Research article
12 Sep 2018
Research article
| 12 Sep 2018
Characterisation of the melting layer variability in an Alpine valley based on polarimetric X-band radar scans
Floor van den Heuvel et al.
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Josué Gehring, Annika Oertel, Étienne Vignon, Nicolas Jullien, Nikola Besic, and Alexis Berne
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Jussi Leinonen and Alexis Berne
Atmos. Meas. Tech., 13, 2949–2964, https://doi.org/10.5194/amt-13-2949-2020, https://doi.org/10.5194/amt-13-2949-2020, 2020
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Nicolas Jullien, Étienne Vignon, Michael Sprenger, Franziska Aemisegger, and Alexis Berne
The Cryosphere, 14, 1685–1702, https://doi.org/10.5194/tc-14-1685-2020, https://doi.org/10.5194/tc-14-1685-2020, 2020
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Floor van den Heuvel, Loris Foresti, Marco Gabella, Urs Germann, and Alexis Berne
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Mathieu Schaer, Christophe Praz, and Alexis Berne
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Seppo Pulkkinen, Daniele Nerini, Andrés A. Pérez Hortal, Carlos Velasco-Forero, Alan Seed, Urs Germann, and Loris Foresti
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Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
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Florentin Lemonnier, Jean-Baptiste Madeleine, Chantal Claud, Christophe Genthon, Claudio Durán-Alarcón, Cyril Palerme, Alexis Berne, Niels Souverijns, Nicole van Lipzig, Irina V. Gorodetskaya, Tristan L'Ecuyer, and Norman Wood
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Claudio Durán-Alarcón, Brice Boudevillain, Christophe Genthon, Jacopo Grazioli, Niels Souverijns, Nicole P. M. van Lipzig, Irina V. Gorodetskaya, and Alexis Berne
The Cryosphere, 13, 247–264, https://doi.org/10.5194/tc-13-247-2019, https://doi.org/10.5194/tc-13-247-2019, 2019
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Niels Souverijns, Alexandra Gossart, Stef Lhermitte, Irina V. Gorodetskaya, Jacopo Grazioli, Alexis Berne, Claudio Duran-Alarcon, Brice Boudevillain, Christophe Genthon, Claudio Scarchilli, and Nicole P. M. van Lipzig
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Christophe Genthon, Alexis Berne, Jacopo Grazioli, Claudio Durán Alarcón, Christophe Praz, and Brice Boudevillain
Earth Syst. Sci. Data, 10, 1605–1612, https://doi.org/10.5194/essd-10-1605-2018, https://doi.org/10.5194/essd-10-1605-2018, 2018
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Nikola Besic, Josué Gehring, Christophe Praz, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, https://doi.org/10.5194/amt-11-4847-2018, 2018
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In this paper we propose an innovative approach for hydrometeor de-mixing, i.e., to identify and quantify the presence of mixtures of different hydrometeor types in a radar sampling volume. It is a bin-based approach, inspired by conventional decomposition methods and evaluated using C- and X-band radar measurements compared with synchronous ground observations. The paper also investigates the potential influence of incoherency in the backscattering from hydrometeor mixtures in a radar volume.
Fanny Jeanneret, Giovanni Martucci, Simon Pinnock, and Alexis Berne
Atmos. Meas. Tech., 11, 4153–4170, https://doi.org/10.5194/amt-11-4153-2018, https://doi.org/10.5194/amt-11-4153-2018, 2018
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Above mountainous regions, satellites may have difficulty in discriminating snow from clouds: this study proposes a new method that combines different ground-based measurements to assess the sky cloudiness with high temporal resolution. The method's output is used as input to a model capable of identifying false satellite cloud detections. Results show that 62 ± 13 % of these false detections can be identified by the model when applied to the AVHRR-PM and MODIS Aqua data sets of the Cloud_cci.
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018, https://doi.org/10.5194/amt-11-3883-2018, 2018
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This work presents a polarimetric forward operator for the COSMO weather prediction model. This tool is able to simulate radar observables from the state of the atmosphere simulated by the model, taking into account most physical aspects of radar beam propagation and backscattering. This operator was validated with a large dataset of radar observations from several instruments and it was shown that is able to simulate a realistic radar signature in liquid precipitation.
Daniel Wolfensberger, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, and Alexis Berne
Atmos. Chem. Phys., 17, 14253–14273, https://doi.org/10.5194/acp-17-14253-2017, https://doi.org/10.5194/acp-17-14253-2017, 2017
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Precipitation intensities simulated by the COSMO weather prediction model are compared to radar observations over a range of spatial and temporal scales using the universal multifractal framework. Our results highlight the strong influence of meteorological and topographical features on the multifractal characteristics of precipitation. Moreover, the influence of the subgrid parameterizations of COSMO is clearly visible by a break in the scaling properties that is absent from the radar data.
Jacopo Grazioli, Christophe Genthon, Brice Boudevillain, Claudio Duran-Alarcon, Massimo Del Guasta, Jean-Baptiste Madeleine, and Alexis Berne
The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, https://doi.org/10.5194/tc-11-1797-2017, 2017
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We present medium and long-term measurements of precipitation in a coastal region of Antarctica. These measurements are among the first of their kind on the Antarctic continent and combine remote sensing with in situ observations. The benefits of this synergy are demonstrated and the lessons learned from this measurements, which are still ongoing, are very important for the creation of similar observatories elsewhere on the continent.
Timothy H. Raupach and Alexis Berne
Atmos. Meas. Tech., 10, 2573–2594, https://doi.org/10.5194/amt-10-2573-2017, https://doi.org/10.5194/amt-10-2573-2017, 2017
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The raindrop size distribution (DSD) describes the microstructure of rain. It is required knowledge for weather radar applications and has broad applicability to studies of rainfall processes, including weather models and rain retrieval algorithms. We present a new technique for estimating the DSD from polarimetric radar data. The new method was tested in three different domains, and its performance was found to be similar to and often better than an an existing DSD retrieval method.
Daniele Nerini, Nikola Besic, Ioannis Sideris, Urs Germann, and Loris Foresti
Hydrol. Earth Syst. Sci., 21, 2777–2797, https://doi.org/10.5194/hess-21-2777-2017, https://doi.org/10.5194/hess-21-2777-2017, 2017
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Stochastic generators are effective tools for the quantification of uncertainty in a number of applications with weather radar data, including quantitative precipitation estimation and very short-term forecasting. However, most of the current stochastic rainfall field generators cannot handle spatial non-stationarity. We propose an approach based on the short-space Fourier transform, which aims to reproduce the local spatial structure of the observed rainfall fields.
Christophe Praz, Yves-Alain Roulet, and Alexis Berne
Atmos. Meas. Tech., 10, 1335–1357, https://doi.org/10.5194/amt-10-1335-2017, https://doi.org/10.5194/amt-10-1335-2017, 2017
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The Multi-Angle Snowflake Camera (MASC) provides high-resolution pictures of individual falling snowflakes and ice crystals. A method is proposed to automatically classify these pictures into six classes of snowflakes as well to estimate the degree of riming and to detect whether or not the particles are melting. Multinomial logistic regression is used with a manually classified
reference set. The evaluation demonstrates the good and reliable performance of the proposed technique.
Guillaume Nord, Brice Boudevillain, Alexis Berne, Flora Branger, Isabelle Braud, Guillaume Dramais, Simon Gérard, Jérôme Le Coz, Cédric Legoût, Gilles Molinié, Joel Van Baelen, Jean-Pierre Vandervaere, Julien Andrieu, Coralie Aubert, Martin Calianno, Guy Delrieu, Jacopo Grazioli, Sahar Hachani, Ivan Horner, Jessica Huza, Raphaël Le Boursicaud, Timothy H. Raupach, Adriaan J. Teuling, Magdalena Uber, Béatrice Vincendon, and Annette Wijbrans
Earth Syst. Sci. Data, 9, 221–249, https://doi.org/10.5194/essd-9-221-2017, https://doi.org/10.5194/essd-9-221-2017, 2017
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A high space–time resolution dataset linking hydrometeorological forcing and hydro-sedimentary response in a mesoscale catchment (Auzon, 116 km2) of the Ardèche region (France) is presented. This region is subject to precipitating systems of Mediterranean origin, which can result in significant rainfall amount. The data presented cover a period of 4 years (2011–2014) and aim at improving the understanding of processes triggering flash floods.
Nikola Besic, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, https://doi.org/10.5194/amt-9-4425-2016, 2016
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In this paper we propose a novel semi-supervised method for hydrometeor classification, which takes into account both the specificities of acquired polarimetric radar measurements and the presumed electromagnetic behavior of different hydrometeor types. The method has been applied on three datasets, each acquired by different C-band radar from the Swiss network, and on two X-band research radar datasets. The obtained classification is found to be of high quality.
Luca Panziera, Marco Gabella, Stefano Zanini, Alessandro Hering, Urs Germann, and Alexis Berne
Hydrol. Earth Syst. Sci., 20, 2317–2332, https://doi.org/10.5194/hess-20-2317-2016, https://doi.org/10.5194/hess-20-2317-2016, 2016
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This paper presents a novel system to issue heavy rainfall alerts for predefined geographical regions by evaluating the sum of precipitation fallen in the immediate past and expected in the near future. In order to objectively define the thresholds for the alerts, an extreme rainfall analysis for the 159 regions used for official warnings in Switzerland was developed. It is shown that the system has additional lead time with respect to thunderstorm tracking tools targeted for convective storms.
J. Grazioli, G. Lloyd, L. Panziera, C. R. Hoyle, P. J. Connolly, J. Henneberger, and A. Berne
Atmos. Chem. Phys., 15, 13787–13802, https://doi.org/10.5194/acp-15-13787-2015, https://doi.org/10.5194/acp-15-13787-2015, 2015
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This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during CLACE2014. From polarimetric radar and in situ observations, riming is shown to be an important process leading to more intense snowfall. Riming is usually associated with more intense turbulence providing supercooled liquid water. Distinct features are identified in the vertical structure of polarimetric radar variables.
M. Stähli, M. Sättele, C. Huggel, B. W. McArdell, P. Lehmann, A. Van Herwijnen, A. Berne, M. Schleiss, A. Ferrari, A. Kos, D. Or, and S. M. Springman
Nat. Hazards Earth Syst. Sci., 15, 905–917, https://doi.org/10.5194/nhess-15-905-2015, https://doi.org/10.5194/nhess-15-905-2015, 2015
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This review paper describes the state of the art in monitoring and predicting rapid mass movements for early warning. It further presents recent innovations in observation technologies and modelling to be used in future early warning systems (EWS). Finally, the paper proposes avenues towards successful implementation of next-generation EWS.
T. H. Raupach and A. Berne
Atmos. Meas. Tech., 8, 343–365, https://doi.org/10.5194/amt-8-343-2015, https://doi.org/10.5194/amt-8-343-2015, 2015
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Using the 2-D video disdrometer (2DVD) as a reference, a technique to correct the spectra of drop size distribution (DSD) measured by Parsivel disdrometers (1st and 2nd generation) is proposed. The measured velocities and equivolume diameters are corrected to better match those from the 2DVD. The correction is evaluated using data from southern France and the Swiss Plateau. It appears to be similar for both climatologies, and to improve the consistency with colocated 2DVDs and rain gauges.
J. Grazioli, D. Tuia, and A. Berne
Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, https://doi.org/10.5194/amt-8-149-2015, 2015
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A new approach for hydrometeor classification from polarimetric radar measurements is proposed. It takes adavantage of clustering techniques to objectively determine the number of hydrometeor classes that can be reliably identified. The proposed method is tested using observations from an X-band polarimetric radar in different regions and evaluated by comparison with existing algorithms and with measurements from a ground-based 2D video disdrometer (providing 2-D views of falling hydrometeors).
J. Grazioli, D. Tuia, S. Monhart, M. Schneebeli, T. Raupach, and A. Berne
Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, https://doi.org/10.5194/amt-7-2869-2014, 2014
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Spectral replacement using machine learning methods for continuous mapping of the Geostationary Environment Monitoring Spectrometer (GEMS)
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning
Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems
Satellite observations of gravity wave momentum flux in the mesosphere and lower thermosphere (MLT): feasibility and requirements
An improved near-real-time precipitation retrieval for Brazil
Radio frequency interference detection and mitigation in the DWD C-band weather radar network
Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign
Long-distance propagation of 162 MHz shipping information links associated with sporadic E
Estimation of refractivity uncertainties and vertical error correlations in collocated radio occultations, radiosondes, and model forecasts
DeepPrecip: a deep neural network for precipitation retrievals
Machine learning-based prediction of Alpine foehn events using GNSS troposphere products: first results for Altdorf, Switzerland
Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras
Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data
Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion
Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at La Réunion Island and the Observatoire de Haute Provence
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Sensitivity analysis of DSD retrievals from polarimetric radar in stratiform rain based on the μ–Λ relationship
On the use of high-frequency surface wave oceanographic research radars as bistatic single-frequency oblique ionospheric sounders
High Resolution 3D Winds Derived from a Newly Developed WISSDOM Synthesis Scheme using Multiple Doppler Lidars and Observations
A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System
Hierarchical deconvolution for incoherent scatter radar data
An alternative cloud index for estimating downwelling surface solar irradiance from various satellite imagers in the framework of a Heliosat-V method
ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO)
On the derivation of zonal and meridional wind components from Aeolus horizontal line-of-sight wind
Quantification of lightning-produced NOx over the Pyrenees and the Ebro Valley by using different TROPOMI-NO2 and cloud research products
Sensitivity analysis of attenuation in convective rainfall at X-band frequency using the mountain reference technique
A new scanning scheme and flexible retrieval for mean winds and gusts from Doppler lidar measurements
Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone
High-resolution typhoon precipitation integrations using satellite infrared observations and multisource data
Continuous temperature soundings at the stratosphere and lower mesosphere with a ground-based radiometer considering the Zeeman effect
Retrieval of solar-induced chlorophyll fluorescence (SIF) from satellite measurements: comparison of SIF between TanSat and OCO-2
Identification of tropical cyclones via deep convolutional neural network based on satellite cloud images
Time evolution of temperature profiles retrieved from 13 years of infrared atmospheric sounding interferometer (IASI) data using an artificial neural network
Emissivity retrievals with FORUM's end-to-end simulator: challenges and recommendations
Detecting wave features in Doppler radial velocity radar observations
Remote sensing of solar surface radiation – a reflection of concepts, applications and input data based on experience with the effective cloud albedo
Snow microphysical retrieval from the NASA D3R radar during ICE-POP 2018
Retrieval improvements for the ALADIN Airborne Demonstrator in support of the Aeolus wind product validation
Cloud-probability-based estimation of black-sky surface albedo from AVHRR data
A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations
Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): retrieval framework and first results
Improving thermodynamic profile retrievals from microwave radiometers by including radio acoustic sounding system (RASS) observations
Calibration of radar differential reflectivity using quasi-vertical profiles
Improvement in algorithms for quality control of weather radar data (RADVOL-QC system)
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
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Yeeun Lee, Myoung-Hwan Ahn, Mina Kang, and Mijin Eo
Atmos. Meas. Tech., 16, 153–168, https://doi.org/10.5194/amt-16-153-2023, https://doi.org/10.5194/amt-16-153-2023, 2023
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This study aims to verify that a partly defective hyperspectral measurement can be successfully reproduced with concise machine learning models coupled with principal component analysis. Evaluation of the approach is performed with radiances and retrieval results of ozone and cloud properties. Considering that GEMS is the first geostationary UV–VIS hyperspectral spectrometer, we expect our findings can be introduced further to similar geostationary environmental instruments to be launched soon.
Mathias Gergely, Maximilian Schaper, Matthias Toussaint, and Michael Frech
Atmos. Meas. Tech., 15, 7315–7335, https://doi.org/10.5194/amt-15-7315-2022, https://doi.org/10.5194/amt-15-7315-2022, 2022
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This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
Kenneth A. Brown and Thomas G. Herges
Atmos. Meas. Tech., 15, 7211–7234, https://doi.org/10.5194/amt-15-7211-2022, https://doi.org/10.5194/amt-15-7211-2022, 2022
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The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022, https://doi.org/10.5194/amt-15-7105-2022, 2022
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Water vapor concentration in the atmosphere at small scales (< 6 km) is considered. The measurements show Gaussian random field behavior following Kolmogorov's theory of turbulence two-thirds law. These properties can be useful when estimating the water vapor variability within a given observed satellite scene or when different water vapor measurements have to be merged consistently.
Qiuyu Chen, Konstantin Ntokas, Björn Linder, Lukas Krasauskas, Manfred Ern, Peter Preusse, Jörn Ungermann, Erich Becker, Martin Kaufmann, and Martin Riese
Atmos. Meas. Tech., 15, 7071–7103, https://doi.org/10.5194/amt-15-7071-2022, https://doi.org/10.5194/amt-15-7071-2022, 2022
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Observations of phase speed and direction spectra as well as zonal mean net gravity wave momentum flux are required to understand how gravity waves reach the mesosphere–lower thermosphere and how they there interact with background flow. To this end we propose flying two CubeSats, each deploying a spatial heterodyne spectrometer for limb observation of the airglow. End-to-end simulations demonstrate that individual gravity waves are retrieved faithfully for the expected instrument performance.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Maximilian Schaper, Michael Frech, David Michaelis, Cornelius Hald, and Benjamin Rohrdantz
Atmos. Meas. Tech., 15, 6625–6642, https://doi.org/10.5194/amt-15-6625-2022, https://doi.org/10.5194/amt-15-6625-2022, 2022
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C-band weather radar data are commonly compromised by radio frequency interference (RFI) from external sources. It is not possible to separate a superimposed interference signal from the radar data. Therefore, the best course of action is to shut down RFI sources as quickly as possible. An automated RFI detection algorithm has been developed. Since its implementation, persistent RFI sources are eliminated much more quickly, while the number of short-lived RFI sources keeps steadily increasing.
Oliver Lux, Benjamin Witschas, Alexander Geiß, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Stephan Rahm, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 6467–6488, https://doi.org/10.5194/amt-15-6467-2022, https://doi.org/10.5194/amt-15-6467-2022, 2022
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We discuss the influence of different quality control schemes on the results of Aeolus wind product validation and present statistical tools for ensuring consistency and comparability among diverse validation studies with regard to the specific error characteristics of the Rayleigh-clear and Mie-cloudy winds. The developed methods are applied for the validation of Aeolus winds against an ECMWF model background and airborne wind lidar data from the Joint Aeolus Tropical Atlantic Campaign.
Alex T. Chartier, Thomas R. Hanley, and Daniel J. Emmons
Atmos. Meas. Tech., 15, 6387–6393, https://doi.org/10.5194/amt-15-6387-2022, https://doi.org/10.5194/amt-15-6387-2022, 2022
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This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.
Johannes K. Nielsen, Hans Gleisner, Stig Syndergaard, and Kent B. Lauritsen
Atmos. Meas. Tech., 15, 6243–6256, https://doi.org/10.5194/amt-15-6243-2022, https://doi.org/10.5194/amt-15-6243-2022, 2022
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This paper provides a new way to estimate uncertainties and error correlations. The method is a generalization of a known method called the
three-cornered hat: Instead of calculating uncertainties from assumed knowledge about the observation method, uncertainties and error correlations are estimated statistically from tree independent observation series, measuring the same variable. The results are useful for future estimation of atmospheric-specific humidity from the bending of radio waves.
Fraser King, George Duffy, Lisa Milani, Christopher G. Fletcher, Claire Pettersen, and Kerstin Ebell
Atmos. Meas. Tech., 15, 6035–6050, https://doi.org/10.5194/amt-15-6035-2022, https://doi.org/10.5194/amt-15-6035-2022, 2022
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Under warmer global temperatures, precipitation patterns are expected to shift substantially, with critical impact on the global water-energy budget. In this work, we develop a deep learning model for predicting snow and rain accumulation based on surface radar observations of the lower atmosphere. Our model demonstrates improved skill over traditional methods and provides new insights into the regions of the atmosphere that provide the most significant contributions to high model accuracy.
Matthias Aichinger-Rosenberger, Elmar Brockmann, Laura Crocetti, Benedikt Soja, and Gregor Moeller
Atmos. Meas. Tech., 15, 5821–5839, https://doi.org/10.5194/amt-15-5821-2022, https://doi.org/10.5194/amt-15-5821-2022, 2022
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This study develops an innovative approach for the detection and prediction of foehn winds. The approach uses products generated from GNSS (Global Navigation Satellite Systems) in combination with machine learning-based classification algorithms to detect and predict foehn winds at Altdorf, Switzerland. Results are encouraging and comparable to similar studies using meteorological data, which might qualify the method as an additional tool for short-term foehn forecasting in the future.
Gunter Stober, Alan Liu, Alexander Kozlovsky, Zishun Qiao, Ales Kuchar, Christoph Jacobi, Chris Meek, Diego Janches, Guiping Liu, Masaki Tsutsumi, Njål Gulbrandsen, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, and Nicholas Mitchell
Atmos. Meas. Tech., 15, 5769–5792, https://doi.org/10.5194/amt-15-5769-2022, https://doi.org/10.5194/amt-15-5769-2022, 2022
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Precise and accurate measurements of vertical winds at the mesosphere and lower thermosphere are rare. Although meteor radars have been used for decades to observe horizontal winds, their ability to derive reliable vertical wind measurements was always questioned. In this article, we provide mathematical concepts to retrieve mathematically and physically consistent solutions, which are compared to the state-of-the-art non-hydrostatic model UA-ICON.
Benjamin Schumacher, Marwan Katurji, Jiawei Zhang, Peyman Zawar-Reza, Benjamin Adams, and Matthias Zeeman
Atmos. Meas. Tech., 15, 5681–5700, https://doi.org/10.5194/amt-15-5681-2022, https://doi.org/10.5194/amt-15-5681-2022, 2022
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This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.
Laura M. Tomkins, Sandra E. Yuter, Matthew A. Miller, and Luke R. Allen
Atmos. Meas. Tech., 15, 5515–5525, https://doi.org/10.5194/amt-15-5515-2022, https://doi.org/10.5194/amt-15-5515-2022, 2022
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Locally higher radar reflectivity values in winter storms can mean more snowfall or a transition from snow to mixtures of snow, partially melted snow, and/or rain. We use the correlation coefficient to de-emphasize regions of mixed precipitation. Visual muting is valuable for analyzing and monitoring evolving weather conditions during winter storm events.
Willem J. Marais and Matthew Hayman
Atmos. Meas. Tech., 15, 5159–5180, https://doi.org/10.5194/amt-15-5159-2022, https://doi.org/10.5194/amt-15-5159-2022, 2022
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For atmospheric science and weather prediction, it is important to make water vapor measurements in real time. A low-cost lidar instrument has been developed by Montana State University and the National Center for Atmospheric Research. We developed an advanced signal-processing method to extend the scientific capability of the lidar instrument. With the new method we show that the maximum altitude at which the MPD can make water vapor measurements can be extended up to 8 km.
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
EGUsphere, https://doi.org/10.5194/egusphere-2022-822, https://doi.org/10.5194/egusphere-2022-822, 2022
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Aeolus is the first space-borne wind lidar providing global wind measurements since 2018. This study offers a comprehensive of analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022, https://doi.org/10.5194/amt-15-5033-2022, 2022
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 15, 4951–4969, https://doi.org/10.5194/amt-15-4951-2022, https://doi.org/10.5194/amt-15-4951-2022, 2022
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Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape–size (μ–Λ) relationship.
Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, and Teresa Updyke
Atmos. Meas. Tech., 15, 4531–4545, https://doi.org/10.5194/amt-15-4531-2022, https://doi.org/10.5194/amt-15-4531-2022, 2022
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This investigation demonstrates how useful ionospheric parameters can be extracted from existing high-frequency radars that are used for oceanographic research. The methodology presented can be used by scientists and radio amateurs to understand ionospheric dynamics.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and Gyuwon Lee
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-218, https://doi.org/10.5194/amt-2022-218, 2022
Revised manuscript accepted for AMT
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Since the winds in clear-air conditions usually play an important role in the initiations of various weather systems and phenomena. A modified WISSDOM synthesis scheme was developed to derive high-quality and high-spatial resolution of 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this newly developed scheme were be well evaluated associated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Hui Liu, Kevin Garrett, Kayo Ide, Ross N. Hoffman, and Katherine E. Lukens
Atmos. Meas. Tech., 15, 3925–3940, https://doi.org/10.5194/amt-15-3925-2022, https://doi.org/10.5194/amt-15-3925-2022, 2022
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A total least squares (TLS) regression is used to optimally estimate linear speed-dependent biases between Aeolus Level-2B winds and short-term (6 h) forecasts of NOAA’s FV3GFS. The winds for 1–7 September 2019 are examined. Clear speed-dependent biases for both Mie and Rayleigh winds are found, particularly in the tropics and Southern Hemisphere. Use of the TLS correction improves the forecast of the 26–28 November 2019 winter storm over the USA.
Snizhana Ross, Arttu Arjas, Ilkka I. Virtanen, Mikko J. Sillanpää, Lassi Roininen, and Andreas Hauptmann
Atmos. Meas. Tech., 15, 3843–3857, https://doi.org/10.5194/amt-15-3843-2022, https://doi.org/10.5194/amt-15-3843-2022, 2022
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Radar measurements of thermal fluctuations in the Earth's ionosphere produce weak signals, and tuning to specific altitudes results in suboptimal resolution for other regions, making an accurate analysis of these changes difficult. A novel approach to improve the resolution and remove measurement noise is considered. The method can capture variable characteristics, making it ideal for the study of a large range of data. Synthetically generated examples and two measured datasets were considered.
Benoît Tournadre, Benoît Gschwind, Yves-Marie Saint-Drenan, Xuemei Chen, Rodrigo Amaro E Silva, and Philippe Blanc
Atmos. Meas. Tech., 15, 3683–3704, https://doi.org/10.5194/amt-15-3683-2022, https://doi.org/10.5194/amt-15-3683-2022, 2022
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Solar radiation received by the Earth's surface is valuable information for various fields like the photovoltaic industry or climate research. Pictures taken from satellites can be used to estimate the solar radiation from cloud reflectivity. Two issues for a good estimation are different instrumentations and orbits. We modify a widely used method that is today only used on geostationary satellites, so it can be applied on instruments on different orbits and with different sensitivities.
Alfonso Ferrone, Anne-Claire Billault-Roux, and Alexis Berne
Atmos. Meas. Tech., 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, https://doi.org/10.5194/amt-15-3569-2022, 2022
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The Micro Rain Radar PRO (MRR-PRO) is a meteorological radar, with a relevant set of features for deployment in remote locations. We developed an algorithm, named ERUO, for the processing of its measurements of snowfall. The algorithm addresses typical issues of the raw spectral data, such as interference lines, but also improves the quality and sensitivity of the radar variables. ERUO has been evaluated over four different datasets collected in Antarctica and in the Swiss Jura.
Isabell Krisch, Neil P. Hindley, Oliver Reitebuch, and Corwin J. Wright
Atmos. Meas. Tech., 15, 3465–3479, https://doi.org/10.5194/amt-15-3465-2022, https://doi.org/10.5194/amt-15-3465-2022, 2022
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The Aeolus satellite measures global height resolved profiles of wind along a certain line-of-sight. However, for atmospheric dynamics research, wind measurements along the three cardinal axes are most useful. This paper presents methods to convert the measurements into zonal and meridional wind components. By combining the measurements during ascending and descending orbits, we achieve good derivation of zonal wind (equatorward of 80° latitude) and meridional wind (poleward of 70° latitude).
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
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Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Guy Delrieu, Anil Kumar Khanal, Frédéric Cazenave, and Brice Boudevillain
Atmos. Meas. Tech., 15, 3297–3314, https://doi.org/10.5194/amt-15-3297-2022, https://doi.org/10.5194/amt-15-3297-2022, 2022
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The RadAlp experiment aims at improving quantitative precipitation estimation in the Alps thanks to X-band polarimetric radars and in situ measurements deployed in Grenoble, France. We revisit the physics of propagation and attenuation of microwaves in rain. We perform a generalized sensitivity analysis in order to establish useful parameterization for attenuation corrections. Originality lies in the use of otherwise undesired mountain returns for constraining the considered physical model.
Julian Steinheuer, Carola Detring, Frank Beyrich, Ulrich Löhnert, Petra Friederichs, and Stephanie Fiedler
Atmos. Meas. Tech., 15, 3243–3260, https://doi.org/10.5194/amt-15-3243-2022, https://doi.org/10.5194/amt-15-3243-2022, 2022
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Doppler wind lidars (DWLs) allow the determination of wind profiles with high vertical resolution and thus provide an alternative to meteorological towers. We address the question of whether wind gusts can be derived since they are short-lived phenomena. Therefore, we compare different DWL configurations and develop a new method applicable to all of them. A fast continuous scanning mode that completes a full observation cycle within 3.4 s is found to be the best-performing configuration.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
Atmos. Meas. Tech., 15, 2939–2953, https://doi.org/10.5194/amt-15-2939-2022, https://doi.org/10.5194/amt-15-2939-2022, 2022
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
You Zhao, Chao Liu, Di Di, Ziqiang Ma, and Shihao Tang
Atmos. Meas. Tech., 15, 2791–2805, https://doi.org/10.5194/amt-15-2791-2022, https://doi.org/10.5194/amt-15-2791-2022, 2022
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A typhoon is a high-impact atmospheric phenomenon that causes most significant socioeconomic damage, and its precipitation observation is always needed for typhoon characteristics and disaster prevention. This study developed a typhoon precipitation fusion method to combine observations from satellite radiometers, rain gauges and reanalysis to provide much improved typhoon precipitation datasets.
Witali Krochin, Francisco Navas-Guzmán, David Kuhl, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 15, 2231–2249, https://doi.org/10.5194/amt-15-2231-2022, https://doi.org/10.5194/amt-15-2231-2022, 2022
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This study leverages atmospheric temperature measurements performed with a ground-based radiometer making use of data that was collected during a 4-year observational campaign applying a new retrieval algorithm that improves the maximal altitude range from 45 to 55 km. The measurements are validated against two independent data sets, MERRA2 reanalysis data and the meteorological analysis of NAVGEM-HA.
Lu Yao, Yi Liu, Dongxu Yang, Zhaonan Cai, Jing Wang, Chao Lin, Naimeng Lu, Daren Lyu, Longfei Tian, Maohua Wang, Zengshan Yin, Yuquan Zheng, and Sisi Wang
Atmos. Meas. Tech., 15, 2125–2137, https://doi.org/10.5194/amt-15-2125-2022, https://doi.org/10.5194/amt-15-2125-2022, 2022
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A physics-based SIF retrieval algorithm, IAPCAS/SIF, is introduced and applied to OCO-2 and TanSat measurements. The strong linear relationship between OCO-2 SIF retrieved by IAPCAS/SIF and the official product indicates the algorithm's reliability. The good consistency in the spatiotemporal patterns and magnitude of the OCO-2 and TanSat SIF products suggests that the combinative usage of multi-satellite products has potential and that such work would contribute to further research.
Biao Tong, Xiangfei Sun, Jiyang Fu, Yuncheng He, and Pakwai Chan
Atmos. Meas. Tech., 15, 1829–1848, https://doi.org/10.5194/amt-15-1829-2022, https://doi.org/10.5194/amt-15-1829-2022, 2022
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In recent years, there has been numerous research on tropical cyclone (TC) observation based on satellite cloud images (SCIs), but most methods are limited by low efficiency and subjectivity. To overcome subjectivity and improve efficiency of traditional methods, this paper uses deep learning technology to do further research on fingerprint identification of TCs. Results provide an automatic and objective method to distinguish TCs from SCIs and are convenient for subsequent research.
Marie Bouillon, Sarah Safieddine, Simon Whitburn, Lieven Clarisse, Filipe Aires, Victor Pellet, Olivier Lezeaux, Noëlle A. Scott, Marie Doutriaux-Boucher, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 1779–1793, https://doi.org/10.5194/amt-15-1779-2022, https://doi.org/10.5194/amt-15-1779-2022, 2022
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The IASI instruments have been observing Earth since 2007. We use a neural network to retrieve atmospheric temperatures. This new temperature data record is validated against other datasets and shows good agreement. We use this new dataset to compute trends over the 2008–2020 period. We found a warming of the troposphere, more important at the poles. In the stratosphere, we found that temperatures decrease everywhere except at the South Pole. The cooling is more pronounced at the South pole.
Maya Ben-Yami, Hilke Oetjen, Helen Brindley, William Cossich, Dulce Lajas, Tiziano Maestri, Davide Magurno, Piera Raspollini, Luca Sgheri, and Laura Warwick
Atmos. Meas. Tech., 15, 1755–1777, https://doi.org/10.5194/amt-15-1755-2022, https://doi.org/10.5194/amt-15-1755-2022, 2022
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Spectral emissivity is a key property of the Earth's surface. Few measurements exist in the far-infrared, despite recent work showing that its contribution is important for accurate modelling of global climate. In preparation for ESA’s EE9 FORUM mission (launch in 2026), this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product to different physical and operational parameters.
Matthew A. Miller, Sandra E. Yuter, Nicole P. Hoban, Laura M. Tomkins, and Brian A. Colle
Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022, https://doi.org/10.5194/amt-15-1689-2022, 2022
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Apparent waves in the atmosphere and similar features in storm winds can be detected by taking the difference between successive Doppler weather radar scans measuring radar-relative storm air motions. Applying image filtering to the difference data better isolates the detected signal. This technique is a useful tool in weather research and forecasting since such waves can trigger or enhance precipitation.
Richard Müller and Uwe Pfeifroth
Atmos. Meas. Tech., 15, 1537–1561, https://doi.org/10.5194/amt-15-1537-2022, https://doi.org/10.5194/amt-15-1537-2022, 2022
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The great works of physics teach us that a central paradigm of science should be to make methods and theories as easy as possible and as complex as needed. This paper provides a brief review of remote sensing of solar surface irradiance based on this paradigm.
S. Joseph Munchak, Robert S. Schrom, Charles N. Helms, and Ali Tokay
Atmos. Meas. Tech., 15, 1439–1464, https://doi.org/10.5194/amt-15-1439-2022, https://doi.org/10.5194/amt-15-1439-2022, 2022
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The ability to measure snowfall with weather radar has greatly advanced with the development of techniques that utilize dual-polarization measurements, which provide information about the snow particle shape and orientation, and multi-frequency measurements, which provide information about size and density. This study combines these techniques with the NASA D3R radar, which provides dual-frequency polarimetric measurements, with data that were observed during the 2018 Winter Olympics.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 1303–1331, https://doi.org/10.5194/amt-15-1303-2022, https://doi.org/10.5194/amt-15-1303-2022, 2022
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The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
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A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Brian J. Carroll, Amin R. Nehrir, Susan A. Kooi, James E. Collins, Rory A. Barton-Grimley, Anthony Notari, David B. Harper, and Joseph Lee
Atmos. Meas. Tech., 15, 605–626, https://doi.org/10.5194/amt-15-605-2022, https://doi.org/10.5194/amt-15-605-2022, 2022
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HALO is a recently developed lidar system that demonstrates new technologies and advanced algorithms for profiling water vapor as well as aerosol and cloud properties. The high-resolution, high-accuracy measurements have unique advantages within the suite of atmospheric instrumentation, such as directly trading water vapor measurement resolution for precision. This paper provides the methodology and first water vapor results, showing agreement with in situ and spaceborne sounder measurements.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 15, 503–520, https://doi.org/10.5194/amt-15-503-2022, https://doi.org/10.5194/amt-15-503-2022, 2022
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In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity ZDR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with ZDR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.
Katarzyna Ośródka and Jan Szturc
Atmos. Meas. Tech., 15, 261–277, https://doi.org/10.5194/amt-15-261-2022, https://doi.org/10.5194/amt-15-261-2022, 2022
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Weather radar data are used in weather monitoring and forecasting, but they are affected by numerous errors and require advanced corrections. Different systems are designed and implemented to suit specific local conditions, like the RADVOL-QC system. The radar errors are divided into several groups: disturbance by non-meteorological echoes (from the mountains, RLAN signals, wind turbines, etc.), beam blockage, attenuation, etc. Each of them has different properties and is corrected differently.
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.
Cited articles
Andrieu, H. and Creutin, J. D.: Identification of Vertical Profiles of Radar
Reflectivity for Hydrological Applications Using an Inverse Method, Part I:
Formulation, J. Appl. Meteorol., 34, 225–239, https://doi.org/10.1175/1520-0450(1995)034<0225:IOVPOR>2.0.CO;2, 1995. a, b
Andrieu, H., Delrieu, G., and Creutin, J. D.: Identification of Vertical
Profiles of Radar Reflectivity For Hydrological Applications Using on Inverse
Method. Part 2: Sensitivity Analysis And Case-Study, J. Appl. Meteorol., 34, 240–259, 1995. a
Battan, L. J.: Radar observation of the atmosphere, University of Chicago
Press, Chicago, USA, https://doi.org/10.1002/qj.49709942229, 1973. a
Bell, C.: Detection of the Riming Process with a Vertically Pointing Radar,
PhD thesis, McGill University, Montreal, Quebec, Canada, 2000. a
Bellon, A., Lee, G., and Zawadzki, I.: Error statistics of VPR corrections in
stratiform precipitation, J. Appl. Meteorol., 44, 998–1015,
https://doi.org/10.1175/JAM2253.1, 2005. a
Berne, A., Delrieu, G., Andrieu, H., and Creutin, J. D.: Influence of the
Vertical Profile of Reflectivity on Radar-Estimated Rain Rates at Short Time
Steps, J. Hydrometeorol., 5, 296–310,
https://doi.org/10.1175/1525-7541(2004)005<0296:IOTVPO>2.0.CO;2, 2004. a, b
Boodoo, S., Hudak, D., Donaldson, N., and Leduc, M.: Application of
dual-polarization radar melting-layer detection algorithm, J. Appl.
Meteorol. Clim, 49, 1779–1793, https://doi.org/10.1175/2010JAMC2421.1, 2010. a
Bowler, N. E., Pierce, C. E., and Seed, A. W.: STEPS: A probabilistic
precipitation forecasting scheme which merges an extrapolation nowcast with
downscaled NWP, Q. J. Roy. Meteor. Soc., 132, 2127–2155,
https://doi.org/10.1256/qj.04.100, 2006. a
Brandes, E. A. and Ikeda, K.: Freezing-Level Estimation with Polarimetric
Radar, J. Appl. Meteorol., 43, 1541–1553, https://doi.org/10.1175/JAM2155.1, 2004. a, b
Campbell, L. S. and Steenburgh, W. J.: Finescale Orographic Precipitation
Variability and Gap-Filling Radar Potential in Little Cottonwood Canyon,
Utah, Weather Forecast, 29, 912–935, https://doi.org/10.1175/WAF-D-13-00129.1,
2014. a
Cluckie, I. D., Griffith, R. J., Lane, A., and Tilford, K. A.: Radar
hydrometeorology using a vertically pointing radar, Hydrol. Earth Syst. Sci.,
4, 565–580, https://doi.org/10.5194/hess-4-565-2000, 2000. a, b, c, d
Colle, B. A. and Zeng, Y.: Bulk microphysical sensitivities within the MM5 for
orographic precipitation. Part I: The Sierra 1986 event, Mon. Weather. Rev.,
132, 2780–2801, https://doi.org/10.1175/MWR2821.1, 2004a. a
Colle, B. A. and Zeng, Y.: Bulk Microphysical Sensitivities within the MM5 for
Orographic Precipitation. Part II: Impact of Barrier Width and Freezing
Level, Mon. Weather. Rev., 132, 2802–2815, https://doi.org/10.1175/MWR2822.1,
2004b. a
Colle, B. A., Garvert, M. F., Wolfe, J. B., Mass, C. F., and Woods, C. P.: The
13–14 December 2001 IMPROVE-2 Event. Part II: Comparisons of MM5 Model,
J. Atmos. Sci, 62, 3535–3558, https://doi.org/10.1175/JAS3551.1, 2005a. a
Colle, B. A., Wolfe, J. B., Steenburgh, W. J., Kingsmill, D. E., Cox, J. A. W.,
and Shafer, J. C.: High-Resolution Simulations and Microphysical Validation
of an Orographic Precipitation Event over the Wasatch Mountains during IPEX
IOP3, Mon. Weather. Rev., 133, 2947–2971, https://doi.org/10.1175/MWR3017.1,
2005b. a
Colle, B. A., Smith, R. B., and Wesley, D. A.: Theory, Observations, and
Predictions of Orographic Precipitation, in: Mountain Weather Research and
Forecasting: Recent Progress and Current Challenges, edited by: Chow, F. K.,
De Wekker, S. F., and Snyder, B. J., Springer Netherlands,
Dordrecht, the Netherlands, 291–344, https://doi.org/10.1007/978-94-007-4098-3_6, 2013. a
Crane, R. K.: A review of radar observations of turbulence in the lower
stratosphere, Radio Sci., 15, 177–193, https://doi.org/10.1029/RS015i002p00177, 1980. a
Das, S., Maitra, A., and Shukla, A. K.: Melting layer characteristics at
different climatic conditions in the Indian region: Ground based measurements
and satellite observations, Atmos. Res., 101, 78–83,
https://doi.org/10.1016/j.atmosres.2011.01.013, 2011. a, b
Davis, A., Marshak, A., Wiscombe, W., and Cahalan, R.: Scale Invariance of
Liquid Water Distributions in Marine Stratocumulus. Part I: Spectral
Properties and Stationarity Issues, J. Atmos. Sci, 53, 1538–1558,
https://doi.org/10.1175/1520-0469(1996)053<1538:SIOLWD>2.0.CO;2, 1996. a
De Montera, L., Barthès, L., Mallet, C., and Golé, P.: The
Effect of Rain–No Rain Intermittency on the Estimation of the Universal
Multifractals Model Parameters, J. Hydrometeorol., 10, 493–506,
https://doi.org/10.1175/2008JHM1040.1, 2009. a
Dixon, M. J., Hubbert, J. C., and Ellis, S.: A ZDR Calibration Check using
Hydrometeors in the Ice Phase, in: AMS 38th Conference on Radar Meteorology, 28 August–1 September 2017, Chicago, IL, USA, 1–15, 2017. a
Doviak, R. J. and Zrnić, D. S.: Doppler Radar and Weather Observations,
Dover Publications, Inc. Mineola, New York, USA, 33, https://doi.org/10.1016/B978-0-12-221422-6.50022-X, 1993. a
Fabry, F., Bellon, A., Duncan, M. R., and Austin, G. L.: High resolution
rainfall measurements by radar for very small basins: the sampling problem
reexamined, J. Hydrol., 161, 415–428, https://doi.org/10.1016/0022-1694(94)90138-4,
1994a. a
Figueras i Ventura, J., Schneebeli, M., Leuenberger, A., Gabella, M.,
Grazioli, J., Raupach, T. H., Wolfensberger, D., Graf, P., Wernli, H., Berne,
A., and Germann, U.: The PARADISO campaign: Description and first results,
in: AMS: 37th Conference on Radar Meteorology, 14–18 September 2015, Norman, OK, USA, p. 11B.3, https://ams.confex.com/ams/37RADAR/webprogram/Paper275852.html, 2015. a
Fraedrich, K. and Larnder, C.: Scaling regimes of composite rainfall time
series, Tellus A, 45, 289–298,
https://doi.org/10.1034/j.1600-0870.1993.t01-3-00004.x, 1993. a
Germann, U. and Joss, J.: Variograms of radar reflectivity to describe the
spatial continuity of Alpine precipitation, J. Appl. Meteorol, 40,
1042–1059, https://doi.org/10.1175/1520-0450(2001)040<1042:VORRTD>2.0.CO;2, 2001. a, b
Germann, U. and Joss, J.: Operational Measurement of Precipitation in
Mountainous Terrain, Springer Berlin Heidelberg, Germany, chap. 2,
52–77, https://doi.org/10.1007/978-3-662-05202-0_2, 2004. a, b
Germann, U., Galli, G., Boscacci, M., and Bolliger, M.: Radar precipitation
measurement in a mountainous region, Q. J. Roy. Meteor. Soc., 132,
1669–1692, https://doi.org/10.1256/qj.05.190, 2006. a
Germann, U., Boscacci, M., Gabella, M., and Sartori, M.: Peak Performance;
radar design for prediction in the Swiss Alps, Meteorological Technology
International, 42–45, 2015. a
Gray, W. R., Uddstrom, M. J., and Larsen, H. R.: Radar surface rainfall
estimates using a typical shape function approach to correct for the
variations in the vertical profile of reflectivity, Int. J. Remote. Sens,
23, 2489–2504, https://doi.org/10.1080/01431160110070834, 2002. a, b
Harris, D., Seed, A., Menabde, M., and Austin, G.: Factors affecting
multiscaling analysis of rainfall time series, Nonlin. Processes Geophys., 4,
137–156, https://doi.org/10.5194/npg-4-137-1997, 1997. a
Harris, D., Foufoula-Georgiou, E., Droegemeier, K. K., and Levit, J. J.:
Multiscale Statistical Properties of a High-Resolution Precipitation
Forecast, J. Hydrometeorol., 2, 406–418,
https://doi.org/10.1175/1525-7541(2001)002<0406:MSPOAH>2.0.CO;2, 2001. a
Harris, G. N., Bowman, K. P., and Shin, D. B.: Comparison of freezing-level
altitudes from the NCEP reanalysis with TRMM precipitation radar brightband
data, J. Climate, 13, 4137–4148,
https://doi.org/10.1175/1520-0442(2000)013<4137:COFLAF>2.0.CO;2, 2000. a
Helmus, J. J. and Collis, S. M., The Python ARM Radar Toolkit (Py-ART), a
Library for Working with Weather Radar Data in the Python Programming
Language, Journal of Open Research Software, 4, e25, https://doi.org/10.5334/jors.119, 2016. a, b
Houze, R. A.: Orographic effects on precipitating clouds, Rev. Geophys., 50,
1–47, https://doi.org/10.1029/2011RG000365, 2012. a
Houze, R. A. and Medina, S.: Turbulence as a Mechanism for Orographic
Precipitation Enhancement, J. Atmos. Sci, 62, 3599–3623,
https://doi.org/10.1175/JAS3555.1, 2005. a
Jarvis, A., Reuter, H., Nelson, A., and Guevara, E.: Hole-filled seamless SRTM
data V4. Tech. rep., International Centre for Tropical Agriculture (CIAT),
available at: http://srtm.csi.cgiar.org (last access: 8 May 2015), 2008. a
Jordan, P., Seed, A., and Austin, G.: Sampling errors in radar estimates of
rainfall, J. Geophys. Res., 105, 2247–2257, https://doi.org/10.1029/1999jd900130, 2000. a
Joss, J. and Lee, R.: The Application of Radar-Gauge Comparisons to
Operational Precipitation Profile Corrections, J. Appl. Meteorol., 34,
2612–2630, https://doi.org/10.1175/1520-0450(1995)034<2612:TAORCT>2.0.CO;2, 1995. a, b, c
Joss, J. and Pittini, A.: Real-time estimation of the vertical profile of
radar reflectivity to improve the measurement of precipitation in an Alpine
region, Meteorol. Atmos. Phys, 47, 61–72, https://doi.org/10.1007/BF01025828, 1991. a, b
Kirstetter, P. E., Andrieu, H., Boudevillain, B., and Delrieu, G.: A
Physically based identification of vertical profiles of reflectivity from
volume scan radar data, J. Appl. Meteorol. Clim, 52, 1645–1663,
https://doi.org/10.1175/JAMC-D-12-0228.1, 2013. a, b
Koistinen, J.: Operational correction of radar rainfall errors due to the
radar reflectivity profile, in: Proceedings of the 25th International
Conference on Radar Meteorology, 24–28 June 1991, AMS, 91–94, 1991. a
Koistinen, J., Michelson, D. B., Hohti, H., and Peura, M.: Operational
Measurement of Precipitation in Cold Climates,
Springer Berlin Heidelberg, Germany, chap. 3, 78–110, 2004. a
Lumb, F.: Sharp snow-rain contrasts-an explanation, Weather, 38, 71–73,
1983. a
Mandapaka, P. V., Lewandowski, P., Eichinger, W. E., and Krajewski, W. F.:
Multiscaling analysis of high resolution space-time lidar-rainfall, Nonlin.
Processes Geophys., 16, 579–586, https://doi.org/10.5194/npg-16-579-2009,
2009. a
Marigo, G., Robert-Luciani, T., and Crepaz, A.: Snow level forecasting methods
and parameters: two practical examples on eastern Italian Alps, in: 13th
Mtn. Meteor. Conf., 11–15 August 2008, Whistler, Canada, 2008. a
Marwitz, J.: The kinematics of orographic flow during Sierra storms, J.
Atmos. Sci, 40, 1218–1227, 1983. a
Matrosov, S. Y., Clark, K. A., and Kingsmill, D. E.: A polarimetric radar
approach to identify rain, melting-layer, and snow regions for applying
corrections to vertical profiles of reflectivity, J. Appl. Meteorol. Clim.,
46, 154–166, https://doi.org/10.1175/JAM2508.1, 2007. a
Matsuo, T. and Sasyo, Y.: Melting of Snowflakes below Freezing Level in the
Atmosphere, J. Meteorol. Soc. Jpn., 59, 10–25,
https://doi.org/10.2151/jmsj1965.59.1_10, 1981. a, b
Medina, S., Smull, B. F., Houze, R. A., and Steiner, M.: Cross-Barrier Flow
during Orographic Precipitation Events: Results from MAP and IMPROVE, J.
Atmos. Sci, 62, 3580–3598, https://doi.org/10.1175/JAS3554.1, 2005. a
Mittermaier, M. P. and Illingworth, A. J.: Comparison of model-derived and
radar-observed freezing-level heights: Implications for vertical reflectivity
profile-correction schemes, Q. J. Roy. Meteor. Soc., 129, 83–95,
https://doi.org/10.1256/qj.02.19, 2003. a
Mohymont, B. and Delobbe, L.: Is the variogram a good tool for assessing the
spatial variability of vertical profiles of reflectivity?, in: ERAD, 30 June–4 July 2008, 2008. a
Montopoli, M., Roberto, N., Adirosi, E., Gorgucci, E., and Baldini, L.:
Investigation of weather radar quantitative precipitation estimation
methodologies in complex orography, Atmosphere, 8, https://doi.org/10.3390/atmos8020034, 2017. a
Nerini, D., Besic, N., Sideris, I., Germann, U., and Foresti, L.: A
non-stationary stochastic ensemble generator for radar rainfall fields based
on the short-space Fourier transform, Hydrol. Earth Syst. Sci., 21,
2777–2797, https://doi.org/10.5194/hess-21-2777-2017, 2017. a
Nykanen, D. K.: Linkages between Orographic Forcing and the Scaling Properties
of Convective Rainfall in Mountainous Regions, J. Hydrometeorol., 9,
327–347, https://doi.org/10.1175/2007JHM839.1, 2008. a
Nykanen, D. K. and Harris, D.: Orographic influences on the multiscale
statistical properties of precipitation, J. Geophys. Res.,
108, 8381, https://doi.org/10.1029/2001JD001518, 2003. a
Purdy, J. C., Harris, D., Austin, G. L., Seed, A. W., and Gray, W.: A case
study of orographic rainfall processes incorporating multiscaling
characterization techniques, J. Geophys. Res.-Atmos., 106, 7837–7845,
https://doi.org/10.1029/2000JD900622, 2001. a, b
Roe, G. H.: Orographic Precipitation, Annu. Rev. Earth. Pl. Sc., 33, 645–671,
https://doi.org/10.1146/annurev.earth.33.092203.122541, 2005. a, b
Rudolph, J. V. and Friedrich, K.: Seasonality of vertical structure in
radar-observed precipitation over southern Switzerland, J. Hydrometeorol.,
14, 318–330, https://doi.org/10.1175/jhm-d-12-042.1, 2013. a, b
Rudolph, J. V. and Friedrich, K.: Dynamic and thermodynamic predictors of
vertical structure in radar-observed regional precipitation, J. Climate, 27,
2143–2158, https://doi.org/10.1175/JCLI-D-13-00239.1, 2014. a
Rysman, J. F., Verrier, S., Lemaître, Y., and Moreau, E.: Space-time
variability of the rainfall over the western Mediterranean region: A
statistical analysis, J. Geophys. Res.-Atmos, 118, 8448–8459,
https://doi.org/10.1002/jgrd.50656, 2013. a, b, c, d
Schneebeli, M., Dawes, N., Lehning, M., and Berne, A.: High-resolution
vertical profiles of X-band polarimetric radar observables during snowfall in
the Swiss Alps, J. Appl. Meteorol. Clim., 52, 378–394,
https://doi.org/10.1175/JAMC-D-12-015.1, 2013. a
Smith, B.: Accuracy and resolution of shuttle radar topography mission data,
Geophys. Res. Lett, 30, 1467, https://doi.org/10.1029/2002GL016643, 2003. a
Stoelinga, M. T., Stewart, R. E., Thompson, G., and Thériault, J. M.:
Microphysical Processes Within Winter Orographic Cloud and Precipitation
Systems, in: Mountain Weather Research and Forecasting: Recent Progress and
Current Challenges, edited by Chow, F. K., De Wekker, S. F., and Snyder,
B. J., Springer Netherlands, Dordrecht, the Netherlands, 345–408,
https://doi.org/10.1007/978-94-007-4098-3_7, 2013. a, b, c, d, e
Stull, R. B.: An Introduction to Boundary Layer Meteorology, Springer,
Dordrecht, the Netherlands, https://doi.org/10.1007/978-94-009-3027-8, 1988. a, b
Testud, J., Bouar, E. L., Obligis, E., and Ali-Mehenni, M.: The rain profiling
algorithm applied to polarimetric weather radar, J. Atmos.
Ocean. Tech., 17, 332–356, https://doi.org/10.1175/1520-0426(2000)017<0332:TRPAAT>2.0.CO;2,
2000. a
Thurai, M., Deguchi, E., Iguchi, T., and Okamoto, K.: Freezing height
distribution in the tropics, Int. J. Satell. Co. Netw, 21, 533–545,
https://doi.org/10.1002/sat.768, 2003. a
Van der Hoven, I.: Power spectrum of horizontal wind speed in the frequency
range from 0.0007 to 900 cycles per hour, J. Meteorol., 14, 160–164,
https://doi.org/10.1175/1520-0469(1957)014<0160:PSOHWS>2.0.CO;2, 1957. a
Verrier, S., Mallet, C., and Barthès, L.: Multiscaling properties of
rain in the time domain, taking into account rain support biases, J.
Geophys. Res.-Atmos., 116, D20119, https://doi.org/10.1029/2011JD015719, 2011. a
Vignal, B. and Krajewski, W. F.: Large-Sample Evaluation of Two Methods to
Correct Range-Dependent Error for WSR-88D Rainfall Estimates, J.
Hydrometeorol., 2, 490–504,
https://doi.org/10.1175/1525-7541(2001)002<0490:LSEOTM>2.0.CO;2, 2001. a
Vignal, B., Andrieu, H., and Creutin, J. D.: Identification of Vertical
Profiles of Reflectivity from Volume Scan Radar Data, J. Appl. Meteorol., 38,
1214–1228, https://doi.org/10.1175/1520-0450(1999)038<1214:IOVPOR>2.0.CO;2, 1999. a, b
Vignal, B., Galli, G., Joss, J., and Germann, U.: Three methods to determine
profiles of reflectivity from volumetric radar data to correct precipitation
estimates, J. Appl. Meteorol, 39, 1715–1726,
https://doi.org/10.1175/1520-0450-39.10.1715, 2000. a
Vulpiani, G., Montopoli, M., Della Passeri, L., Gioia, A., Giordano, P., and
Marzano, F. S.: On the Use of Dual-Polarized C-Band Radar for Operational
Rainfall Retrieval in Mountainous Areas, J. Appl. Meteor. Climatol, 51,
https://doi.org/10.1175/JAMC-D-10-05024.1, 2012. a
Zhang, J. and Qi, Y.: A Real-Time Algorithm for the Correction of Brightband
Effects in Radar-Derived QPE, J. Hydrometeorol., 11, 1157–1171,
https://doi.org/10.1175/2010JHM1201.1, 2010. a, b
Zrnic, D. S., Balakrishnan, N., Ziegler, C. L., Bringi, V. N., Aydin, K., and
Matejka, T.: Polarimetric Signatures in the Stratiform Region of a Mesoscale
Convective System, J. Appl. Meteorol., 32, 678–693,
https://doi.org/10.1175/1520-0450(1993)032<0678:PSITSR>2.0.CO;2, 1993. a
Short summary
The paper aims at characterising and quantifying the spatio-temporal variability of the melting layer (ML; transition zone from solid to liquid precipitation). A method based on the Fourier transform is found to accurately describe different ML signatures. Hence, it is applied to characterise the ML variability in a relatively flat area and in an inner Alpine valley in Switzerland, where the variability at smaller spatial scales is found to be relatively more important.
The paper aims at characterising and quantifying the spatio-temporal variability of the melting...