Articles | Volume 4, issue 12
Atmos. Meas. Tech., 4, 2837–2850, 2011
https://doi.org/10.5194/amt-4-2837-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Observing atmosphere and climate with occultation techniques...
Atmos. Meas. Tech., 4, 2837–2850, 2011
https://doi.org/10.5194/amt-4-2837-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 22 Dec 2011
Research article | 22 Dec 2011
The impact of large scale ionospheric structure on radio occultation retrievals
A. J. Mannucci et al.
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
Intra-annual variations of spectrally resolved gravity wave activity in the upper mesosphere/lower thermosphere (UMLT) region
Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Estimation of the height of turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part I: Theoretical framework
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part II: Applications to synthetic and real LiDAR data of wind turbine wakes
Detection of non-linear effects in satellite UV/Vis reflectance spectra: Application to the Ozone Monitoring Instrument
Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation
Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans
Optimised degradation correction for SCIAMACHY satellite solar measurements from 330 to 1600 nm by using the internal white light source
Monitoring Sudden Stratospheric Warmings using radio occultation: a new approach demonstrated based on the 2009 event
Rain event detection in commercial microwave link attenuation data using convolutional neural networks
Preliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment
Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion
Assimilation of lidar planetary boundary layer height observations
What millimeter-wavelength radar reflectivity reveals about snowfall: An information-centric analysis
Observation of sensible and latent heat flux profiles with lidar
Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar
Update of Infrared Atmospheric Sounding Interferometer (IASI) channel selection with correlated observation errors for numerical weather prediction (NWP)
Spectral correction of turbulent energy damping on wind LiDAR measurements due to range-gate averaging
Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method
Learning about the vertical structure of radar reflectivity using hydrometeor classes and neural networks in the Swiss Alps
Generalized Canonical Transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients
Toward a variational assimilation of polarimetric radar observations in a convective-scale numerical weather prediction (NWP) model
Estimating raindrop size distributions using microwave link measurements: potential and limitations
An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions
Analysis of flow in complex terrain using multi-Doppler lidar retrievals
Unsupervised classification of vertical profiles of dual polarization radar variables
Monitoring the differential reflectivity and receiver calibration of the German polarimetric weather radar network
A channel selection method for hyperspectral atmospheric infrared sounders based on layering
Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data
Advanced hodograph-based analysis technique to derive gravity-wave parameters from lidar observations
Rayleigh wind retrieval for the ALADIN airborne demonstrator of the Aeolus mission using simulated response calibration
Determining the daytime Earth radiative flux from National Institute of Standards and Technology Advanced Radiometer (NISTAR) measurements
Determination of time-varying periodicities in unequally spaced time series of OH* temperatures using a moving Lomb–Scargle periodogram and a fast calculation of the false alarm probabilities
A GPS water vapour tomography method based on a genetic algorithm
kCARTA: a fast pseudo line-by-line radiative transfer algorithm with analytic Jacobians, fluxes, nonlocal thermodynamic equilibrium, and scattering for the infrared
Potential for the measurement of mesosphere and lower thermosphere (MLT) wind, temperature, density and geomagnetic field with Superconducting Submillimeter-Wave Limb-Emission Sounder 2 (SMILES-2)
Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign
An experimental 2D-Var retrieval using AMSR2
Retrieval of intrinsic mesospheric gravity wave parameters using lidar and airglow temperature and meteor radar wind data
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
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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
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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
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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.
René Sedlak, Alexandra Zuhr, Carsten Schmidt, Sabine Wüst, Michael Bittner, Goderdzi G. Didebulidze, and Colin Price
Atmos. Meas. Tech., 13, 5117–5128, https://doi.org/10.5194/amt-13-5117-2020, https://doi.org/10.5194/amt-13-5117-2020, 2020
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Gravity wave (GW) activity in the UMLT in the period range 6-480 min is calculated by applying a wavelet analysis to nocturnal temperature time series derived from OH* airglow spectrometers. We analyse measurements from eight different locations at different latitudes.
GW activity shows strong period dependence. We find hardly any seasonal variability for periods below 60 min and a semi-annual cycle for periods longer than 60 min that evolves into an annual cycle around a period of 200 min.
Cornelia Strube, Manfred Ern, Peter Preusse, and Martin Riese
Atmos. Meas. Tech., 13, 4927–4945, https://doi.org/10.5194/amt-13-4927-2020, https://doi.org/10.5194/amt-13-4927-2020, 2020
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We present how inertial instabilities affect gravity wave background removal filters on different temperature data sets. Vertical filtering has to remove a part of the gravity wave spectrum to eliminate inertial instability remnants, while horizontal filtering leaves typical gravity wave scales untouched. In addition, we show that it is possible to separate inertial instabilities from gravity wave perturbations for infrared limb-sounding satellite profiles using a cutoff zonal wavenumber of 6.
Viktor A. Banakh, Igor N. Smalikho, and Andrey V. Falits
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-259, https://doi.org/10.5194/amt-2020-259, 2020
Revised manuscript accepted for AMT
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-227, https://doi.org/10.5194/amt-2020-227, 2020
Revised manuscript accepted for AMT
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A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of LiDAR scans and retrieval of the 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. Discuss., https://doi.org/10.5194/amt-2020-228, https://doi.org/10.5194/amt-2020-228, 2020
Revised manuscript accepted for AMT
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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. This procedure is firstly tested for a numerical dataset obtained by means of the virtual LiDAR technique applied to LES data, then to data collected during a field campaign for a wind farm in complex terrain. The results endorse the application of the LiSBOA for LiDAR-based wind resource assessment and farm diagnostics.
Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-327, https://doi.org/10.5194/amt-2020-327, 2020
Revised manuscript accepted for AMT
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Non-linear effects, such as from saturation, negatively impact satellite measured Earthshine radiance spectra. We introduce a new detection method that is based on the correlation, r, between the observed radiance and solar irradiance spectra over a 10 nm-spectral range; our Decorrelation Index (DI) is defined as DI=1−r. We developed a set of DIs for two channels (Vis and UV2) of OMI. DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
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With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Norman Wildmann, Eileen Päschke, Anke Roiger, and Christian Mallaun
Atmos. Meas. Tech., 13, 4141–4158, https://doi.org/10.5194/amt-13-4141-2020, https://doi.org/10.5194/amt-13-4141-2020, 2020
Tina Hilbig, Klaus Bramstedt, Mark Weber, John P. Burrows, and Matthijs Krijger
Atmos. Meas. Tech., 13, 3893–3907, https://doi.org/10.5194/amt-13-3893-2020, https://doi.org/10.5194/amt-13-3893-2020, 2020
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One of the main limitations for long-term space-based measurements is
instrument degradation. We present an optimisation of the
degradation correction approach (Krijger et al. 2014) for SCIAMACHY
on-board Envisat, focusing on the improvement of the solar spectral
irradiance data. The main achievement of this study is the
successful integration of SCIAMACHY’s internal white light source
(WLS) into the existing degradation model and the
characterisation of WLS ageing in space.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-184, https://doi.org/10.5194/amt-2020-184, 2020
Revised manuscript accepted for AMT
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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 for SSW monitoring. Based on our method, a SSW event can be detected and tracked, the duration and the strength of the event can be recorded. The results are consistent with other researches on this 2009 event.
Julius Polz, Christian Chwala, Maximilian Graf, and Harald Kunstmann
Atmos. Meas. Tech., 13, 3835–3853, https://doi.org/10.5194/amt-13-3835-2020, https://doi.org/10.5194/amt-13-3835-2020, 2020
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Commercial microwave link (CML) networks can be used to estimate path-averaged rain rates. This study evaluates the ability of convolutional neural networks to distinguish between wet and dry periods in CML time series data and the ability to transfer this detection skill to sensors not used for training. Our data set consists of several months of data from 3904 CMLs covering all of Germany. Compared to a previously used detection method, we could show a significant increase in performance.
Guy Delrieu, Anil Kumar Khanal, Nan Yu, Frédéric Cazenave, Brice Boudevillain, and Nicolas Gaussiat
Atmos. Meas. Tech., 13, 3731–3749, https://doi.org/10.5194/amt-13-3731-2020, https://doi.org/10.5194/amt-13-3731-2020, 2020
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, and Bryan A. Baum
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-248, https://doi.org/10.5194/amt-2020-248, 2020
Revised manuscript accepted for AMT
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As the VIIRS satellite sensor has no infrared (IR) H2O absorption bands, we construct the missing bands through 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.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-238, https://doi.org/10.5194/amt-2020-238, 2020
Revised manuscript accepted for AMT
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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 model accuracy.
Norman B. Wood and Tristan S. L'Ecuyer
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-216, https://doi.org/10.5194/amt-2020-216, 2020
Revised manuscript accepted for AMT
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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.
Andreas Behrendt, Volker Wulfmeyer, Christoph Senff, Shravan Kumar Muppa, Florian Späth, Diego Lange, Norbert Kalthoff, and Andreas Wieser
Atmos. Meas. Tech., 13, 3221–3233, https://doi.org/10.5194/amt-13-3221-2020, https://doi.org/10.5194/amt-13-3221-2020, 2020
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In order to understand how solar radiation energy hitting the ground is distributed into the atmosphere, we use a new combination of laser-based remote-sensing techniques to quantify these energy fluxes up to heights of more than 1 km above ground. Before, similar techniques had already been presented for determining the energy flux component regarding the exchange of humidity but not the warm air itself. Now, we show that this can also be measured by remote sensing with low uncertainties.
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, https://doi.org/10.5194/amt-13-2849-2020, 2020
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We provide a methodology for obtaining a function describing how the Doppler lidar telescope configuration
impacts the measurements. Together with the function itself, we also provide the uncertainties in the function, which propagate through to provide uncertainties in the geophysical quantities obtained from the measurements. The method can be used to determine how stable the instrument is over time and also identify if changes have been made in the instrument setup.
Olivier Coopmann, Vincent Guidard, Nadia Fourrié, Béatrice Josse, and Virginie Marécal
Atmos. Meas. Tech., 13, 2659–2680, https://doi.org/10.5194/amt-13-2659-2020, https://doi.org/10.5194/amt-13-2659-2020, 2020
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The objective of this paper is to make a new selection of IASI channels by taking into account inter-channel observation-error correlations. Our selection further reduces the analysis error by 3 % in temperature, 1.8 % in humidity and 0.9 % in ozone compared to Collard’s selection, when using the same number of channels. A selection of 400 IASI channels is proposed at the end of the paper which is able to further reduce analysis errors.
Matteo Puccioni and Giacomo Valerio Iungo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-27, https://doi.org/10.5194/amt-2020-27, 2020
Revised manuscript accepted for AMT
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A procedure for correcting the turbulent-energy damping connected with the range-gate 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 co-located LiDAR and sonic-anemometer measurements, then it is applied to several datasets collected at sites with different terrain roughness.
Maryna Lukach, David Dufton, Jonathan Crosier, Joshua M. Hampton, Lindsay Bennett, and Ryan R. Neely III
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-143, https://doi.org/10.5194/amt-2020-143, 2020
Revised manuscript accepted for AMT
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This paper presents a novel technique of data-driven hydrometeor classification (HC) from QVPs, 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 the dual-polarimetric weather radar observations and the embedded flexibility in the extent of granularity is the main advantage of this technique.
Floor van den Heuvel, Loris Foresti, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 13, 2481–2500, https://doi.org/10.5194/amt-13-2481-2020, https://doi.org/10.5194/amt-13-2481-2020, 2020
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In areas with reduced visibility at the ground level, radar precipitation measurements higher up in the atmosphere need to be extrapolated to the ground and be corrected for the vertical change (i.e. growth and transformation) of precipitation. This study proposes a method based on hydrometeor proportions and machine learning (ML) to apply these corrections at smaller spatiotemporal scales. In comparison with existing techniques, the ML methods can make predictions from higher altitudes.
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-147, https://doi.org/10.5194/amt-2020-147, 2020
Revised manuscript accepted for AMT
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By now, the Canonical Transform (CT) approach to the processing of Radio Occultation (RO) 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.
Guillaume Thomas, Jean-François Mahfouf, and Thibaut Montmerle
Atmos. Meas. Tech., 13, 2279–2298, https://doi.org/10.5194/amt-13-2279-2020, https://doi.org/10.5194/amt-13-2279-2020, 2020
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This paper presents the potential of a polarimetric weather radar observation operator for hydrometeor content initialization. The non-linear operator allows to simulate ZHH, ZDR, KDP and ρHV, using the T-Matrix method, prognostic variables forecasted by the AROME-France NWP model and a one-moment microphysical scheme. After sensitivity studies, it has been found that ZHH and ZDR are good candidates for hydrometeor initialization and that KDP seems useful for rain content only.
Thomas C. van Leth, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 13, 1797–1815, https://doi.org/10.5194/amt-13-1797-2020, https://doi.org/10.5194/amt-13-1797-2020, 2020
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We present a method of using collocated microwave link instruments to estimate the average size distribution of raindrops along a path of several kilometers. Our method is validated using simulated fields as well as five laser disdrometers installed along a path. We also present preliminary results from an experimental setup measuring at 26 and 38 GHz along a 2.2 km path. We show that a retrieval on the basis of microwave links can be highly accurate, provided the base power level is stable.
Philipp Gasch, Andreas Wieser, Julie K. Lundquist, and Norbert Kalthoff
Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, https://doi.org/10.5194/amt-13-1609-2020, 2020
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We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.
Tyler M. Bell, Petra Klein, Norman Wildmann, and Robert Menke
Atmos. Meas. Tech., 13, 1357–1371, https://doi.org/10.5194/amt-13-1357-2020, https://doi.org/10.5194/amt-13-1357-2020, 2020
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This study investigates the utility of using multi-Doppler retrievals during the Perdigão 2017 campaign. By combining scans from the multitude of Doppler lidars, it was possible to derive virtual towers that greatly extend the range of traditional in situ meteorological towers. Uncertainties from the measurements are analyzed and discussed. Despite multiple sources of error, it was found that the virtual towers are useful for analyzing the complex flows observed during the campaign.
Jussi Tiira and Dmitri Moisseev
Atmos. Meas. Tech., 13, 1227–1241, https://doi.org/10.5194/amt-13-1227-2020, https://doi.org/10.5194/amt-13-1227-2020, 2020
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Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.
Michael Frech and John Hubbert
Atmos. Meas. Tech., 13, 1051–1069, https://doi.org/10.5194/amt-13-1051-2020, https://doi.org/10.5194/amt-13-1051-2020, 2020
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The prime source of the temperature sensitivity of ZDR can be attributed to the antenna assembly. This result is based on over 2000 solar box scans. These data also reveal that there is a 0.6 dB decrease in gain for a 10 °C temperature increase, which directly relates to a bias of the radar reflectivity factor Z, which has not been not accounted for previously. The ZDR variability in and ZDR calibration performance of the German weather radar network are shown.
Shujie Chang, Zheng Sheng, Huadong Du, Wei Ge, and Wei Zhang
Atmos. Meas. Tech., 13, 629–644, https://doi.org/10.5194/amt-13-629-2020, https://doi.org/10.5194/amt-13-629-2020, 2020
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Because a satellite channel’s ability to resolve hyperspectral data varies with height, an improved channel selection method is proposed based on information content. An improved channel selection scheme (ICS) for a hyperspectral atmospheric infrared sounder using AIRS data based on layering is proposed. The accuracy of the retrieval temperature is improved by using our method, which means the ICS method selected in this paper is feasible and shows great promise for various applications.
Shuai Zhang, Xingyou Huang, Jinzhong Min, Zhigang Chu, Xiaoran Zhuang, and Hengheng Zhang
Atmos. Meas. Tech., 13, 537–551, https://doi.org/10.5194/amt-13-537-2020, https://doi.org/10.5194/amt-13-537-2020, 2020
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The discrimination between meteorological and non-meteorological echoes is necessary to obtain better meteorological application performance. However, the widely used algorithms have high expectations for polarimetric data, which have similar characteristics between meteorological and non-meteorological echoes in the weak-signal regions. Therefore, an improved fuzzy logic method is proposed in this paper to improve the classification performance in weak-signal regions.
Irina Strelnikova, Gerd Baumgarten, and Franz-Josef Lübken
Atmos. Meas. Tech., 13, 479–499, https://doi.org/10.5194/amt-13-479-2020, https://doi.org/10.5194/amt-13-479-2020, 2020
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One of the major problems of climate and weather modeling is atmospheric gravity waves. All measured meteorological parameters such as winds and temperature reveal superposition of large-scale background field and small-scale features created by waves. We developed an analysis technique that decomposes the measured winds and temperature into single waves, which allows for a detailed description of wave parameters. Application of this technique will improve understanding of atmospheric dynamics.
Xiaochun Zhai, Uwe Marksteiner, Fabian Weiler, Christian Lemmerz, Oliver Lux, Benjamin Witschas, and Oliver Reitebuch
Atmos. Meas. Tech., 13, 445–465, https://doi.org/10.5194/amt-13-445-2020, https://doi.org/10.5194/amt-13-445-2020, 2020
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An airborne prototype called A2D was developed for validating the Aeolus measurement principle based on realistic atmospheric signals. However, the atmospheric and instrumental variability currently limit the reliability and repeatability of the measured Rayleigh response calibration (MRRC), which is a prerequisite for accurate wind retrieval. A procedure for a simulated Rayleigh response calibration (SRRC) is developed and presented to resolve these limitations of the A2D Rayleigh channel MRRC.
Wenying Su, Patrick Minnis, Lusheng Liang, David P. Duda, Konstantin Khlopenkov, Mandana M. Thieman, Yinan Yu, Allan Smith, Steven Lorentz, Daniel Feldman, and Francisco P. J. Valero
Atmos. Meas. Tech., 13, 429–443, https://doi.org/10.5194/amt-13-429-2020, https://doi.org/10.5194/amt-13-429-2020, 2020
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The Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. In this paper, the algorithm used to derive daytime shortwave and longwave fluxes from NISTAR measurements is presented.
Christoph Kalicinsky, Robert Reisch, Peter Knieling, and Ralf Koppmann
Atmos. Meas. Tech., 13, 467–477, https://doi.org/10.5194/amt-13-467-2020, https://doi.org/10.5194/amt-13-467-2020, 2020
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This study presents an approach to analyse unequally spaced time series of OH* temperatures with respect to time-varying periodic fluctuations. The approach is based on the classical Lomb–Scargle periodogram and, additionally, the idea of a moving window is used. Furthermore, a fast and easy way to analyse the significance of the results is presented. The general performance of the approach is tested with artificially generated time series and results for real observations are presented.
Fei Yang, Jiming Guo, Junbo Shi, Xiaolin Meng, Yinzhi Zhao, Lv Zhou, and Di Zhang
Atmos. Meas. Tech., 13, 355–371, https://doi.org/10.5194/amt-13-355-2020, https://doi.org/10.5194/amt-13-355-2020, 2020
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The development of GPS station networks that provide rich data sources containing atmospheric information will enable more GPS applications in the field of meteorology. This study describes a genetic algorithm for the water vapour tomography; overcomes the ill-conditioned problem; and eliminates the reliance on excessive constraints, priori information, and external data. It is proven in the paper that accurate 3-D water vapour distribution can be provided by this study for atmospheric research.
Sergio DeSouza-Machado, L. Larrabee Strow, Howard Motteler, and Scott Hannon
Atmos. Meas. Tech., 13, 323–339, https://doi.org/10.5194/amt-13-323-2020, https://doi.org/10.5194/amt-13-323-2020, 2020
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The current instruments being used for weather forecasting and climate require accurate radiative transfer codes to process the acquired data. In addition the codes are becoming more realistic, as they can now account for the effects of cloud and aerosols, rather than only simulating radiances for a clear sky. We describe a fast, accurate, and general purpose code that we have developed to help model data from these instruments.
Philippe Baron, Satoshi Ochiai, Eric Dupuy, Richard Larsson, Huixin Liu, Naohiro Manago, Donal Murtagh, Shin-ichiro Oyama, Hideo Sagawa, Akinori Saito, Takatoshi Sakazaki, Masato Shiotani, and Makoto Suzuki
Atmos. Meas. Tech., 13, 219–237, https://doi.org/10.5194/amt-13-219-2020, https://doi.org/10.5194/amt-13-219-2020, 2020
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Submillimeter-Wave Limb-Emission Sounder 2 (SMILES-2) is a satellite mission proposed in Japan to probe the middle and upper atmosphere (20–160 km). The key products are wind, temperature and density. If selected, this mission could provide new insights into vertical coupling in the atmosphere and could help improve weather and climate models. We conducted simulation studies to assess the measurement performances in the altitude range 60–110 km, with a special focus on the geomagnetic effects.
Norman Wildmann, Nicola Bodini, Julie K. Lundquist, Ludovic Bariteau, and Johannes Wagner
Atmos. Meas. Tech., 12, 6401–6423, https://doi.org/10.5194/amt-12-6401-2019, https://doi.org/10.5194/amt-12-6401-2019, 2019
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Turbulence is the variation of wind velocity on short timescales. In this study we introduce a new method to measure turbulence in a two-dimensionial plane with lidar instruments. The method allows for the detection and quantification of subareas of distinct turbulence conditions in the observed plane. We compare the results to point and profile measurements with more established instruments. It is shown that turbulence below low-level jets and in wind turbine wakes can be investigated this way.
David Ian Duncan, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 12, 6341–6359, https://doi.org/10.5194/amt-12-6341-2019, https://doi.org/10.5194/amt-12-6341-2019, 2019
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The overlapping beams of some satellite observations contain spatial information that is discarded by most data processing techniques. This study applies an established technique in a new way to improve the spatial resolution of retrieval targets, effectively using the overlapping information to achieve a higher ultimate resolution. It is argued that this is a more optimal use of the total information available from current microwave sensors, using AMSR2 as an example.
Robert Reichert, Bernd Kaifler, Natalie Kaifler, Markus Rapp, Pierre-Dominique Pautet, Michael J. Taylor, Alexander Kozlovsky, Mark Lester, and Rigel Kivi
Atmos. Meas. Tech., 12, 5997–6015, https://doi.org/10.5194/amt-12-5997-2019, https://doi.org/10.5194/amt-12-5997-2019, 2019
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To determine gravity wave properties like wavelengths, periods and propagation directions at mesospheric altitudes (∼ 86 km) we combine lidar and airglow temperature and meteor radar wind data. By means of wavelet transformation we investigate the wave field and determine intrinsic wave properties as functions of time and period. We are able to identify several gravity wave packets by their distinct propagation and discover a superposition with possible wave–wave and wave–mean-flow interaction.
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