Articles | Volume 14, issue 4
Atmos. Meas. Tech., 14, 3033–3048, 2021
https://doi.org/10.5194/amt-14-3033-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: Tropospheric profiling (ISTP11) (AMT/ACP inter-journal SI)
Atmos. Meas. Tech., 14, 3033–3048, 2021
https://doi.org/10.5194/amt-14-3033-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 26 Apr 2021
Research article | 26 Apr 2021
Ground-based temperature and humidity profiling: combining active and passive remote sensors
David D. Turner and Ulrich Löhnert
Related authors
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
Short summary
Short summary
We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
Short summary
Short summary
Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-9, https://doi.org/10.5194/amt-2021-9, 2021
Revised manuscript under review for AMT
Short summary
Short summary
In this paper we show the usefulness of observational data in the radiative transfer model to retrieve the reliable atmospheric temperature profiles. In particular, the additional data from radio acoustic sounding systems (RASS) could improve the temperature in terms of bias and RMSE in comparison to the radiosonde temperature profiles not only in the 200–2000 m atmospheric layer above the ground where RASS data available, but in the deep 0–5000 m atmosphere stratum.
Laura Bianco, Irina V. Djalalova, James M. Wilczak, Joseph B. Olson, Jaymes S. Kenyon, Aditya Choukulkar, Larry K. Berg, Harindra J. S. Fernando, Eric P. Grimit, Raghavendra Krishnamurthy, Julie K. Lundquist, Paytsar Muradyan, Mikhail Pekour, Yelena Pichugina, Mark T. Stoelinga, and David D. Turner
Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019, https://doi.org/10.5194/gmd-12-4803-2019, 2019
Short summary
Short summary
During the second Wind Forecast Improvement Project, improvements to the parameterizations were applied to the High Resolution Rapid Refresh model and its nested version. The impacts of the new parameterizations on the forecast of 80 m wind speeds and power are assessed, using sodars and profiling lidars observations for comparison. Improvements are evaluated as a function of the model’s initialization time, forecast horizon, time of the day, season, site elevation, and meteorological phenomena.
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
Short summary
Short summary
A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Robert A. Stillwell, Ryan R. Neely III, Jeffrey P. Thayer, Matthew D. Shupe, and David D. Turner
Atmos. Meas. Tech., 11, 835–859, https://doi.org/10.5194/amt-11-835-2018, https://doi.org/10.5194/amt-11-835-2018, 2018
Short summary
Short summary
This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those measurements within the context of cloud radiative effects. It is found that effects related to lidar data recording systems can cause retrieval ambiguities that alter the interpretation of cloud phase in as much as 30 % of the available data. This misinterpretation of cloud-phase data can cause a misinterpretation of the effect of cloud phase on the surface radiation budget by as much as 10 to 30 %.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
Short summary
Short summary
Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
Short summary
Short summary
We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
Andrew M. Dzambo, David D. Turner, and Eli J. Mlawer
Atmos. Meas. Tech., 9, 1613–1626, https://doi.org/10.5194/amt-9-1613-2016, https://doi.org/10.5194/amt-9-1613-2016, 2016
Short summary
Short summary
Radiosondes are used to characterize the humidity in the middle and upper troposphere, but suffer from a solar radiation induced dry bias. This work investigates the accuracy of two published correction algorithms using comparisons with other instruments.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
Short summary
Short summary
We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
Short summary
Short summary
Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-9, https://doi.org/10.5194/amt-2021-9, 2021
Revised manuscript under review for AMT
Short summary
Short summary
In this paper we show the usefulness of observational data in the radiative transfer model to retrieve the reliable atmospheric temperature profiles. In particular, the additional data from radio acoustic sounding systems (RASS) could improve the temperature in terms of bias and RMSE in comparison to the radiosonde temperature profiles not only in the 200–2000 m atmospheric layer above the ground where RASS data available, but in the deep 0–5000 m atmosphere stratum.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, and Christoph Ritter
Atmos. Chem. Phys., 20, 5157–5173, https://doi.org/10.5194/acp-20-5157-2020, https://doi.org/10.5194/acp-20-5157-2020, 2020
Short summary
Short summary
This paper presents an influence of water vapor anomalies on cloud properties and their radiative effect at Ny-Ålesund. The study is based on a 2.5-year active and passive cloud observation and a radiative transfer model. The results show that moist and dry conditions are related to strong changes in cloud occurrence, phase partitioning, water path, and, consequently, modulate the surface radiative budget.
Rosa Gierens, Stefan Kneifel, Matthew D. Shupe, Kerstin Ebell, Marion Maturilli, and Ulrich Löhnert
Atmos. Chem. Phys., 20, 3459–3481, https://doi.org/10.5194/acp-20-3459-2020, https://doi.org/10.5194/acp-20-3459-2020, 2020
Short summary
Short summary
Multiyear statistics of persistent low-level mixed-phase clouds observed at an Arctic fjord environment in Svalbard are presented. The effects the local boundary layer (i.e. the fjords' wind climate and surface coupling), regional wind direction, and seasonality have on the cloud occurrence and properties are evaluated using a synergy of ground-based remote sensing methods and auxiliary data. The phenomena considered were found to modify the amount of liquid and ice in the studied clouds.
Tobias Marke, Ulrich Löhnert, Vera Schemann, Jan H. Schween, and Susanne Crewell
Atmos. Chem. Phys., 20, 1723–1736, https://doi.org/10.5194/acp-20-1723-2020, https://doi.org/10.5194/acp-20-1723-2020, 2020
Short summary
Short summary
In this study, land surface and atmosphere interactions are addressed using ground-based remote sensing, satellite products, and high-resolution large-eddy simulations. The focus is on water vapor transport from the surface into the atmosphere. Patterns found in long-term observations can be linked to properties of the surrounding land surface. The simulation results suggest that a different distribution of land use types has implications for boundary layer characteristics and clouds.
Laura Bianco, Irina V. Djalalova, James M. Wilczak, Joseph B. Olson, Jaymes S. Kenyon, Aditya Choukulkar, Larry K. Berg, Harindra J. S. Fernando, Eric P. Grimit, Raghavendra Krishnamurthy, Julie K. Lundquist, Paytsar Muradyan, Mikhail Pekour, Yelena Pichugina, Mark T. Stoelinga, and David D. Turner
Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019, https://doi.org/10.5194/gmd-12-4803-2019, 2019
Short summary
Short summary
During the second Wind Forecast Improvement Project, improvements to the parameterizations were applied to the High Resolution Rapid Refresh model and its nested version. The impacts of the new parameterizations on the forecast of 80 m wind speeds and power are assessed, using sodars and profiling lidars observations for comparison. Improvements are evaluated as a function of the model’s initialization time, forecast horizon, time of the day, season, site elevation, and meteorological phenomena.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, Christoph Ritter, and Ewan O'Connor
Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, https://doi.org/10.5194/acp-19-4105-2019, 2019
Short summary
Short summary
In this study, properties of clouds at the French–German Arctic research station in Ny-Ålesund are related to in-cloud thermodynamic conditions. The dataset used was collected within the Arctic Amplification project with a set of active and passive remote instruments. The results are compared with a model output. Significant divergence in observations and modelling of single-layer ice and mixed-phase clouds was found.
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
Short summary
Short summary
A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Robert A. Stillwell, Ryan R. Neely III, Jeffrey P. Thayer, Matthew D. Shupe, and David D. Turner
Atmos. Meas. Tech., 11, 835–859, https://doi.org/10.5194/amt-11-835-2018, https://doi.org/10.5194/amt-11-835-2018, 2018
Short summary
Short summary
This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those measurements within the context of cloud radiative effects. It is found that effects related to lidar data recording systems can cause retrieval ambiguities that alter the interpretation of cloud phase in as much as 30 % of the available data. This misinterpretation of cloud-phase data can cause a misinterpretation of the effect of cloud phase on the surface radiation budget by as much as 10 to 30 %.
Francesco De Angelis, Domenico Cimini, Ulrich Löhnert, Olivier Caumont, Alexander Haefele, Bernhard Pospichal, Pauline Martinet, Francisco Navas-Guzmán, Henk Klein-Baltink, Jean-Charles Dupont, and James Hocking
Atmos. Meas. Tech., 10, 3947–3961, https://doi.org/10.5194/amt-10-3947-2017, https://doi.org/10.5194/amt-10-3947-2017, 2017
Short summary
Short summary
Modern data assimilation systems require knowledge of the typical differences between observations and model background (O–B). This work illustrates a 1-year O–B analysis for ground-based microwave radiometer (MWR) observations in clear-sky conditions for a prototype network of six MWRs in Europe. Observations are MWR brightness temperatures (TB). Background profiles extracted from the output of a convective-scale model are used to simulate TB through the radiative transfer model RTTOV-gb.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
Short summary
Short summary
Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Claudia Acquistapace, Stefan Kneifel, Ulrich Löhnert, Pavlos Kollias, Maximilian Maahn, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 10, 1783–1802, https://doi.org/10.5194/amt-10-1783-2017, https://doi.org/10.5194/amt-10-1783-2017, 2017
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The goal of the paper is to understand what the optimal cloud radar settings for drizzle detection are. The number of cloud radars in the world has increased in the last 10 years and it is important to develop strategies to derive optimal settings which can be applied to all radar systems. The study is part of broader research focused on better understanding the microphysical process of drizzle growth using ground-based observations.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
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This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
María Barrera-Verdejo, Susanne Crewell, Ulrich Löhnert, Emiliano Orlandi, and Paolo Di Girolamo
Atmos. Meas. Tech., 9, 4013–4028, https://doi.org/10.5194/amt-9-4013-2016, https://doi.org/10.5194/amt-9-4013-2016, 2016
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
Short summary
Short summary
We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
Andrew M. Dzambo, David D. Turner, and Eli J. Mlawer
Atmos. Meas. Tech., 9, 1613–1626, https://doi.org/10.5194/amt-9-1613-2016, https://doi.org/10.5194/amt-9-1613-2016, 2016
Short summary
Short summary
Radiosondes are used to characterize the humidity in the middle and upper troposphere, but suffer from a solar radiation induced dry bias. This work investigates the accuracy of two published correction algorithms using comparisons with other instruments.
M. Barrera-Verdejo, S. Crewell, U. Löhnert, E. Orlandi, and P. Di Girolamo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-5467-2015, https://doi.org/10.5194/amtd-8-5467-2015, 2015
Revised manuscript not accepted
S. Steinke, S. Eikenberg, U. Löhnert, G. Dick, D. Klocke, P. Di Girolamo, and S. Crewell
Atmos. Chem. Phys., 15, 2675–2692, https://doi.org/10.5194/acp-15-2675-2015, https://doi.org/10.5194/acp-15-2675-2015, 2015
J. H. Schween, A. Hirsikko, U. Löhnert, and S. Crewell
Atmos. Meas. Tech., 7, 3685–3704, https://doi.org/10.5194/amt-7-3685-2014, https://doi.org/10.5194/amt-7-3685-2014, 2014
Short summary
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Two different methods for the determination of the mixing layer height (MLH) are investigated with a one-year data set from central Europe: (i) based on a significant gradient of backscatter and (ii) on the vertical velocity. The aerosol-based method shows significant over-estimation in the morning hours when the ML grows into the residual layer and late afternoon hours when turbulent mixing decays. This results in systematic over-estimation of average characteristcs as e.g. maximum MLH.
A. Battaglia, C. D. Westbrook, S. Kneifel, P. Kollias, N. Humpage, U. Löhnert, J. Tyynelä, and G. W. Petty
Atmos. Meas. Tech., 7, 1527–1546, https://doi.org/10.5194/amt-7-1527-2014, https://doi.org/10.5194/amt-7-1527-2014, 2014
G. Maschwitz, U. Löhnert, S. Crewell, T. Rose, and D. D. Turner
Atmos. Meas. Tech., 6, 2641–2658, https://doi.org/10.5194/amt-6-2641-2013, https://doi.org/10.5194/amt-6-2641-2013, 2013
V. Meunier, U. Löhnert, P. Kollias, and S. Crewell
Atmos. Meas. Tech., 6, 1171–1187, https://doi.org/10.5194/amt-6-1171-2013, https://doi.org/10.5194/amt-6-1171-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Support vector machine tropical wind speed retrieval in the presence of rain for Ku-band wind scatterometry
Evaluation of convective boundary layer height estimates using radars operating at different frequency bands
Four-dimensional mesospheric and lower thermospheric wind fields using Gaussian process regression on multistatic specular meteor radar observations
Correction of wind bias for the lidar on board Aeolus using telescope temperatures
Leveraging machine learning for quantitative precipitation estimation from Fengyun-4 geostationary observations and ground meteorological measurements
Deriving column-integrated thermospheric temperature with the N2 Lyman–Birge–Hopfield (2,0) band
Atmospheric tomography using the Nordic Meteor Radar Cluster and Chilean Observation Network De Meteor Radars: network details and 3D-Var retrieval
Using vertical phase differences to better resolve 3D gravity wave structure
High-temporal-resolution wet delay gradients estimated from multi-GNSS and microwave radiometer observations
Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy
GNSS-based water vapor estimation and validation during the MOSAiC expedition
Meteor radar observations of polar mesospheric summer echoes over Svalbard
Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars
Calibration of radar differential reflectivity using quasi-vertical profiles
Evaluation of micro rain radar-based precipitation classification algorithms to discriminate between stratiform and convective precipitation
On the estimation of boundary layer heights: a machine learning approach
IMK/IAA MIPAS temperature retrieval version 8: nominal measurements
Resolving the ambiguous direction of arrival of weak meteor radar trail echoes
Comparison of single-Doppler and multiple-Doppler wind retrievals in Hurricane Matthew (2016)
Insights into wind turbine reflectivity and radar cross-section (RCS) and their variability using X-band weather radar observations
Eddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos
Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure
Consistency of total column ozone measurements between the Brewer and Dobson spectroradiometers of the LKO Arosa and PMOD/WRC Davos
RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland
Statistically analyzing the effect of ionospheric irregularity on GNSS radio occultation atmospheric measurement
Detection of the melting level with polarimetric weather radar
Integrated water vapor and liquid water path retrieval using a single-channel radiometer
Improving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profiling
A new global grid-based weighted mean temperature model considering vertical nonlinear variation
Monitoring sudden stratospheric warmings using radio occultation: a new approach demonstrated based on the 2009 event
LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 1: Theoretical framework
LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 2: Applications to lidar measurements of wind turbine wakes
Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam
Spectral correction of turbulent energy damping on wind lidar measurements due to spatial averaging
Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion
Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method
Assimilation of lidar planetary boundary layer height observations
Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument
What millimeter-wavelength radar reflectivity reveals about snowfall: an information-centric analysis
Generalized canonical transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients
Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study
Classification of lidar measurements using supervised and unsupervised machine learning methods
The development of rainfall retrievals from radar at Darwin
Retrieved wind speed from the Orbiting Carbon Observatory-2
Probabilistic analysis of ambiguities in radar echo direction of arrival from meteors
Detecting the melting layer with a micro rain radar using a neural network approach
Detecting turbulent structures on single Doppler lidar large datasets: an automated classification method for horizontal scans
Real-time estimation of airflow vector based on lidar observations for preview control
Filtering of pulsed lidar data using spatial information and a clustering algorithm
Variability of the Brunt–Väisälä frequency at the OH∗-airglow layer height at low and midlatitudes
Xingou Xu and Ad Stoffelen
Atmos. Meas. Tech., 14, 7435–7451, https://doi.org/10.5194/amt-14-7435-2021, https://doi.org/10.5194/amt-14-7435-2021, 2021
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The support vector machine can effectively represent the increasing effect of rain affecting wind speeds. This research provides a correction of deviations that are skew- to Gaussian-like features caused by rain in Ku-band scatterometer wind. It demonstrates the effectiveness of a machine learning method when used based on elaborate analysis of the model establishment and result validation procedures. The corrected winds provide information previously lacking, which is vital for nowcasting.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Ryan Volz, Jorge L. Chau, Philip J. Erickson, Juha P. Vierinen, J. Miguel Urco, and Matthias Clahsen
Atmos. Meas. Tech., 14, 7199–7219, https://doi.org/10.5194/amt-14-7199-2021, https://doi.org/10.5194/amt-14-7199-2021, 2021
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We introduce a new way of estimating winds in the upper atmosphere (about 80 to 100 km in altitude) from the observed Doppler shift of meteor trails using a statistical method called Gaussian process regression. Wind estimates and, critically, the uncertainty of those estimates can be evaluated smoothly (i.e., not gridded) in space and time. The effective resolution is set by provided parameters, which are limited in practice by the number density of the observed meteors.
Fabian Weiler, Michael Rennie, Thomas Kanitz, Lars Isaksen, Elena Checa, Jos de Kloe, Ngozi Okunde, and Oliver Reitebuch
Atmos. Meas. Tech., 14, 7167–7185, https://doi.org/10.5194/amt-14-7167-2021, https://doi.org/10.5194/amt-14-7167-2021, 2021
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This paper summarizes the identification and correction of one of the most important systematic error sources for the wind measurements of the ESA satellite Aeolus. It depicts the effects of small temperature variations in the primary telescope mirror on the quality of the wind products and describes the approach to correct for it in the near-real-time processing. Moreover, the performance of the correction approach is assessed, and alternative approaches are discussed.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, https://doi.org/10.5194/amt-14-7007-2021, 2021
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A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Clayton Cantrall and Tomoko Matsuo
Atmos. Meas. Tech., 14, 6917–6928, https://doi.org/10.5194/amt-14-6917-2021, https://doi.org/10.5194/amt-14-6917-2021, 2021
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This paper presents a new technique to determine temperature in the thermosphere from observations of far ultraviolet radiation emitted by molecular nitrogen. The technique utilizes a ratio of two far ultraviolet spectral channels to capture the thermosphere temperature signal. Applying the technique to NASA GOLD observations results in temperatures that agree well with other thermosphere observations during a geomagnetic disturbance.
Gunter Stober, Alexander Kozlovsky, Alan Liu, Zishun Qiao, Masaki Tsutsumi, Chris Hall, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Patrick J. Espy, Robert E. Hibbins, and Nicholas Mitchell
Atmos. Meas. Tech., 14, 6509–6532, https://doi.org/10.5194/amt-14-6509-2021, https://doi.org/10.5194/amt-14-6509-2021, 2021
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Wind observations at the edge to space, 70–110 km altitude, are challenging. Meteor radars have become a widely used instrument to obtain mean wind profiles above an instrument for these heights. We describe an advanced mathematical concept and present a tomographic analysis using several meteor radars located in Finland, Sweden and Norway, as well as Chile, to derive the three-dimensional flow field. We show an example of a gravity wave decelerating the mean flow.
Corwin J. Wright, Neil P. Hindley, M. Joan Alexander, Laura A. Holt, and Lars Hoffmann
Atmos. Meas. Tech., 14, 5873–5886, https://doi.org/10.5194/amt-14-5873-2021, https://doi.org/10.5194/amt-14-5873-2021, 2021
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Measuring atmospheric gravity waves in low vertical-resolution data is technically challenging, especially when the waves are significantly longer in the vertical than in the length of the measurement domain. We introduce and demonstrate a modification to the existing Stockwell transform methods of characterising these waves that address these problems, with no apparent reduction in the other capabilities of the technique.
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 14, 5593–5605, https://doi.org/10.5194/amt-14-5593-2021, https://doi.org/10.5194/amt-14-5593-2021, 2021
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We have estimated horizontal gradients of the propagation delay caused by water vapour in the atmosphere using two independent techniques, namely global navigation satellite systems (GNSS) and microwave radiometry. The highest resolution was 5 min. We found that the sampling of the atmosphere in different directions is an important factor for high correlations between the two techniques and that GNSS data can be used to detect large short-lived gradients, however, with increased formal errors.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021, https://doi.org/10.5194/amt-14-5127-2021, 2021
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Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027, https://doi.org/10.5194/amt-14-5015-2021, https://doi.org/10.5194/amt-14-5015-2021, 2021
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A radar in Svalbard usually used to study meteor trails was used to observe a thin icy layer in the upper atmosphere. New methods used the layer to measure wind speed over short periods of time and found that the layer is most reflective within 6.8 ± 3.3° of vertical. Analysis of meteor trail radar echo durations found that the layer may shorten meteor trail echoes, but more data are needed. This study shows new uses for data collected by meteor radars for other purposes.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-194, https://doi.org/10.5194/amt-2021-194, 2021
Revised manuscript accepted for AMT
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In this work, we examine different methods for monitoring the calibration of the radar differential reflectivity ZDR. First, we implemented a well-known procedure to calibrate and monitor the ZDR offset using vertical profiles of polarimetric variables. Then, we propose a novel, operational method to calibrate ZDR using quasi-vertical profiles of polarimetric variables. We observed an excellent agreement between both methods, as the errors (MAE and RMSE) are within 0.1 dB.
Andreas Foth, Janek Zimmer, Felix Lauermann, and Heike Kalesse-Los
Atmos. Meas. Tech., 14, 4565–4574, https://doi.org/10.5194/amt-14-4565-2021, https://doi.org/10.5194/amt-14-4565-2021, 2021
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In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, https://doi.org/10.5194/amt-14-4111-2021, 2021
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An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Daniel Kastinen, Johan Kero, Alexander Kozlovsky, and Mark Lester
Atmos. Meas. Tech., 14, 3583–3596, https://doi.org/10.5194/amt-14-3583-2021, https://doi.org/10.5194/amt-14-3583-2021, 2021
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When a meteor enters the atmosphere, it causes a trail of diffusing plasma that moves with the neutral wind. An interferometric radar system can measure such trails and determine its location. However, there is a chance of determining the wrong position due to noise. We simulate this behaviour and use the simulations to successfully determine the true location of ambiguous events. We also successfully test two simple temporal integration methods for avoiding such erroneous determinations.
Ting-Yu Cha and Michael M. Bell
Atmos. Meas. Tech., 14, 3523–3539, https://doi.org/10.5194/amt-14-3523-2021, https://doi.org/10.5194/amt-14-3523-2021, 2021
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Doppler radar provides high-resolution wind measurements within tropical cyclones (TCs) for real-time monitoring and weather forecasting. Hurricane Matthew (2016) was observed by the ground-based single-Doppler and NOAA P-3 Hurricane Hunter airborne radar simultaneously, providing a novel opportunity to compare single- and multiple-Doppler wind retrieval techniques. Here, we improve the single-Doppler wind retrieval algorithm and show the pros and cons of each method for studying TC structure.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Pavel Alekseychik, Gabriel Katul, Ilkka Korpela, and Samuli Launiainen
Atmos. Meas. Tech., 14, 3501–3521, https://doi.org/10.5194/amt-14-3501-2021, https://doi.org/10.5194/amt-14-3501-2021, 2021
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Drones with thermal cameras are powerful new tools with the potential to provide new insights into atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos at 500 m a.g.l. over the Siikaneva peatland in southern Finland. A method to visualize the turbulent structures and derive their parameters from thermal videos is developed. The study provides a novel approach for turbulence analysis.
Svetla Hristova-Veleva, Sara Q. Zhang, F. Joseph Turk, Ziad S. Haddad, and Randy C. Sawaya
Atmos. Meas. Tech., 14, 3333–3350, https://doi.org/10.5194/amt-14-3333-2021, https://doi.org/10.5194/amt-14-3333-2021, 2021
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The assimilation of airborne-based three-dimensional winds into a mesoscale weather forecast model resulted in better agreement with airborne radar-derived precipitation 3-D structure at later model time steps. More importantly, there was also a discernible impact on the resultant wind and moisture structure, in accord with independent analysis of the wind structure and external satellite observations.
Julian Gröbner, Herbert Schill, Luca Egli, and René Stübi
Atmos. Meas. Tech., 14, 3319–3331, https://doi.org/10.5194/amt-14-3319-2021, https://doi.org/10.5194/amt-14-3319-2021, 2021
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The world's longest continuous total column ozone time series was initiated in 1926 at the Lichtklimatisches Observatorium (LKO), at Arosa, in the Swiss Alps. The measurements between Dobson and Brewer spectroradiometers have shown seasonal variations of the order of 2 %. The results of the study show that the consistency between the two instrument types can be significantly improved when the ozone cross-sections from Serdyuchenko et al. (2013) and the measured slit functions are used.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
Mingzhe Li and Xinan Yue
Atmos. Meas. Tech., 14, 3003–3013, https://doi.org/10.5194/amt-14-3003-2021, https://doi.org/10.5194/amt-14-3003-2021, 2021
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In this study, we statistically analyzed the correlation between the ionospheric irregularity and the quality of the GNSS atmospheric radio occultation (RO) products. The results show that the ionospheric irregularity could affect the GNSS atmospheric RO in terms of causing failed inverted RO events and the bending angle oscillation. Awareness of the ionospheric irregularity effect on RO could be beneficial to improve the RO data quality for weather and climate research.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 14, 2873–2890, https://doi.org/10.5194/amt-14-2873-2021, https://doi.org/10.5194/amt-14-2873-2021, 2021
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In our paper, we propose a robust and operational algorithm to determine the height of the melting level that can be applied to either quasi-vertical profiles (QVPs) or vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied to 1 year of rainfall events that occurred over southeast England and validated using radiosonde data. The algorithm proves to be accurate as the errors (mean absolute error and root mean square error) are close to 200 m.
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, https://doi.org/10.5194/amt-14-2749-2021, 2021
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In the context of climate studies, understanding the role of clouds on a global and local scale is of paramount importance. One aspect is the quantification of cloud liquid water, which impacts the Earth’s radiative balance. This is routinely achieved with radiometers operating at different frequencies. In this study, we propose an approach that uses a single-frequency radiometer and that can be applied at any location to retrieve vertically integrated quantities of liquid water and water vapor.
Ayham Alyosef, Domenico Cimini, Lorenzo Luini, Carlo Riva, Frank S. Marzano, Marianna Biscarini, Luca Milani, Antonio Martellucci, Sabrina Gentile, Saverio T. Nilo, Francesco Di Paola, Ayman Alkhateeb, and Filomena Romano
Atmos. Meas. Tech., 14, 2737–2748, https://doi.org/10.5194/amt-14-2737-2021, https://doi.org/10.5194/amt-14-2737-2021, 2021
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Telecommunication is based on the propagation of radio signals through the atmosphere. The signal power diminishes along the path due to atmospheric attenuation, which needs to be estimated to be accounted for. In a study funded by the European Space Agency, we demonstrate an innovative method improving atmospheric attenuation estimates from ground-based radiometric measurements by 10–30 %. More accurate atmospheric attenuation estimates imply better telecommunication services in the future.
Peng Sun, Suqin Wu, Kefei Zhang, Moufeng Wan, and Ren Wang
Atmos. Meas. Tech., 14, 2529–2542, https://doi.org/10.5194/amt-14-2529-2021, https://doi.org/10.5194/amt-14-2529-2021, 2021
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In GPS or Global navigation satellite systems (GNSS) meteorology, precipitable water vapor (PWV) at a station is obtained from a conversion of the GNSS signal zenith wet delay (ZWD) using a conversion factor which is a function of weighted mean temperature (Tm) over the site. We developed a new global grid-based empirical Tm model using ERA5 reanalysis data. The model-predicted Tm value has significance for applications needing real-time or near real-time PWV converted from GNSS signals.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
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We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2065–2093, https://doi.org/10.5194/amt-14-2065-2021, https://doi.org/10.5194/amt-14-2065-2021, 2021
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A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of velocity statistics is proposed. The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2095–2113, https://doi.org/10.5194/amt-14-2095-2021, https://doi.org/10.5194/amt-14-2095-2021, 2021
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The LiDAR Statistical Barnes Objective Analysis (LiSBOA) is applied to lidar data collected in the wake of wind turbines to reconstruct mean wind speed and turbulence intensity. Various lidar scans performed during a field campaign for a wind farm in complex terrain are analyzed. The results endorse the application of the LiSBOA for lidar-based wind resource assessment and farm diagnosis.
Viktor A. Banakh, Igor N. Smalikho, and Andrey V. Falits
Atmos. Meas. Tech., 14, 1511–1524, https://doi.org/10.5194/amt-14-1511-2021, https://doi.org/10.5194/amt-14-1511-2021, 2021
Matteo Puccioni and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 1457–1474, https://doi.org/10.5194/amt-14-1457-2021, https://doi.org/10.5194/amt-14-1457-2021, 2021
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A procedure for correcting the turbulent-energy damping connected with spatial averaging of wind lidars is proposed. This effect of the lidar measuring process is modeled through a low-pass filter, whose order and cut-off frequency are estimated directly from the lidar data. The proposed procedure is first assessed through simultaneous and colocated lidar and sonic-anemometer measurements. Then it is applied to several datasets collected at sites with different terrain roughness.
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, and Bryan A. Baum
Atmos. Meas. Tech., 14, 1191–1203, https://doi.org/10.5194/amt-14-1191-2021, https://doi.org/10.5194/amt-14-1191-2021, 2021
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As the VIIRS satellite sensor has no infrared (IR) H2O absorption bands, we construct the missing bands through the fusion of imager (VIIRS) and sounder (CrIS) data in an attempt to improve derivation of moisture products. This study clearly demonstrates the positive impact by adding fusion IR absorption spectral bands and the potential for continuing the moisture record from MODIS and the previous generations of polar-orbiting satellite sensors.
Maryna Lukach, David Dufton, Jonathan Crosier, Joshua M. Hampton, Lindsay Bennett, and Ryan R. Neely III
Atmos. Meas. Tech., 14, 1075–1098, https://doi.org/10.5194/amt-14-1075-2021, https://doi.org/10.5194/amt-14-1075-2021, 2021
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This paper presents a novel technique of data-driven hydrometeor classification (HC) from quasi-vertical profiles, where the hydrometeor types are identified from an optimal number of hierarchical clusters, obtained recursively. This data-driven HC approach is capable of providing an optimal number of classes from dual-polarimetric weather radar observations. The embedded flexibility in the extent of granularity is the main advantage of this technique.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech., 14, 1099–1110, https://doi.org/10.5194/amt-14-1099-2021, https://doi.org/10.5194/amt-14-1099-2021, 2021
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Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.
Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov
Atmos. Meas. Tech., 14, 961–974, https://doi.org/10.5194/amt-14-961-2021, https://doi.org/10.5194/amt-14-961-2021, 2021
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Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as DI of 1–r.
Norman B. Wood and Tristan S. L'Ecuyer
Atmos. Meas. Tech., 14, 869–888, https://doi.org/10.5194/amt-14-869-2021, https://doi.org/10.5194/amt-14-869-2021, 2021
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Although millimeter-wavelength radar reflectivity observations are used to investigate snowfall properties, their ability to constrain specific properties has not been well-quantified. An information-focused retrieval
method shows how well snowfall properties, including rate and size distribution, are constrained by reflectivity. Sources of uncertainty in snowfall rate are dominated by uncertainties in the retrieved size distribution properties rather than by other retrieval assumptions.
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech., 14, 853–867, https://doi.org/10.5194/amt-14-853-2021, https://doi.org/10.5194/amt-14-853-2021, 2021
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Currently, the canonical transform (CT) approach to the processing of radio occultation observations is widely used. For the spherically symmetric atmosphere, the applicability of this method can be strictly proven. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a generalization of the CT method in order to reduce the errors due to horizontal gradients.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
Ghazal Farhani, Robert J. Sica, and Mark Joseph Daley
Atmos. Meas. Tech., 14, 391–402, https://doi.org/10.5194/amt-14-391-2021, https://doi.org/10.5194/amt-14-391-2021, 2021
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While it is relatively straightforward to automate the processing of lidar signals, it is difficult to automatically preprocess the measurements to distinguish between
goodand
badscans. It is easy to train humans to perform the task; however, considering the growing number of measurements, it is a time-consuming, on-going process. We have tested some machine learning algorithms for lidar signal classification and had success with both supervised and unsupervised methods.
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
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About 4 years of 2D video disdrometer data in Darwin are used to develop and validate rainfall retrievals for tropical convection in C- and X-band radars in Darwin. Using blended techniques previously used for Colorado and Manus and Gan islands, with modified coefficients in each estimator, provided the most optimal results. Using multiple radar observables to develop a rainfall retrieval provided a greater advantage than using a single observable, including using specific attenuation.
Robert R. Nelson, Annmarie Eldering, David Crisp, Aronne J. Merrelli, and Christopher W. O'Dell
Atmos. Meas. Tech., 13, 6889–6899, https://doi.org/10.5194/amt-13-6889-2020, https://doi.org/10.5194/amt-13-6889-2020, 2020
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Measurements of surface wind speed over oceans are scientifically useful. Here we show that the Orbiting Carbon Observatory-2 (OCO-2), originally designed to measure carbon dioxide using reflected sunlight, can also accurately and precisely measure wind speed. OCO-2's high spatial resolution means that it can observe close to coastlines and therefore be used to study coastal wind processes and inform related economic sectors.
Daniel Kastinen and Johan Kero
Atmos. Meas. Tech., 13, 6813–6835, https://doi.org/10.5194/amt-13-6813-2020, https://doi.org/10.5194/amt-13-6813-2020, 2020
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The behaviour of position determination with interferometric radar systems and possible ambiguities therein depends on the spatial configuration of the radar-receiving antennas and their individual characteristics. We have simulated the position determination performance of five different radar systems. These simulations showed that ambiguities are dynamic and need to be examined on a case-by-case basis. However, the simulations can be used to analyse and understand previously ambiguous data.
Maren Brast and Piet Markmann
Atmos. Meas. Tech., 13, 6645–6656, https://doi.org/10.5194/amt-13-6645-2020, https://doi.org/10.5194/amt-13-6645-2020, 2020
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An artificial neural network was trained to identify melting layers in micro rain radar data. It was successfully tested on simple and complex cases, which are difficult to identify using classical approaches, and also provided information on the melting layer width.
Ioannis Cheliotis, Elsa Dieudonné, Hervé Delbarre, Anton Sokolov, Egor Dmitriev, Patrick Augustin, and Marc Fourmentin
Atmos. Meas. Tech., 13, 6579–6592, https://doi.org/10.5194/amt-13-6579-2020, https://doi.org/10.5194/amt-13-6579-2020, 2020
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The current study presents an automated method to classify coherent structures near the surface, based on the observations recorded by a single scanning Doppler lidar. This methodology combines texture analysis with a supervised machine-learning algorithm in order to study large datasets. The algorithm classified correctly about 91 % of cases of a training ensemble (150 scans). Furthermore the results of a 2-month classified dataset (4577 scans) by the algorithm are presented.
Ryota Kikuchi, Takashi Misaka, Shigeru Obayashi, and Hamaki Inokuchi
Atmos. Meas. Tech., 13, 6543–6558, https://doi.org/10.5194/amt-13-6543-2020, https://doi.org/10.5194/amt-13-6543-2020, 2020
Short summary
Short summary
The control technique in a gust-alleviation system using the airborne Doppler lidar is expected to minimize the risks of turbulence-related accidents. Accurate estimation of the vertical wind is important in the successful implementation of a gust-alleviation system. An estimation algorithm of the airflow vector based on the lidars is proposed for preview control. The estimation performance and the computational cost of the proposed method can satisfy the performance demand for preview control.
Leonardo Alcayaga
Atmos. Meas. Tech., 13, 6237–6254, https://doi.org/10.5194/amt-13-6237-2020, https://doi.org/10.5194/amt-13-6237-2020, 2020
Short summary
Short summary
Wind lidars present advantages over meteorological masts, including simultaneous multipoint observations, flexibility in measuring geometry, and reduced installation cost. But wind lidars come with the cost of increased complexity in terms of data quality and analysis. The common carrier-to-noise ratio and median filters are compared to the DBSCAN clustering algorithm to find improved data quality and recovery rate.
Sabine Wüst, Michael Bittner, Jeng-Hwa Yee, Martin G. Mlynczak, and James M. Russell III
Atmos. Meas. Tech., 13, 6067–6093, https://doi.org/10.5194/amt-13-6067-2020, https://doi.org/10.5194/amt-13-6067-2020, 2020
Short summary
Short summary
With airglow spectrometers, the temperature in the upper mesosphere/lower thermosphere can be derived each night. The data allow to estimate the amount of energy which is transported by small-scale atmospheric waves, known as gravity waves. In order to do this, information about the Brunt–Väisälä frequency and its evolution during the year is necessary. This is provided here for low and midlatitudes based on 18 years of satellite data.
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Short summary
Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.
Temperature and humidity profiles in the lowest couple of kilometers near the surface are very...
