Articles | Volume 8, issue 1
https://doi.org/10.5194/amt-8-369-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-369-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Adaptive neuro-fuzzy inference system for temperature and humidity profile retrieval from microwave radiometer observations
K. Ramesh
Department of Computer Applications, Anna University, Regional Center, Tirunelveli, Tamil Nadu 627 005, India
A. P. Kesarkar
CORRESPONDING AUTHOR
National Atmospheric Research Laboratory, Gadanki 517 112, Chittoor District, Andhra Pradesh, India
J. Bhate
National Atmospheric Research Laboratory, Gadanki 517 112, Chittoor District, Andhra Pradesh, India
M. Venkat Ratnam
National Atmospheric Research Laboratory, Gadanki 517 112, Chittoor District, Andhra Pradesh, India
A. Jayaraman
National Atmospheric Research Laboratory, Gadanki 517 112, Chittoor District, Andhra Pradesh, India
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Amit Kumar Pandit, Jean-Paul Vernier, Thomas Duncan Fairlie, Kristopher M. Bedka, Melody A. Avery, Harish Gadhavi, Madineni Venkat Ratnam, Sanjeev Dwivedi, Kasimahanthi Amar Jyothi, Frank G. Wienhold, Holger Vömel, Hongyu Liu, Bo Zhang, Buduru Suneel Kumar, Tra Dinh, and Achuthan Jayaraman
Atmos. Chem. Phys., 24, 14209–14238, https://doi.org/10.5194/acp-24-14209-2024, https://doi.org/10.5194/acp-24-14209-2024, 2024
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This study investigates the formation mechanism of a tropopause cirrus cloud layer observed at extremely cold temperatures over Hyderabad in India during the 2017 Asian summer monsoon using balloon-borne sensors. Ice crystals smaller than 50 µm were found in this optically thin cirrus cloud layer. Combined analysis of back trajectories, satellite, and model data revealed that the formation of this layer was influenced by waves and stratospheric hydration induced by typhoon Hato.
Vadassery Neelamana Santhosh, Bomidi Lakshmi Madhavan, Sivan Thankamani Akhil Raj, Madineni Venkat Ratnam, Jean-Paul Vernier, and Frank Gunther Wienhold
EGUsphere, https://doi.org/10.5194/egusphere-2024-2861, https://doi.org/10.5194/egusphere-2024-2861, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Our study examines a lesser-known atmospheric feature, the Asian Tropopause Aerosol Layer, located high above Earth. We investigated how different aerosols, such as sulfates, nitrates, and pollutants, influence heat entering and leaving the atmosphere. The results show that these particles can alter temperature patterns, especially during the Asian summer monsoon. This research improves our understanding of how human activities may affect regional climate.
Hazel Vernier, Neeraj Rastogi, Hongyu Liu, Amit Kumar Pandit, Kris Bedka, Anil Patel, Madineni Venkat Ratnam, Buduru Suneel Kumar, Bo Zhang, Harish Gadhavi, Frank Wienhold, Gwenael Berthet, and Jean-Paul Vernier
Atmos. Chem. Phys., 22, 12675–12694, https://doi.org/10.5194/acp-22-12675-2022, https://doi.org/10.5194/acp-22-12675-2022, 2022
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The chemical composition of the stratospheric aerosols collected aboard high-altitude balloons above the summer Asian monsoon reveals the presence of nitrate/nitrite. Using numerical simulations and satellite observations, we found that pollution as well as lightning could explain some of our observations.
Varaha Ravi Kiran, Madineni Venkat Ratnam, Masatomo Fujiwara, Herman Russchenberg, Frank G. Wienhold, Bomidi Lakshmi Madhavan, Mekalathur Roja Raman, Renju Nandan, Sivan Thankamani Akhil Raj, Alladi Hemanth Kumar, and Saginela Ravindra Babu
Atmos. Meas. Tech., 15, 4709–4734, https://doi.org/10.5194/amt-15-4709-2022, https://doi.org/10.5194/amt-15-4709-2022, 2022
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We proposed and conducted the multi-instrumental BACIS (Balloon-borne Aerosol–Cloud Interaction Studies) field campaigns using balloon-borne in situ measurements and ground-based and space-borne remote sensing instruments. Aerosol-cloud interaction is quantified for liquid clouds by segregating aerosol and cloud information in a balloon profile. Overall, the observational approach proposed here demonstrated its capability for understanding the aerosol–cloud interaction process.
Rohit Chakraborty, Arindam Chakraborty, Ghouse Basha, and Madineni Venkat Ratnam
Atmos. Chem. Phys., 21, 11161–11177, https://doi.org/10.5194/acp-21-11161-2021, https://doi.org/10.5194/acp-21-11161-2021, 2021
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In this study, urbanization-induced surface warming has been found to trigger prominent changes in upper-troposphere–lower-stratosphere regions leading to stronger and more frequent lightning extremes over India. Consequently, the implementation of this hypothesis in global climate models reveals that lightning frequency and intensity values across India will rise by ~10–25 % and 15–50 %, respectively, by 2100 at the current urbanization rate, which should be alarming for present policymakers.
Saginela Ravindra Babu, Madineni Venkat Ratnam, Ghouse Basha, Shantanu Kumar Pani, and Neng-Huei Lin
Atmos. Chem. Phys., 21, 5533–5547, https://doi.org/10.5194/acp-21-5533-2021, https://doi.org/10.5194/acp-21-5533-2021, 2021
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The present study explores the detailed structure, dynamics, and trace gas variability in the Asian summer monsoon anticyclone (ASMA) in the extreme El Niño of 2015/16. The results find the structure of the ASMA shows strong spatial variability between July and August. A West Pacific mode of the anticyclone is noticed in August. A significant lowering of tropospheric tracers and strong increase in stratospheric tracers are found. The tropopause temperatures also exhibit a warming in the ASMA.
Akash Biswal, Vikas Singh, Shweta Singh, Amit P. Kesarkar, Khaiwal Ravindra, Ranjeet S. Sokhi, Martyn P. Chipperfield, Sandip S. Dhomse, Richard J. Pope, Tanbir Singh, and Suman Mor
Atmos. Chem. Phys., 21, 5235–5251, https://doi.org/10.5194/acp-21-5235-2021, https://doi.org/10.5194/acp-21-5235-2021, 2021
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Satellite and surface observations show a reduction in NO2 levels over India during the lockdown compared to business-as-usual years. A substantial reduction, proportional to the population, was observed over the urban areas. The changes in NO2 levels at the surface during the lockdown appear to be present in the satellite observations. However, TROPOMI showed a better correlation with surface NO2 and was more sensitive to the changes than OMI because of the finer resolution.
Kizhathur Narasimhan Uma, Siddarth Shankar Das, Madineni Venkat Ratnam, and Kuniyil Viswanathan Suneeth
Atmos. Chem. Phys., 21, 2083–2103, https://doi.org/10.5194/acp-21-2083-2021, https://doi.org/10.5194/acp-21-2083-2021, 2021
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Reanalysis data of vertical wind (w) are widely used by the atmospheric community to determine various calculations of atmospheric circulations, diabatic heating, convection, etc. There are no studies that assess the available reanalysis data with respect to observations. The present study assesses for the first time all the reanalysis w by comparing it with 20 years of radar data from Gadanki and Kototabang and shows that downdrafts and peaks in the updrafts are not produced in the reanalyses.
Ghouse Basha, M. Venkat Ratnam, and Pangaluru Kishore
Atmos. Chem. Phys., 20, 6789–6801, https://doi.org/10.5194/acp-20-6789-2020, https://doi.org/10.5194/acp-20-6789-2020, 2020
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This study explores the variability of the Asian summer monsoon anticyclone (ASMA) spatial variability and trends using long-term observational and reanalysis data sets. The decadal variability of the anticyclone is very large at the edges compared with the core region. We propose that the transport process over the Tibetan Plateau and the Indian region is significant in active monsoon, strong monsoon and strong La Niña years. Thus, different phases of the monsoon are important in UTLS analyses.
Ghouse Basha, M. Venkat Ratnam, Pangaluru Kishore, S. Ravindrababu, and Isabella Velicogna
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-743, https://doi.org/10.5194/acp-2019-743, 2019
Preprint withdrawn
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The Asian Summer Monsoon Anticyclone (ASMA) plays an important role in confining the trace gases and aerosols for a longer period. This study explores the variability of tropopause parameters, trace gases and aerosols and its relation with ENSO and QBO in ASMA. Further, the influence of the Indian summer monsoon activity on the ASMA trace gases and aerosols is studied with respect to active and break spells of monsoon, strong and weak monsoon years and strong La Niña, El Niño years.
Rohit Chakraborty, Bijay Kumar Guha, Shamitaksha Talukdar, Madineni Venkat Ratnam, and Animesh Maitra
Atmos. Chem. Phys., 19, 12325–12341, https://doi.org/10.5194/acp-19-12325-2019, https://doi.org/10.5194/acp-19-12325-2019, 2019
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The present study investigates the plausible aspects which influence the probability of drought occurrences over three Indian regions during the southwest Asian mid-monsoon period. The investigation reveals that an increasing tendency of dry day frequency (DDF) over urbanized regions in the last few decades has significant association with the abundance of anthropogenic aerosols. Additionally, future projections of DDF indicate a five-fold rise which can be a crucial concern for policy makers.
Rohit Chakraborty, Madineni Venkat Ratnam, and Shaik Ghouse Basha
Atmos. Chem. Phys., 19, 3687–3705, https://doi.org/10.5194/acp-19-3687-2019, https://doi.org/10.5194/acp-19-3687-2019, 2019
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Intense convective phenomena are a common climatic feature in the Indian tropical region which occur during the pre-monsoon to post-monsoon seasons (April–October) and are generally accompanied by intense thunderstorms, lightning, and wind gusts with heavy rainfall. Here we show long-term trends of the parameters related to convection and instability obtained from 27 radiosonde stations across six subdivisions over the Indian region during the period 1980–2016.
Nelli Narendra Reddy, Madineni Venkat Ratnam, Ghouse Basha, and Varaha Ravikiran
Atmos. Chem. Phys., 18, 11709–11727, https://doi.org/10.5194/acp-18-11709-2018, https://doi.org/10.5194/acp-18-11709-2018, 2018
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Cloud vertical structure affects large-scale atmosphere circulation by altering gradients in total diabatic heating and cooling and latent heat release. Detailed cloud vertical structure in all seasons, including diurnal variation over the Indian region, is made for the first time. The detected cloud layers are verified with independent observations using cloud particle sensor sonde. Heating and cooling in the troposphere and lower stratosphere due to these cloud layers are also investigated.
Sivan Thankamani Akhil Raj, Madineni Venkat Ratnam, Daggumati Narayana Rao, and Boddam Venkata Krishna Murthy
Ann. Geophys., 36, 149–165, https://doi.org/10.5194/angeo-36-149-2018, https://doi.org/10.5194/angeo-36-149-2018, 2018
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Ozone and water vapor are two potent greenhouse gases in the atmosphere. They influence the temperature structure greatly, particularly in the upper troposphere and lower stratosphere. We have investigated the long-term trends in these trace gases over the Indian region using long-term data (1993–2015) constructed from multi-satellite observations. A decreasing trend in ozone associated with NOx chemistry in the tropical middle stratosphere and a good correlation between N2O and O3 is found.
Sanjay Kumar Mehta, Madineni Venkat Ratnam, Sukumarapillai V. Sunilkumar, Daggumati Narayana Rao, and Boddapaty V. Krishna Murthy
Atmos. Chem. Phys., 17, 531–549, https://doi.org/10.5194/acp-17-531-2017, https://doi.org/10.5194/acp-17-531-2017, 2017
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Study of the diurnal variation of the atmospheric boundary layer (ABL) height is important for the knowledge of pollutant dispersion, crucial for all living beings. The most difficult part in the study of the diurnal variation is in identification of the stable boundary layer which occurs ~ 50% of times only and mostly during nighttime winter. Surface temperature and clouds directly affect the diurnal pattern of the ABL. Thus, stronger (weaker) diurnal variation found during pre-monsoon (winter).
Madineni Venkat Ratnam, Alladi Hemanth Kumar, and Achuthan Jayaraman
Atmos. Meas. Tech., 9, 5735–5745, https://doi.org/10.5194/amt-9-5735-2016, https://doi.org/10.5194/amt-9-5735-2016, 2016
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Launch of INSAT-3D carrying a multi-spectral imager by the ISRO made it possible to obtain profiles of temperature and water vapour over India with higher temporal and vertical resolutions. Initial validation is made with the radiosonde, other satellites and reanalysis data sets. Good correlation between INSAT-3D and in situ measurements is noticed with a few cautions. Temperature data from INSAT-3D are of high quality and can be directly assimilated for better forecasts over India.
M. Venkat Ratnam, S. Ravindra Babu, S. S. Das, G. Basha, B. V. Krishnamurthy, and B. Venkateswararao
Atmos. Chem. Phys., 16, 8581–8591, https://doi.org/10.5194/acp-16-8581-2016, https://doi.org/10.5194/acp-16-8581-2016, 2016
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The impact of cyclones that occurred over the north Indian Ocean during 2007–2013 on the STE process is quantified using satellite observations. It is shown that cyclones have a significant impact on the tropopause structure, ozone and water vapour budget, and consequentially STE in the UTLS region. The cross-tropopause mass flux from the stratosphere to the troposphere for cyclonic storms is found to be 0.05 ± 0.29 × 10−3 kg m−2, and for very severe cyclonic storms it is 0.5 ± 1.07 × 10−3 kg m−2.
K. K. Shukla, K. Niranjan Kumar, D. V. Phanikumar, R. K. Newsom, V. R. Kotamarthi, T. B. M. J. Ouarda, and M. V. Ratnam
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-162, https://doi.org/10.5194/amt-2016-162, 2016
Revised manuscript not accepted
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Estimation of Cloud base height was carried out by using various ground based instruments (Doppler Lidar and Ceilometer) and satellite datasets (MODIS) over central Himalayan region for the first time. The present study demonstrates the potential of Doppler Lidar in precise estimation of cloud base height and updraft velocities. More such deployments will be invaluable inputs for regional weather prediction models over complex Himalayan terrains.
Siddarth Shankar Das, Madineni Venkat Ratnam, Kizhathur Narasimhan Uma, Kandula Venkata Subrahmanyam, Imran Asatar Girach, Amit Kumar Patra, Sundaresan Aneesh, Kuniyil Viswanathan Suneeth, Karanam Kishore Kumar, Amit Parashuram Kesarkar, Sivarajan Sijikumar, and Geetha Ramkumar
Atmos. Chem. Phys., 16, 4837–4847, https://doi.org/10.5194/acp-16-4837-2016, https://doi.org/10.5194/acp-16-4837-2016, 2016
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The present study examines the role of tropical cyclones in the enhancement of tropospheric ozone. The most significant and new observation reported is the increase in the upper-tropospheric ozone by 20–50 ppbv, which has extended down to the middle and lower troposphere. The descent rate of enhanced ozone layer during the passage of tropical cyclone is 0.8–1 km day−1. Enhancement of surface ozone concentration by ~ 10 ppbv in the daytime and 10–15 ppbv at night-time is observed.
Sanjeev Dwivedi, M. S. Narayanan, M. Venkat Ratnam, and D. Narayana Rao
Atmos. Chem. Phys., 16, 4497–4509, https://doi.org/10.5194/acp-16-4497-2016, https://doi.org/10.5194/acp-16-4497-2016, 2016
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Monsoon inversion (MI) over the Arabian Sea is one of the important characteristics associated with the monsoon activity over Indian region. The initiation and dissipation times of MI, their percentage of occurrence, strength etc., has been examined. We suggest MI could also be included as one of the semi-permanent features of southwest monsoon.
A. K. Pandit, H. S. Gadhavi, M. Venkat Ratnam, K. Raghunath, S. V. B. Rao, and A. Jayaraman
Atmos. Chem. Phys., 15, 13833–13848, https://doi.org/10.5194/acp-15-13833-2015, https://doi.org/10.5194/acp-15-13833-2015, 2015
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We present the longest (1998 to 2013) cirrus cloud climatology over a tropical station using a ground-based lidar. A statistically significant increase is found in the altitude of sub-visible cirrus clouds. Also a systematic shift from thin to sub-visible cirrus cloud type is observed. Ground-based lidar is found to detect more number of sub-visible cirrus clouds than space-based lidar. These findings have implications to global warming and stratosphere-troposphere water vapour exchange studies.
S. Ravindra Babu, M. Venkat Ratnam, G. Basha, B. V. Krishnamurthy, and B. Venkateswararao
Atmos. Chem. Phys., 15, 10239–10249, https://doi.org/10.5194/acp-15-10239-2015, https://doi.org/10.5194/acp-15-10239-2015, 2015
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The effect of tropical cyclones (TCs) that occurred over the north Indian Ocean in the last decade on the tropical tropopause parameters has been quantified for the first time. The vertical structure of temperature and tropopause parameters within the 5º radius away from the cyclone centre during TC period is also presented. The water vapour variability in the vicinity of TC is investigated.
It is demonstrated that the TCs can significantly affect the tropical tropopause and thus STE processes.
M. Pramitha, M. Venkat Ratnam, A. Taori, B. V. Krishna Murthy, D. Pallamraju, and S. Vijaya Bhaskar Rao
Atmos. Chem. Phys., 15, 2709–2721, https://doi.org/10.5194/acp-15-2709-2015, https://doi.org/10.5194/acp-15-2709-2015, 2015
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Sources and propagation characteristics of high-frequency gravity waves observed in the mesosphere using airglow emissions from Gadanki and Hyderabad, India, are investigated using reverse ray tracing. Wave amplitudes are also traced back, including both radiative and diffusive damping. Interestingly, large vertical shears in the horizontal wind are noticed near the ray terminal points (at 10-12km altitude) and are thus identified to be the source for generating the observed gravity waves.
H. S. Gadhavi, K. Renuka, V. Ravi Kiran, A. Jayaraman, A. Stohl, Z. Klimont, and G. Beig
Atmos. Chem. Phys., 15, 1447–1461, https://doi.org/10.5194/acp-15-1447-2015, https://doi.org/10.5194/acp-15-1447-2015, 2015
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Emission inventories are a key component of simulating past, present and future climate. In this article we have evaluated three black carbon emission inventories for emissions of India using observations made from a strategic location. Annual average simulated black carbon concentration is found to be 35% to 60% lower than observed concentration because of underestimation of emissions of southern India in the inventories.
M. Venkat Ratnam, N. Pravallika, S. Ravindra Babu, G. Basha, M. Pramitha, and B. V. Krishna Murthy
Atmos. Meas. Tech., 7, 1011–1025, https://doi.org/10.5194/amt-7-1011-2014, https://doi.org/10.5194/amt-7-1011-2014, 2014
M. N. Sai Suman, H. Gadhavi, V. Ravi Kiran, A. Jayaraman, and S. V. B. Rao
Atmos. Meas. Tech., 7, 907–917, https://doi.org/10.5194/amt-7-907-2014, https://doi.org/10.5194/amt-7-907-2014, 2014
P. Kishore, M. Venkat Ratnam, I. Velicogna, V. Sivakumar, H. Bencherif, B. R. Clemesha, D. M. Simonich, P. P. Batista, and G. Beig
Ann. Geophys., 32, 301–317, https://doi.org/10.5194/angeo-32-301-2014, https://doi.org/10.5194/angeo-32-301-2014, 2014
D. V. Phanikumar, K. Niranjan Kumar, K. K. Shukla, H. Joshi, M. Venkat Ratnam, M. Naja, and K. Reddy
Ann. Geophys., 32, 175–180, https://doi.org/10.5194/angeo-32-175-2014, https://doi.org/10.5194/angeo-32-175-2014, 2014
S. K. Das, J.-P. Chen, M. Venkat Ratnam, and A. Jayaraman
Ann. Geophys., 31, 647–663, https://doi.org/10.5194/angeo-31-647-2013, https://doi.org/10.5194/angeo-31-647-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Double-moment normalization of hail size number distributions over Switzerland
The role of time averaging of eddy covariance fluxes on water use efficiency dynamics of maize
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
Bias Correction and Application of Labeled Smartphone Pressure Data for Evaluating the Best Track of Landfalling Tropical Cyclones
Hailstorm events in the Central Andes of Peru: insights from historical data and radar microphysics
Hybrid instrument network optimization for air quality monitoring
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
Characteristics of the derived energy dissipation rate using the 1 Hz commercial aircraft quick access recorder (QAR) data
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
Alfonso Ferrone, Jérôme Kopp, Martin Lainer, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 17, 7143–7168, https://doi.org/10.5194/amt-17-7143-2024, https://doi.org/10.5194/amt-17-7143-2024, 2024
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Estimates of hail size have been collected by a network of hail sensors, installed in three regions of Switzerland, since September 2018. In this study, we use a technique called “double-moment normalization” to model the distribution of diameter sizes. The parameters of the method have been defined over 70 % of the dataset and tested over the remaining 30 %. An independent distribution of hail sizes, collected by a drone, has also been used to evaluate the method.
Arun Rao Karimindla, Shweta Kumari, Saipriya S R, Syam Chintala, and BVN P. Kambhammettu
Atmos. Meas. Tech., 17, 5477–5490, https://doi.org/10.5194/amt-17-5477-2024, https://doi.org/10.5194/amt-17-5477-2024, 2024
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This study investigates the role of the averaging period of eddy covariance fluxes on the energy balance ratio and further propagation into water use efficiency dynamics. Application was demonstrated on a maize field considering EC flux data. We found that the time averages of EC fluxes that yield the most effective EBR are at 45 and 60 min. The 30 min averaging period was insufficient to capture low-frequency fluxes. Time averaging of EC fluxes needs to be performed based on crop growth stage.
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
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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
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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.
Ge Qiao, Yuyao Cao, Qinghong Zhang, and Juanzhen Sun
EGUsphere, https://doi.org/10.5194/egusphere-2024-1505, https://doi.org/10.5194/egusphere-2024-1505, 2024
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Smartphones equipped with multiple sensors have great potential to form high-resolution meteorological observation fields. In this study, we focused on smartphone pressure observation in tropical cyclone environment. We developed a machine learning-based quality control program that greatly reduced errors and found that smartphone data led to significant improvements in analysis fields. Some traditional best tracks were found to consistently underestimate the minimum sea level pressure.
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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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
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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.
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
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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.
Soo-Hyun Kim, Jeonghoe Kim, Jung-Hoon Kim, and Hye-Yeong Chun
Atmos. Meas. Tech., 15, 2277–2298, https://doi.org/10.5194/amt-15-2277-2022, https://doi.org/10.5194/amt-15-2277-2022, 2022
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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.
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
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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
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
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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
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.
Cited articles
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Short summary
The study of atmospheric convection is important for the understanding of evolution of diurnal cycles of rainfall. High-resolution observations of vertical profiles of temperature and relative humidity are very useful for understanding the behaviour of these convections. Microwave radiometers are becoming useful tools for it. In this paper, we propose a new method to retrieve these profiles based on adaptive neuro-fuzzy interface systems and find that this method has a better skill of retrieval.
The study of atmospheric convection is important for the understanding of evolution of diurnal...