by easterly winds. We find that Rossby–gravity and inertia–gravity waves weaken the jet core in early stages, and small-scale convective gravity waves, as well as horizontal and vertical components of Rossby waves, reverse the wind sign in later stages. The strong negative wave forcing in the tropics results from the enhanced convection, an anomalous wind profile, and barotropic instability.
In-Sun Song, Changsup Lee, Hye-Yeong Chun, Jeong-Han Kim, Geonhwa Jee, Byeong-Gwon Song, and Julio T. Bacmeister
Atmos. Chem. Phys., 20, 7617–7644, https://doi.org/10.5194/acp-20-7617-2020, https://doi.org/10.5194/acp-20-7617-2020, 2020
Short summary
Short summary
A modeling study on the effects of propagation of atmospheric gravity waves is carried out for the 2009 sudden stratospheric warming (SSW) event. It is found that gravity-wave-induced momentum fluxes are significantly affected by horizontal refraction and the Earth's curvature effects. Gravity wave convergence and effects of ray geometry also have some impact. In the evolution of the SSW, significantly enhanced momentum fluxes are likely to change nonlocally nearby large-scale vortex structures.
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
Short summary
Short summary
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.
Neal Butchart, James A. Anstey, Kevin Hamilton, Scott Osprey, Charles McLandress, Andrew C. Bushell, Yoshio Kawatani, Young-Ha Kim, Francois Lott, John Scinocca, Timothy N. Stockdale, Martin Andrews, Omar Bellprat, Peter Braesicke, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Mikhail Dobrynin, Rolando R. Garcia, Javier Garcia-Serrano, Lesley J. Gray, Laura Holt, Tobias Kerzenmacher, Hiroaki Naoe, Holger Pohlmann, Jadwiga H. Richter, Adam A. Scaife, Verena Schenzinger, Federico Serva, Stefan Versick, Shingo Watanabe, Kohei Yoshida, and Seiji Yukimoto
Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, https://doi.org/10.5194/gmd-11-1009-2018, 2018
Short summary
Short summary
This paper documents the numerical experiments to be used in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi), which was set up to improve the representation of the QBO and tropical stratospheric variability in global climate models.
Byeong-Gwon Song and Hye-Yeong Chun
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-729, https://doi.org/10.5194/acp-2016-729, 2016
Revised manuscript not accepted
Quang Thai Trinh, Silvio Kalisch, Peter Preusse, Manfred Ern, Hye-Yeong Chun, Stephen D. Eckermann, Min-Jee Kang, and Martin Riese
Atmos. Chem. Phys., 16, 7335–7356, https://doi.org/10.5194/acp-16-7335-2016, https://doi.org/10.5194/acp-16-7335-2016, 2016
Short summary
Short summary
Convection is an important source of atmospheric gravity waves (GWs). In this work, scales of convective GWs seen by limb sounders were first defined based on observed spectral information. Interactions of these waves with the background were considered. Long-scale convective GWs addressed by this approach showed significant importance in driving the QBO. Zonal mean of GW momentum flux and its vertical gradients are in good agreement with respective observations provided by limb sounders.
Young-Ha Kim, Hye-Yeong Chun, Sang-Hun Park, In-Sun Song, and Hyun-Joo Choi
Atmos. Chem. Phys., 16, 4799–4815, https://doi.org/10.5194/acp-16-4799-2016, https://doi.org/10.5194/acp-16-4799-2016, 2016
Short summary
Short summary
We investigated the characteristics of atmospheric gravity waves that are generated in a baroclinic life cycle simulation using a high-resolution global model. We analysed the spatiotemporal scales, vertical-propagation aspects, and sources of the gravity waves as well as their phase-velocity spectrum. The wave characteristics investigated in this study are crucial information for parameterizing gravity waves in large-scale models.
Y.-H. Kim and H.-Y. Chun
Atmos. Chem. Phys., 15, 6577–6587, https://doi.org/10.5194/acp-15-6577-2015, https://doi.org/10.5194/acp-15-6577-2015, 2015
Short summary
Short summary
The momentum forcing of the stratospheric quasi-biennial oscillation (QBO) by equatorial waves is estimated using recent reanalysis data sets. The Kelvin wave produces primary forcing of the QBO in the easterly-to-westerly transition phase below 30hPa, whereas mesoscale gravity waves produce larger forcing than the Kelvin wave above 30hPa. Still, the recent reanalyses underestimate the forcing by the large-scale equatorial waves.
Q. T. Trinh, S. Kalisch, P. Preusse, H.-Y. Chun, S. D. Eckermann, M. Ern, and M. Riese
Atmos. Meas. Tech., 8, 1491–1517, https://doi.org/10.5194/amt-8-1491-2015, https://doi.org/10.5194/amt-8-1491-2015, 2015
J. Y. Jia, P. Preusse, M. Ern, H.-Y. Chun, J. C. Gille, S. D. Eckermann, and M. Riese
Ann. Geophys., 32, 1373–1394, https://doi.org/10.5194/angeo-32-1373-2014, https://doi.org/10.5194/angeo-32-1373-2014, 2014
S. H. Kim, H.-Y. Chun, and W. Jang
Atmos. Chem. Phys., 14, 3175–3182, https://doi.org/10.5194/acp-14-3175-2014, https://doi.org/10.5194/acp-14-3175-2014, 2014
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Number- and size-controlled rainfall regimes in the Netherlands: physical reality or statistical mirage?
The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) – Part 2: First measurements of the emissivity of water in the far-infrared
Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics
Hybrid instrument network optimization for air quality monitoring
Role of time-averaging of eddy covariance fluxes on water use efficiency dynamics of Maize crop
Objective identification of pressure wave events from networks of 1 Hz, high-precision sensors
Adjustment of 1 min rain gauge time series using co-located drop size distribution and wind speed measurements
Estimating turbulent energy flux vertical profiles from uncrewed aircraft system measurements: exemplary results for the MOSAiC campaign
Gap filling of turbulent heat fluxes over rice–wheat rotation croplands using the random forest model
Estimation of raindrop size distribution and rain rate with infrared surveillance camera in dark conditions
Estimates of the spatially complete, observational-data-driven planetary boundary layer height over the contiguous United States
Detection of turbulence occurrences from temperature, pressure, and position measurements under superpressure balloons
Inferring surface energy fluxes using drone data assimilation in large eddy simulations
Raindrop size distribution (DSD) during the passage of tropical cyclone Nivar: effect of measuring principle and wind on DSDs and retrieved rain integral and polarimetric parameters from impact and laser disdrometers
Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC)
Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC
Considerations for improving data quality of thermo-hygrometer sensors on board unmanned aerial systems for planetary boundary layer research
Low-level buoyancy as a tool to understand boundary layer transitions
Estimating vertical wind power density using tower observation and empirical models over varied desert steppe terrain in northern China
Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems
Wind speed and direction estimation from wave spectra using deep learning
Options to correct local turbulent flux measurements for large-scale fluxes using an approach based on large-eddy simulation
Global ensemble of temperatures over 1850–2018: quantification of uncertainties in observations, coverage, and spatial modeling (GETQUOCS)
Reconstruction of the mass and geometry of snowfall particles from multi-angle snowflake camera (MASC) images
A new zenith hydrostatic delay model for real-time retrievals of GNSS-PWV
Sampling error in aircraft flux measurements based on a high-resolution large eddy simulation of the marine boundary layer
Separation of convective and stratiform precipitation using polarimetric radar data with a support vector machine method
An approach to minimize aircraft motion bias in multi-hole probe wind measurements made by small unmanned aerial systems
Interpolation uncertainty of atmospheric temperature profiles
Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification
An improved post-processing technique for automatic precipitation gauge time series
Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR)
Atmospheric condition identification in multivariate data through a metric for total variation
Identifying persistent temperature inversion events in a subalpine basin using radon-222
Evaluation of wake influence on high-resolution balloon-sonde measurements
Improving the mean and uncertainty of ultraviolet multi-filter rotating shadowband radiometer in situ calibration factors: utilizing Gaussian process regression with a new method to estimate dynamic input uncertainty
Empirical high-resolution wind field and gust model in mountainous and hilly terrain based on the dense WegenerNet station networks
Performance of the FMI cosine error correction method for the Brewer spectral UV measurements
Computational efficiency for the surface renewal method
Raindrop fall velocities from an optical array probe and 2-D video disdrometer
Novel approaches to estimating the turbulent kinetic energy dissipation rate from low- and moderate-resolution velocity fluctuation time series
Smoothing data series by means of cubic splines: quality of approximation and introduction of a repeating spline approach
Data-driven clustering of rain events: microphysics information derived from macro-scale observations
Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera
Dust opacities inside the dust devil column in the Taklimakan Desert
Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring
Ensemble mean density and its connection to other microphysical properties of falling snow as observed in Southern Finland
An automated nowcasting model of significant instability events in the flight terminal area of Rio de Janeiro, Brazil
Retrieving atmospheric turbulence information from regular commercial aircraft using Mode-S and ADS-B
An automatic precipitation-phase distinction algorithm for optical disdrometer data over the global ocean
Marc Schleiss
Atmos. Meas. Tech., 17, 4789–4802, https://doi.org/10.5194/amt-17-4789-2024, https://doi.org/10.5194/amt-17-4789-2024, 2024
Short summary
Short summary
Research is conducted to identify special rainfall patterns in the Netherlands using multiple types of rainfall sensors. A total of eight potentially unique events are analyzed, considering both the number and size of raindrops. However, no clear evidence supporting the existence of a special rainfall regime could be found. The results highlight the challenges in experimentally confirming well-established theoretical ideas in the field of precipitation sciences.
Laura Warwick, Jonathan E. Murray, and Helen Brindley
Atmos. Meas. Tech., 17, 4777–4787, https://doi.org/10.5194/amt-17-4777-2024, https://doi.org/10.5194/amt-17-4777-2024, 2024
Short summary
Short summary
We describe a method for measuring the emissivity of natural surfaces using data from the new Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument. We demonstrate our method by making measurements of the emissivity of water. We then compare our results to the emissivity predicted using a model and find good agreement. The observations from FINESSE are novel because they allow us to determine surface emissivity at longer wavelengths than have been routinely measured before.
Jairo M. Valdivia, José Luis Flores-Rojas, Josep J. Prado, David Guizado, Elver Villalobos-Puma, Stephany Callañaupa, and Yamina Silva-Vidal
Atmos. Meas. Tech., 17, 2295–2316, https://doi.org/10.5194/amt-17-2295-2024, https://doi.org/10.5194/amt-17-2295-2024, 2024
Short summary
Short summary
In this study, we explored hailstorms in the Central Andes of Peru. We used historical records and radar measurements to understand the frequency, timing, and characteristics of these hail events. Our research found a trend of decreasing hail frequency, probably due to anthropogenic climate change. Understanding these weather patterns is critical for local communities, as it can help improve weather forecasts and manage risks related to these potentially destructive events.
Nishant Ajnoti, Hemant Gehlot, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 17, 1651–1664, https://doi.org/10.5194/amt-17-1651-2024, https://doi.org/10.5194/amt-17-1651-2024, 2024
Short summary
Short summary
This research focuses on the optimal placement of hybrid instruments (sensors and monitors) to maximize satisfaction function considering population, PM2.5 concentration, budget, and other factors. Two algorithms are developed in this study: a genetic algorithm and a greedy algorithm. We tested these algorithms on various regions. The insights of this work aid in quantitative placement of air quality monitoring instruments in large cities, moving away from ad hoc approaches.
Arun Rao Karimindla, Shweta Kumari, Saipriya SR, Syam Chintala, and BVN Phanindra Kambhammettu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-253, https://doi.org/10.5194/amt-2023-253, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study is aimed at investigating the role of the averaging period of Eddy Covariance (EC) fluxes on EBR and further propagation into WUE dynamics. Application was demonstrated on a Maize field considering EC flux data. We obtained that the time averages of EC fluxes that yield the most effective EBR are at 45 min and 60 min. The 30-min averaging period proves insufficient for capturing low-frequency fluxes. Time-averaging of EC fluxes needs to be performed based on crop growth stage.
Luke R. Allen, Sandra E. Yuter, Matthew A. Miller, and Laura M. Tomkins
Atmos. Meas. Tech., 17, 113–134, https://doi.org/10.5194/amt-17-113-2024, https://doi.org/10.5194/amt-17-113-2024, 2024
Short summary
Short summary
We present a data set of high-precision surface air pressure observations and a method for detecting wave signals from the time series of pressure. A wavelet-based method is used to find wave signals at specific times and wave periods. From networks of pressure sensors spaced tens of kilometers apart, the wave phase speed and direction are estimated. Examples of wave events and their meteorological context are shown using radar data, weather balloon data, and other surface weather observations.
Arianna Cauteruccio, Mattia Stagnaro, Luca G. Lanza, and Pak-Wai Chan
Atmos. Meas. Tech., 16, 4155–4163, https://doi.org/10.5194/amt-16-4155-2023, https://doi.org/10.5194/amt-16-4155-2023, 2023
Short summary
Short summary
Adjustments for the wind-induced bias of traditional rainfall gauges are applied to data from the Hong Kong Observatory using numerical simulation results. An optical disdrometer allows us to infer the collection efficiency of the rainfall gauge. Due to the local climatology, adjustments are limited but result in a significant amount of available freshwater resources that would be missing from the calculated hydrological budget of the region should the adjustments be neglected.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
Short summary
Short summary
This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Jianbin Zhang, Zexia Duan, Shaohui Zhou, Yubin Li, and Zhiqiu Gao
Atmos. Meas. Tech., 16, 2197–2207, https://doi.org/10.5194/amt-16-2197-2023, https://doi.org/10.5194/amt-16-2197-2023, 2023
Short summary
Short summary
In this paper, we used a random forest model to fill the observation gaps of the fluxes measured during 2015–2019. We found that the net radiation was the most important input variable. And we justified the reliability of the model. Further, it was revealed that the model performed better after relative humidity was removed from the input. Lastly, we compared the results of the model with those of three other machine learning models, and we found that the model outperformed all of them.
Jinwook Lee, Jongyun Byun, Jongjin Baik, Changhyun Jun, and Hyeon-Joon Kim
Atmos. Meas. Tech., 16, 707–725, https://doi.org/10.5194/amt-16-707-2023, https://doi.org/10.5194/amt-16-707-2023, 2023
Short summary
Short summary
Our study addresses raindrop size distribution and rain rate by extracting rain streaks using a k-nearest-neighbor-based algorithm, estimating rainfall intensity using raindrop size distribution based on physical optics analysis, and verifying the estimated raindrop size distribution using a disdrometer. Experimentation demonstrated the possibility of estimating an image-based raindrop size distribution and rain rate obtained based on such low-cost equipment in dark conditions.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
Short summary
Short summary
Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Richard Wilson, Clara Pitois, Aurélien Podglajen, Albert Hertzog, Milena Corcos, and Riwal Plougonven
Atmos. Meas. Tech., 16, 311–330, https://doi.org/10.5194/amt-16-311-2023, https://doi.org/10.5194/amt-16-311-2023, 2023
Short summary
Short summary
Strateole-2 is an French–US initiative designed to study atmospheric events in the tropical upper troposphere–lower stratosphere. In this work, data from several superpressure balloons, capable of staying aloft at an altitude of 18–20 km for over 3 months, were used. The present article describes methods to detect the occurrence of atmospheric turbulence – one efficient process impacting the properties of the atmosphere composition via stirring and mixing.
Norbert Pirk, Kristoffer Aalstad, Sebastian Westermann, Astrid Vatne, Alouette van Hove, Lena Merete Tallaksen, Massimo Cassiani, and Gabriel Katul
Atmos. Meas. Tech., 15, 7293–7314, https://doi.org/10.5194/amt-15-7293-2022, https://doi.org/10.5194/amt-15-7293-2022, 2022
Short summary
Short summary
In this study, we show how sparse and noisy drone measurements can be combined with an ensemble of turbulence-resolving wind simulations to estimate uncertainty-aware surface energy exchange. We demonstrate the feasibility of this drone data assimilation framework in a series of synthetic and real-world experiments. This new framework can, in future, be applied to estimate energy and gas exchange in heterogeneous landscapes more representatively than conventional methods.
Basivi Radhakrishna
Atmos. Meas. Tech., 15, 6705–6722, https://doi.org/10.5194/amt-15-6705-2022, https://doi.org/10.5194/amt-15-6705-2022, 2022
Short summary
Short summary
Raindrop size distributions (DSDs) measured by various types of disdrometers are different in the same environmental conditions. The mass-weighted mean diameter (Dm) measured from JWD is larger, and ZDR is smaller than LPM and PARSIVEL due to the resonance effect at X-band frequency. The effect of wind on DSD measured by various disdrometers is not uniform in different regions of a tropical cyclone.
Katarzyna Ośródka, Irena Otop, and Jan Szturc
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
Short summary
Short summary
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
Atmos. Meas. Tech., 15, 4001–4022, https://doi.org/10.5194/amt-15-4001-2022, https://doi.org/10.5194/amt-15-4001-2022, 2022
Short summary
Short summary
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.
Antonio R. Segales, Phillip B. Chilson, and Jorge L. Salazar-Cerreño
Atmos. Meas. Tech., 15, 2607–2621, https://doi.org/10.5194/amt-15-2607-2022, https://doi.org/10.5194/amt-15-2607-2022, 2022
Short summary
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.
Francesca M. Lappin, Tyler M. Bell, Elizabeth A. Pillar-Little, and Phillip B. Chilson
Atmos. Meas. Tech., 15, 1185–1200, https://doi.org/10.5194/amt-15-1185-2022, https://doi.org/10.5194/amt-15-1185-2022, 2022
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Atmos. Meas. Tech., 14, 7103–7121, https://doi.org/10.5194/amt-14-7103-2021, https://doi.org/10.5194/amt-14-7103-2021, 2021
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Bodini, N., Lundquist, J. K., Krishnamurthy, R., Pekour, M., Berg, L. K., and Choukulkar, A.: Spatial and temporal variability of turbulence dissipation rate in complex terrain, Atmos. Chem. Phys., 19, 4367–4382, https://doi.org/10.5194/acp-19-4367-2019, 2019.
Bramberger, M., Dörnbrack, A., Wilms, H., Gemsa, S., Raynor, K., and
Sharman, R. D.: Vertically propagating mountain wave – A hazard for high-
flying aircraft?, J. Appl. Meteor. Climatol., 57, 1957–1975,
https://doi.org/10.1175/JAMC-D-17-0340.1, 2018.
Champagne, F. H., Friehe, C. A., Larue, J. C., and Wynagaard, J. C.: Flux
measurements, flux estimation techniques, and fine-scale turbulence
measurements in the unstable surface layer over land, J. Atmos. Sci., 34,
515–530, https://doi.org/10.1175/1520-0469(1977)034<0515:FMFETA>2.0.CO;2, 1977.
Cho, J. Y. N. and Lindborg, E.: Horizontal velocity structure functions in
the upper troposphere and lower stratosphere: 1. Observations, J. Geophys.
Res., 106, 10223–10232, https://doi.org/10.1029/2000JD900814, 2001.
Cho, J. Y. N., Newell, R. E., Anderson, B. E., Barrick, J. D. W., and
Thornhill, K. L.: Characterizations of tropospheric turbulence and stability
layers from aircraft observations, J. Geophys. Res., 108, 8784,
https://doi.org/10.1029/2002JD002820, 2003.
Chun, H.-Y. and Baik, J.-J.: Momentum flux by thermally induced internal
gravity waves and its approximation for large-scale models, J. Atmos. Sci.,
55, 3299–3310,
https://doi.org/10.1175/1520-0469(1998)055<3299:MFBTII>2.0.CO;2, 1998.
Clark, T. L., Hall, W. D., Kerr, R. M., Middleton, D., Radke, L., Ralph, F.
M., Neiman, P. J., and Levinson, D.: Origins of aircraft-damaging clear-air
turbulence during the 9 December 1992 Colorado downslope windstorm:
Numerical simulations and comparison with observations, J. Atmos. Sci., 57,
1105–1131, https://doi.org/10.1175/1520-0469(2000)057<1105:OOADCA>2.0.CO;2, 2000.
Cornman, L. B.: Airborne in situ measurements of turbulence, in: Aviation
Turbulence: Processes, Detection, Prediction, edited by: Sharman, R. D. and
Lane, T. D., Springer, Switzerland, 97–120,
https://doi.org/10.1007/978-3-319-23630-8_5, 2016.
Drüe, C. and Heinemann, G.: A review and practical guide to in-flight
calibration for aircraft turbulence sensors, J. Atmos. Ocean. Technol., 30,
2820–2837, https://doi.org/10.1175/JTECH-D-12-00103.1, 2013.
Dutton, J. A. and Panofsky, H. A.: Clear air turbulence: A mystery may be
unfolding, Science, 167, 937–944,
https://doi.org/10.1126/science.167.3920.937, 1970.
Ellrod, G. P. and Knapp, D. I.: An objective clear-air turbulence
forecasting technique: Verification and operational use, Weather Forecast.,
7, 150–165,
https://doi.org/10.1175/1520-0434(1992)007<0150:AOCATF>2.0.CO;2, 1992.
Ellrod, G. P. and Knox, J. A.: Improvements to an operational clear-air
turbulence diagnostic index by addition of a divergence trend term, Weather
Forecast., 25, 789–798, https://doi.org/10.1175/2009WAF2222290.1, 2010.
Frehlich, R.: Laser scintillation measurements of the temperature spectrum
in the atmospheric surface layer, J. Atmos. Sci., 49, 1494–1509,
https://doi.org/10.1175/1520-0469(1992)049<1494:LSMOTT>2.0.CO;2, 1992.
Frehlich, R. and Sharman, R. D.: Estimates of turbulence from numerical
weather prediction model output with applications to turbulence diagnosis
and data assimilation, Mon. Weather Rev., 132, 2308–2324,
https://doi.org/10.1175/1520-0493(2004)132<2308:EOTFNW>2.0.CO;2, 2004.
Gao, F. and Han, L.: Implementing the Nelder-Mead simplex algorithm with
adaptive parameters, Comput. Optim. Appl., 51, 259–277,
https://doi.org/10.1007/s10589-010-9329-3, 2012.
Gill, P. G.: Objective verification of World Area Forecast Centre clear air
turbulence forecasts, Meteor. Appl., 21, 3–11,
https://doi.org/10.1002/met.1288, 2014.
Gultepe, I., Sharman, R. D., Williams, P. D., Zhou, B., Ellrod, G., Minnis,
P., Trier, S., Griffin, S., Yum, S. S., Gharabaghi, B., Feltz, W., Temimi,
M., Pu, Z., Storer, L. N., Kneringer, P., Weston, M. J., Chuang, H.-Y.,
Thobois, L., Dimri, A. P., Dietz, S. J., França, G. B., Almeida, M. V.,
and Neto, F. L. A.: A review of high impact weather for aviation
meteorology, Pure Appl. Geophys., 176, 1869–1921,
https://doi.org/10.1007/s00024-019-02168-6, 2019.
Haverdings, H. and Chan, P. W.: Quick access recorder data analysis for
windshear and turbulence studies, J. Aircr., 47, 1443–1446,
https://doi.org/10.2514/1.46954, 2010.
Hersbach, H., Bell, B., Berrisford, P., et al.: The ERA5 global reanalysis, Q. J. Roy.
Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hinze, J. O.: Turbulence, 2nd Edition, McGraw-Hill, New York, 790 pp., 1975.
Hoblit, F. M. (Ed.): Gust Loads on Aircraft: Concepts and Applications, AIAA
Education Series, American Institute of Aeronautics and Asctronautics,
Washington, 306 pp., 1988.
International Civil Aviation Organization: Meteorological service for
international air navigation: Annex 3 to the Convention on International
Civil Aviation, 14th ed. ICAO International Standards and Recommended
Practices Tech. Rep., ICAO, Montreal, 128 pp., 2001.
International Civil Aviation Organization: Meteorological service for
international air navigation: Annex 3 to the Convention on International
Civil Aviation, 17th ed. ICAO International Standards and Recommended
Practices Tech. Rep., ICAO, Montreal, 206 pp., 2010.
Kim, J., Kim, J.-H., and Sharman, R. D.: Characteristics of energy
dissipation rate observed from the high-frequency sonic anemometer at
Boseong, South Korea, Atmosphere, 12, 837,
https://doi.org/10.3390/atmos12070837, 2021.
Kim, J.-H. and Chun, H.-Y.: A numerical study of clear-air turbulence (CAT)
encounters over South Korea on 2 April 2007, J. Appl. Meteor. Climatol., 49,
2381–2403, https://doi.org/10.1175/2010JAMC2449.1, 2010.
Kim, J.-H. and Chun, H.-Y.: Statistics and possible sources of aviation
turbulence over South Korea, J. Appl. Meteor. Climatol., 50, 311–324,
https://doi.org/10.1175/2010JAMC2492.1, 2011.
Kim, J.-H. and Chun, H.-Y.: A numerical simulation of convectively induced
turbulence above deep convection, J. Appl. Meteor. Climatol., 51, 1180–1200,
https://doi.org/10.1175/JAMC-D-11-0140.1, 2012.
Kim, J.-H., Chun, H.-Y., Sharman, R. D., and Keller, T. L.: Evaluations of
upper-level turbulence diagnostics performance using the Graphical
Turbulence Guidance (GTG) system and pilot reports (PIREPs) over East Asia,
J. Appl. Meteor. Climatol., 50, 1936–1951,
https://doi.org/JAMC-D-10-05017.1, 2011.
Kim, J.-H., Chan, W. N., Sridhar, B., and Sharman, R. D.: Combined winds and
turbulence prediction system for automated air-traffic management
applications, J. Appl. Meteor. Climatol., 54, 766–784,
https://doi.org/10.1175/JAMC-D-14-0216.1, 2015.
Kim, J.-H., Sharman, R. D., Strahan, M., Scheck, J. W., Bartholomew, C.,
Cheung, J. C., Buchanan, P., and Gait, N.: Improvements in nonconvective
aviation turbulence prediction for the world area forecast system, B.
Am. Meteorol. Soc., 98, 2295–2311, https://doi.org/10.1175/BAMS-D-17-0117.1,
2018.
Kim, J.-H., Sharman, R. D., Benjamin, S. G., Brown, J. M., Park, S.-H., and
K. J. B.: Improvement of mountain-wave turbulence forecasts in NOAA's Rapid
Refresh (RAP) model with the hybrid vertical coordinate system, Weather
Forecast., 34, 773–780, https://doi.org/10.1175/WAF-D-18-0187.1, 2019.
Kim, J.-H., Park, J.-R., Kim, S.-H., Kim, J., Lee, E., Baek, S., and Lee,
G.: A detection of convectively induced turbulence using in situ aircraft
and radar spectral width data, Remote Sens., 13, 726,
https://doi.org/10.3390/rs13040726, 2021.
Kim, S.-H. and Chun, H.-Y.: Aviation turbulence encounters detected from
aircraft observations: Spatiotemporal characteristics and application to
Korean aviation turbulence guidance, Meteor. Appl., 23, 594–604,
https://doi.org/10.1002/met.1581, 2016.
Kim, S.-H., Chun, H.-Y., and Chan, P. W.: Comparison of turbulence
indicators obtained from in situ flight data, J. Appl. Meteor. Climatol.,
56, 1609–1623, https://doi.org/10.1175/JAMC-D-16-0291.1, 2017.
Kim, S.-H., Chun, H.-Y., Sharman, R. D., and Trier, S. B.: Development of
near-cloud turbulence diagnostics based on a convective gravity wave drag
parameterization, J. Appl. Meteor. Climatol., 58, 1725–1750,
https://doi.org/10.1175/JAMC-D-18-0300.1, 2019.
Kim, S.-H., Chun, H.-Y., Kim, J.-H., Sharman, R. D., and Strahan, M.: Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR), Atmos. Meas. Tech., 13, 1373–1385, https://doi.org/10.5194/amt-13-1373-2020, 2020.
Kim, S.-H., Chun, H.-Y., Lee, D.-B., Kim, J.-H., and Sharman, R. D.:
Improving numerical weather prediction-based near-cloud aviation turbulence
forecasts by diagnosing convective gravity wave breaking, Weather Forecast.,
36, 1735–1757, https://doi.org/10.1175/WAF-D-20-0213.1, 2021.
Knapp, K. R., Ansari, S., Bain, C. L., Bourassa, M. A., Dickinson, M. J.,
Funk, C., Helms, C. N., Hennon, C. C., Holmes, C. D., Huffman, G. J.,
Kossin, J. P., Lee, H.-T., Loew, A., and Magnusdottir, G.: Globally gridded
satellite observations for climate studies, B. Am. Meteor. Soc., 92,
893–907, https://doi.org/10.1175/2011BAMS3039.1, 2011.
Knox, J. A., McCann, D. W., and Willams, P. D.: Application of the
Lighthill-Ford theory of spontaneous imbalance to clear-air turbulence
forecasting, J. Atmos. Sci. 65, 3292–3304,
https://doi.org/10.1175/2008JAS2477.1, 2008.
Ko, H.-C., Chun, H.-Y., Wilson, R., and Geller, M. A.: Characteristics of
atmospheric turbulence retrieved from high vertical-resolution radiosonde
data in the United States, J. Geophys. Res.-Atmos., 124, 7553–7579,
https://doi.org/10.1029/2019JD030287, 2019.
Koch, S. E., Jamison, B. D., Lu, C., Smith, T. L., Tollerud, E. I., Girz,
C., Wang, N., Lane, T. P., Shapiro, M. A., Parrish, D. D., and Cooper, O.
R.: Turbulence and gravity waves within an upper-level front, J. Atmos.
Sci., 62, 3885–3908, https://doi.org/10.1175/JAS3674.1, 2005.
Kolmogorov, A. N.: The local structure of turbulence in incompressible
viscous fluid for very large Reynolds numbers, Dokl. Akad. Nauk SSSR, 30,
301–305, 1941.
Kopeć, J. M., Kwiatkowski, K., de Haan, S., and Malinowski, S. P.: Retrieving atmospheric turbulence information from regular commercial aircraft using Mode-S and ADS-B, Atmos. Meas. Tech., 9, 2253–2265, https://doi.org/10.5194/amt-9-2253-2016, 2016.
Krozel, J. A. and Sharman, R. D.: Remote Detection of Turbulence via ADS-B,
AIAA Guidance, Navigation, and Control Conference, AIAA 2015-1547, AIAA
SciTech, https://doi.org/10.2514/6.2015-1547, 2015.
Lane, T. P. and Sharman, R. D.: Some influences of background flow
conditions on the generation of turbulence due to gravity wave breaking
above deep convection, J. Appl. Meteor. Climatol., 47, 2777–2796,
https://doi.org/10.1175/2008JAMC1787.1, 2008.
Lane, T. P., Sharman, R. D., Clark, T. L., and Hsu, H.-M.: An investigation
of turbulence generation mechanisms above deep convection, J. Atmos. Sci.,
60, 1297–1321, https://doi.org/10.1175/1520-0469(2003)60<1297:AIOTGM>2.0.CO;2, 2003.
Lane, T. P., Doyle, J. D., Plougonven, R., Shapiro, M. A., and Sharman, R.
D.: Observations and numerical simulations of inertia-gravity waves and
shearing instabilities in the vicinity of a jet stream, J. Atmos. Sci., 61,
2692–2706, https://doi.org/10.1175/JAS3305.1, 2004.
Lane, T. P., Doyle, J. D., Sharman, R. D., Shapiro, M. A., and Watson, C.
D.: Statistics and dynamics of aircraft encounters of turbulence over
Greenland, Mon. Weather Rev., 137, 2687–2702,
https://doi.org/10.1175/2009MWR2878.1, 2009.
Lane, T. P., Sharman, R. D., Trier, S. B., Fovell, R. G., and Williams, J.
K.: Recent advances in the understanding of near-cloud turbulence, B.
Am. Meteorol. Soc., 93, 499–515, https://doi.org/10.1175/BAMS-D-11-00062.1,
2012.
Lee, S. H., Williams, P. D., and Frame, T. H.: Increased shear in the North
Atlantic upper-level jet stream over the past four decades, Nature, 572,
639–642, https://doi.org/10.1038/s41586-019-1465-z, 2019.
Lenschow, D. H.: The measurement of air velocity and temperature using the
NCAR Buffalo aircraft measuring system, NCAR Tech. Note EDD-74, NCAR,
Boulder, Colorado, 39 pp., 1972.
Mann, J.: The spatial structure of neutral atmospheric surface layer
turbulence, J. Fluid Mech., 273, 141–168,
https://doi.org/10.1017/S0022112094001886, 1994:
Meneguz, E., Wells, H., and Turp, D.: An automated system to quantify
aircraft encounters with convectively induced turbulence over Europe and the
Northeast Atlantic, J. Appl. Meteor. Climatol., 55, 1077–1089,
https://doi.org/10.1175/JAMC-D-15-0194.1, 2016.
Moré, J. J.: The Levenberg-Marquardt algorithm: Implementation and
theory, in: Numerical analysis edited by: Waston, G. A., Springer Berlin
Heidelberg, Berlin, Heidelberg, 105–116, 1978.
Muñoz-Esparza, D., Sharman, R. D., and Lundquist, J. K.: Turbulence
dissipation rate in the atmospheric boundary layer: observations and WRF
mesoscale modelling during the XPIA field campaign, Mon. Weather Rev., 146,
351–371, https://doi.org/10.1175/MWR-D-17-0186.1, 2018.
Nastrom, G. D. and Gage, K. S.: A climatology of atmospheric wavenumber
spectra of wind and temperature observed by commercial aircraft, J. Atmos.
Sci., 42, 950–960, https://doi.org/10.1175/1520-0469(1985)042<0950:ACOAWS>2.0.CO;2, 1985.
Oncley, S. P., Friehe, C. A., Larue, J. C., Businger, J. A., Itsweire, E.
C., and Chang, S. S.: Surface-layer fluxes, profiles, and turbulence
measurements over uniform terrain under near-neutral conditions, J. Atmos.
Sci., 53, 1029–1044, https://doi.org/10.1175/1520-0469(1996)053<1029:SLFPAT>2.0.CO;2, 1996.
Pearson, J. M. and Sharman, R. D.: Prediction of energy dissipation rates
for aviation turbulence: Part II: Nowcasting convective and nonconvective
turbulence, J. Appl. Meteor. Climatol., 56, 339–351,
https://doi.org/10.1175/JAMC-D-16-0312.1, 2017.
Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T.:
Numerical Recipes: The Art of Scientific Computing, 2nd ed. Cambridge
University Press, 963 pp., 1992.
Schwartz, B.: The quantitative use of PIREPs in developing aviation weather
guidance products, Weather Forecast., 11, 372–384,
https://doi.org/10.1175/1520-0434(1996)011<0372:TQUOPI>2.0.CO;2, 1996.
Sharman, R. D. and Lane, T. P. (Eds.): Aviation Turbulence: Processes,
Detection, Prediction, Springer, Switzerland, 523 pp.,
https://doi.org/10.1007/978-3-319-23630-8, 2016.
Sharman, R. D. and Pearson, J. M.: Prediction of energy dissipation rates
for aviation turbulence. Part I: Forecasting nonconvective turbulence, J.
Appl. Meteor. Climatol., 56, 317–337,
https://doi.org/10.1175/JAMC-D-16-0205.1, 2017.
Sharman, R. D., Doyle, J. D., and Shapiro, M. A.: An investigation of a
commercial aircraft encounter with severe clear-air turbulence over western
Greenland, J. Appl. Meteor. Climatol., 51, 42–53,
https://doi.org/JAMC-D-11-044.1, 2012.
Sharman, R. D., Tebaldi, C., Wiener, G., and Wolff, J.: An integrated
approach to mid- and upper-level turbulence forecasting, Weather Forecast.,
21, 268–287, https://doi.org/10.1175/WAF924.1, 2006.
Sharman, R. D., Cornman, L. B., Meymaris, G., Pearson, J. M., and Farrar,
T.: Description and derived climatologies of automated in situ
eddy-dissipation-rate reports of atmospheric turbulence, J. Appl. Meteor.
Climatol., 53, 1416–1432, https://doi.org/10.1175/JAMC-D-13-0329.1, 2014.
Storer, L. N., Gill, P. G., and Williams, P. D.: Multi-model ensemble
predictions of aviation turbulence, Meteor. Appl., 26, 416–428,
https://doi.org/10.1002/met.1772, 2019.
Strauss, L., Serafin, S., Haimov, S., and Grubišić, V.: Turbulence
in breaking mountain waves and atmospheric rotors estimated from airborne in
situ and Doppler radar measurements, Q. J. Roy. Meteorol. Soc., 141,
3207–3225, https://doi.org/10.1002/qj.2604, 2015.
Trier, S. B. and Sharman, R. D.: Trapped gravity waves and their
association with turbulence in a large thunderstorm anvil during PECAN, Mon.
Weather Rev., 146, 3031–3052, https://doi.org/10.1175/MWR-D-18-0152.1, 2018.
Trier, S. B., Sharman, R. D., and Lane, T. P.: Influences of moist
convection on a cold-season outbreak of clear-air turbulence (CAT), Mon.
Weather Rev., 140, 2477–2496, https://doi.org/10.1175/MWR-D-11-00353.1, 2012.
Truscott, B. S.: EUMETNET AMDAR AAA AMDAR software developments – Technical
Specification, Doc. Ref. E_AMDAR/TSC/003, Met Office, Exeter,
UK, 18 pp., 2000.
von Kármán, T.: Progress in the statistical theory of turbulence.
P. Natl. Acad. Sci. USA, 34, 530–539,
https://doi.org/10.1073/pnas.34.11530, 1948.
Williams, A. and Marcotte, D.: Wind measurements on a maneuvering
twin-engine turboprop aircraft accounting for flow distortion, J. Atmos.
Ocean. Technol., 17, 795–810,
https://doi.org/10.1175/1520-0426(2000)017<0795:WMOAMT>2.0.CO;2, 2000.
Williams, J. K. and Meymaris, G.: Remote turbulence detection using
ground-based doppler weather radar, in: Aviation Turbulence: Processes,
Detection, Prediction, edited by: Sharman, R. D. and Lane, T. D., Springer,
Switzerland, 149–177,
https://doi.org/10.1007/978-3-319-23630-8_7, 2016.
Williams, P. D. and Joshi, M. M.: Intensification of winter transatlantic
aviation turbulence in response to climate change, Nat. Clim. Change, 3,
644–648, https://doi.org/10.1038/nclimate1866, 2013.
World Meteorological Organization: Aircraft meteorological data relay
(AMDAR) reference manual, WMO 958, 80 pp., available at:
https://library.wmo.int/doc_num.php?explnum_id=9026 (last access: 9 April 2022), 2003.
Wyngaard, J. and Coté, O.: The budgets of turbulent kinetic energy and
temperature variance in the atmospheric surface layer, J. Atmos. Sci., 28,
190–201, https://doi.org/10.1175/1520-0469(1971)028<0190:TBOTKE>2.0.CO;2, 1971.
Zhang, F.: Generation of mesoscale gravity waves in upper-tropospheric
jet–front systems. J. Atmos. Sci., 61, 440–457,
https://doi.org/10.1175/1520-0469(2004)061<0440:GOMGWI>2.0.CO;2, 2004.
Zovko-Rajak, D., Lane, T. P., Sharman, R. D., and Trier, S. B.: The
role of gravity wave breaking in a case of upper-level near-cloud
turbulence, Mon. Weather Rev., 147, 4567–4588,
https://doi.org/10.1175/MWR-D-18-0445.1, 2019.
Short summary
The cube root of the energy dissipation rate (EDR), as a standard reporting metric of atmospheric turbulence, is estimated using 1 Hz commercial quick access recorder data from Korean-based national air carriers with two different types of aircraft. Various EDRs are estimated using zonal, meridional, and derived vertical wind components and the derived equivalent vertical gust. Characteristics of the observed EDR estimates using 1 Hz flight data are examined to observe strong turbulence cases.
The cube root of the energy dissipation rate (EDR), as a standard reporting metric of...