Articles | Volume 13, issue 2
https://doi.org/10.5194/essd-13-417-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-417-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Feb 2021
Data description paper |
| 15 Feb 2021
| 15 Feb 2021
Radar and ground-level measurements of precipitation collected by the École Polytechnique Fédérale de Lausanne during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games
Josué Gehring
Environmental Remote Sensing Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Alfonso Ferrone
Environmental Remote Sensing Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Anne-Claire Billault-Roux
Environmental Remote Sensing Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Nikola Besic
Centre Météorologie Radar, Météo-France, Toulouse, France
Kwang Deuk Ahn
Numerical Data Application Division, Numerical Modeling Center, Korea Meteorological Administration, Seoul, South Korea
GyuWon Lee
Department of Astronomy and Atmospheric Sciences, Kyungpook National University, Daegu, South Korea
Environmental Remote Sensing Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
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Monika Feldmann, Urs Germann, Marco Gabella, and Alexis Berne
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Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Paul Joe, Gyuwon Lee, and Kwonil Kim
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-620, https://doi.org/10.5194/acp-2021-620, 2021
Preprint withdrawn
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Strong gusty wind events were responsible for poor performance of competitors and schedule changes during the PyeongChang 2018 Olympic and Paralympic Winter Games. Three events were investigated and documented to articulate the challenges confronting forecasters which is beyond what they normally do. Quantitative evidence of the challenge and recommendations for future Olympics are provided.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240, https://doi.org/10.5194/essd-13-4219-2021, https://doi.org/10.5194/essd-13-4219-2021, 2021
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This study analyzes the microphysical characteristics of snow in complex terrain and the nearby ocean according to topography and wind pattern during the ICE-POP 2018 campaign. The observations from collocated vertically pointing radars and disdrometers indicate that the riming in the mountainous region is likely caused by a strong shear and turbulence. The different behaviors of aggregation and riming were found by three different synoptic patterns (air–sea interaction, cold low, and warm low).
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
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Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Noémie Planat, Josué Gehring, Étienne Vignon, and Alexis Berne
Atmos. Meas. Tech., 14, 4543–4564, https://doi.org/10.5194/amt-14-4543-2021, https://doi.org/10.5194/amt-14-4543-2021, 2021
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We implement a new method to identify microphysical processes during cold precipitation events based on the sign of the vertical gradient of polarimetric radar variables. We analytically asses the meteorological conditions for this vertical analysis to hold, apply it on two study cases and successfully compare it with other methods informing about the microphysics. Finally, we are able to obtain the main vertical structure and characteristics of the different processes during these study cases.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
Iris Thurnherr, Katharina Hartmuth, Lukas Jansing, Josué Gehring, Maxi Boettcher, Irina Gorodetskaya, Martin Werner, Heini Wernli, and Franziska Aemisegger
Weather Clim. Dynam., 2, 331–357, https://doi.org/10.5194/wcd-2-331-2021, https://doi.org/10.5194/wcd-2-331-2021, 2021
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Extratropical cyclones are important for the transport of moisture from low to high latitudes. In this study, we investigate how the isotopic composition of water vapour is affected by horizontal temperature advection associated with extratropical cyclones using measurements and modelling. It is shown that air–sea moisture fluxes induced by this horizontal temperature advection lead to the strong variability observed in the isotopic composition of water vapour in the marine boundary layer.
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, https://doi.org/10.5194/amt-14-2749-2021, 2021
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In the context of climate studies, understanding the role of clouds on a global and local scale is of paramount importance. One aspect is the quantification of cloud liquid water, which impacts the Earth’s radiative balance. This is routinely achieved with radiometers operating at different frequencies. In this study, we propose an approach that uses a single-frequency radiometer and that can be applied at any location to retrieve vertically integrated quantities of liquid water and water vapor.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, Jung-Hoon Kim, YongHee Lee, and GyuWon Lee
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-100, https://doi.org/10.5194/acp-2021-100, 2021
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This study examines a strong downslope wind event during ICE-POP 2018 using Doppler lidars, and observations. 3D winds can be well retrieved by
WISSDOM. This is first time to document the mechanisms of strong wind in observational aspect under fine weather. The PGF causing by adiabatic warming and channeling effect are key factors to dominate the strong wind. The values of this study are improving our understanding of the strong wind and increase the predictability of the weather forecast.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
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Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
Hwayoung Jeoung, Guosheng Liu, Kwonil Kim, Gyuwon Lee, and Eun-Kyoung Seo
Atmos. Chem. Phys., 20, 14491–14507, https://doi.org/10.5194/acp-20-14491-2020, https://doi.org/10.5194/acp-20-14491-2020, 2020
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Radar and radiometer observations were used to study cloud liquid and snowfall in three types of snow clouds. While near-surface and shallow clouds have an area fraction of 90 %, deep clouds contribute half of the total snowfall volume. Deeper clouds have heavier snowfall, although cloud liquid is equally abundant in all three cloud types. The skills of a GMI Bayesian algorithm are examined. Snowfall in deep clouds may be reasonably retrieved, but it is challenging for near-surface clouds.
Cited articles
Berg, H. W., Stewart, R. E., and Joe, P. I.: The Characteristics of
Precipitation Observed over Cypress Mountain during the SNOW-V10
Campaign, Atmos. Res., 197, 356–369,
https://doi.org/10.1016/j.atmosres.2017.06.009, 2017. a
Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016. a, b
Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmos. Meas. Tech., 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, 2018. a
Billault-Roux, A.-C. and Berne, A.: Integrated water vapor and liquid water path retrieval using a single-channel radiometer, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2020-311, in review, 2020. a, b
Boudala, F. S., Rasmussen, R., Isaac, G. A., and Scott, B.: Performance of Hot
Plate for Measuring Solid Precipitation in Complex Terrain during the 2010
Vancouver Winter Olympics, J. Atmos. Ocean. Technol.,
31, 437–446, https://doi.org/10.1175/JTECH-D-12-00247.1, 2014. a
Bougeault, P., Binder, P., Buzzi, A., Dirks, R., Houze, R., Kuettner, J.,
Smith, R. B., Steinacker, R., and Volkert, H.: The MAP Special Observing
Period, B. Am. Meteorol. Soc., 82, 433–462,
https://doi.org/10.1175/1520-0477(2001)082<0433:TMSOP>2.3.CO;2, 2001. a
Brandes, E. A., Ikeda, K., Zhang, G., Schönhuber, M., and Rasmussen, R. M.:
A Statistical and Physical Description of Hydrometeor Distributions in
Colorado Snowstorms Using a Video Disdrometer, J. Appl.
Meteorol. Clim., 46, 634–650, https://doi.org/10.1175/JAM2489.1, 2007. a
Cole, S., Neely III., R. R., and Stillwell, R. A.: First Look at the Occurrence of Horizontally Oriented Ice Crystals over Summit, Greenland, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2016-1134, 2017. a
Doviak, R. J. and Zrnic, D. S.: Doppler Radar and Weather Observations,
Dover Publications, Mineola, NY, USA, 1993. a
Garrett, T. J., Fallgatter, C., Shkurko, K., and Howlett, D.: Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall, Atmos. Meas. Tech., 5, 2625–2633, https://doi.org/10.5194/amt-5-2625-2012, 2012. a
Gehring, J., Ferrone, A., Billault-Roux, A.-C., Besic, N., and Berne, A.:
Radar and Ground-Level Measurements of Precipitation during the
ICE-POP 2018 Campaign in South-Korea, PANGAEA,
https://doi.org/10.1594/PANGAEA.918315, 2020a. a, b, c
Genthon, C., Berne, A., Grazioli, J., Durán Alarcón, C., Praz, C., and Boudevillain, B.: Precipitation at Dumont d'Urville, Adélie Land, East Antarctica: the APRES3 field campaigns dataset, Earth Syst. Sci. Data, 10, 1605–1612, https://doi.org/10.5194/essd-10-1605-2018, 2018. a
Gorgucci, E., Scarchilli, G., and Chandrasekar, V.: A Procedure to Calibrate
Multi-Parameter Weather Radar Using Properties of the Rain Medium, Geosci.
Remote Sens., 17, 269–276, 1999. a
Grazioli, J., Tuia, D., Monhart, S., Schneebeli, M., Raupach, T., and Berne, A.: Hydrometeor classification from two-dimensional video disdrometer data, Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, 2014. a
Grazioli, J., Tuia, D., and Berne, A.: Hydrometeor classification from polarimetric radar measurements: a clustering approach, Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, 2015. a
Grazioli, J., Genthon, C., Boudevillain, B., Duran-Alarcon, C., Del Guasta, M., Madeleine, J.-B., and Berne, A.: Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica, The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, 2017a. a
Grazioli, J., Madeleine, J.-B., Gallée, H., Forbes, R. M., Genthon, C.,
Krinner, G., and Berne, A.: Katabatic Winds Diminish Precipitation
Contribution to the Antarctic Ice Mass Balance, P.
Natl. Acad. Sci., 114, 10858–10863,
https://doi.org/10.1073/pnas.1707633114, 2017b. a
Haiden, T., Kann, A., and Pistotnik, G.: Nowcasting with INCA During
SNOW-V10, Pure Appl. Geophys., 171, 231–242,
https://doi.org/10.1007/s00024-012-0547-8, 2014. a
Hicks, A. and Notaroš, B. M.: Method for Classification of
Snowflakes Based on Images by a Multi-Angle Snowflake Camera
Using Convolutional Neural Networks, J. Atmos. Ocean.
Technol., 36, 2267–2282, https://doi.org/10.1175/jtech-d-19-0055.1, 2019. a
Hildebrand, P. H. and Sekhon, R. S.: Objective Determination of the Noise
Level in Doppler Spectra, J. Appl. Meteorol., 13, 808–811,
https://doi.org/10.1175/1520-0450(1974)013<0808:odotnl>2.0.co;2, 1974. a, b
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
Houze, R. A., McMurdie, L. A., Petersen, W. A., Schwaller, M. R., Baccus, W.,
Lundquist, J. D., Mass, C. F., Nijssen, B., Rutledge, S. A., Hudak, D. R.,
Tanelli, S., Mace, G. G., Poellot, M. R., Lettenmaier, D. P., Zagrodnik,
J. P., Rowe, A. K., DeHart, J. C., Madaus, L. E., Barnes, H. C., and
Chandrasekar, V.: The Olympic Mountains Experiment (OLYMPEX),
B. Am. Meteorol. Soc., 98, 2167–2188,
https://doi.org/10.1175/bams-d-16-0182.1, 2017. a, b
Huang, G. J., Bringi, V. N., Cifelli, R., Hudak, D., and Petersen, W. A.: A
Methodology to Derive Radar Reflectivity-Liquid Equivalent Snow Rate
Relations Using C-Band Radar and a 2D Video Disdrometer, J.
Atmos. Ocean. Technol., 27, 637–651,
https://doi.org/10.1175/2009JTECHA1284.1, 2010. a
Huang, G. J., Bringi, V. N., Moisseev, D., Petersen, W. A., Bliven, L., and
Hudak, D.: Use of 2D-Video Disdrometer to Derive Mean Density-Size and
Ze-SR Relations: Four Snow Cases from the Light Precipitation
Validation Experiment, Atmos. Res., 153, 34–48,
https://doi.org/10.1016/j.atmosres.2014.07.013, 2015. a
Joe, P., Doyle, C., Wallace, A. L., Cober, S. G., Scott, B., Isaac, G. A.,
Smith, T., Mailhot, J., Snyder, B., Belair, S., Jansen, Q., and Denis, B.:
Weather Services, Science Advances, and the Vancouver 2010 Olympic and
Paralympic Winter Games, B. Am. Meteorol. Soc., 91,
31–36, https://doi.org/10.1175/2009BAMS2998.1, 2010. a
Kalesse, H., Szyrmer, W., Kneifel, S., Kollias, P., and Luke, E.: Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling, Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, 2016. a
Kim, Y. J., Kim, B. G., Shim, J. K., and Choi, B. C.: Observation and
Numerical Simulation of Cold Clouds and Snow Particles in the
Yeongdong Region, Asia-Pac. J. Atmos. Sci., 54,
499–510, https://doi.org/10.1007/s13143-018-0055-6, 2018. a
KMA: Climatological Normals of Korea, Technical Report, Korea Meteorological
Administration, Seoul, Republic of Korea, 678 pp., 2011. a
Kruger, A. and Krajewski, W. F.: Two-Dimensional Video Disdrometer: A
Description, J. Atmos. Ocean. Technol., 19, 602–617,
https://doi.org/10.1175/1520-0426(2002)019<0602:TDVDAD>2.0.CO;2, 2002. a
Küchler, N., Kneifel, S., Löhnert, U., Kollias, P., Czekala, H., and
Rose, T.: A W-Band Radar–Radiometer System for
Accurate and Continuous Monitoring of Clouds and
Precipitation, J. Atmos. Ocean. Technol., 34,
2375–2392, https://doi.org/10.1175/JTECH-D-17-0019.1, 2017. a
Löhnert, U., Kneifel, S., Battaglia, A., Hagen, M., Hirsch, L., and
Crewell, S.: A Multisensor Approach Toward a Better Understanding of
Snowfall Microphysics: The TOSCA Project, B. Am.
Meteorol. Soc., 92, 613–628, https://doi.org/10.1175/2010BAMS2909.1, 2011. a
Lubin, D., Zhang, D., Silber, I., Scott, R. C., Kalogeras, P., Battaglia, A.,
Bromwich, D. H., Cadeddu, M., Eloranta, E., Fridlind, A., Frossard, A.,
Hines, K. M., Kneifel, S., Leaitch, W. R., Lin, W., Nicolas, J., Powers, H.,
Quinn, P. K., Rowe, P., Russell, L. M., Sharma, S., Verlinde, J., and
Vogelmann, A. M.: AWARE: The Atmospheric Radiation Measurement
(ARM) West Antarctic Radiation Experiment, B. Am.
Meteorol. Soc., 101, 1069–1091, https://doi.org/10.1175/BAMS-D-18-0278.1,
2020. a
Mech, M., Maahn, M., Kneifel, S., Ori, D., Orlandi, E., Kollias, P., Schemann, V., and Crewell, S.: PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, 2020. a
Myagkov, A., Kneifel, S., and Rose, T.: Evaluation of the reflectivity calibration of W-band radars based on observations in rain, Atmos. Meas. Tech., 13, 5799–5825, https://doi.org/10.5194/amt-13-5799-2020, 2020. a
Nešpor, V., Krajewski, W. F., and Kruger, A.: Wind-Induced Error of
Raindrop Size Distribution Measurement Using a Two-Dimensional Video
Disdrometer, J. Atmos. Ocean. Technol., 17, 1483–1492,
https://doi.org/10.1175/1520-0426(2000)017<1483:WIEORS>2.0.CO;2, 2000. a
Panziera, L., James, C. N., and Germann, U.: Mesoscale Organization and
Structure of Orographic Precipitation Producing Flash Floods in the Lago
Maggiore Region, Q. J. Roy. Meteor. Soc., 141,
224–248, https://doi.org/10.1002/qj.2351, 2015. a
Petäjä, T., O'Connor, E. J., Moisseev, D., Sinclair, V. A., Manninen,
A. J., Väänänen, R., von Lerber, A., Thornton, J. A., Nicoll,
K., Petersen, W., Chandrasekar, V., Smith, J. N., Winkler, P. M., Krüger,
O., Hakola, H., Timonen, H., Brus, D., Laurila, T., Asmi, E., Riekkola,
M.-L., Mona, L., Massoli, P., Engelmann, R., Komppula, M., Wang, J., Kuang,
C., Bäck, J., Virtanen, A., Levula, J., Ritsche, M., and Hickmon, N.:
BAECC: A Field Campaign to Elucidate the Impact of Biogenic
Aerosols on Clouds and Climate, B. Am.
Meteorol. Soc., 97, 1909–1928, https://doi.org/10.1175/BAMS-D-14-00199.1,
2016. a
Ray, P. S. and Ziegler, C.: De-Aliasing First-Moment Doppler Estimates,
J. Appl. Meteorol., 16, 563–564,
https://doi.org/10.1175/1520-0450(1977)016<0563:DAFMDE>2.0.CO;2, 1977. a
Saleeby, S. M., Cotton, W. R., Lowenthal, D., Borys, R. D., and Wetzel, M. A.:
Influence of Cloud Condensation Nuclei on Orographic Snowfall, J.
Appl. Meteorol. Clim., 48, 903–922,
https://doi.org/10.1175/2008JAMC1989.1, 2009. a
Schaer, M., Praz, C., and Berne, A.: Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera, The Cryosphere, 14, 367–384, https://doi.org/10.5194/tc-14-367-2020, 2020.
a, b
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
Schneebeli, M., Grazioli, J., and Berne, A.: Improved Estimation of the
Specific Differential Phase Shift Using a Compilation of Kalman Filter
Ensembles, IEEE T. Geosci. Remote, 52,
5137–5149, https://doi.org/10.1109/TGRS.2013.2287017, 2014. a
Schönhuber, M., Lammer, G., and Randeu, W. L.: One decade of imaging precipitation measurement by 2D-video-distrometer, Adv. Geosci., 10, 85–90, https://doi.org/10.5194/adgeo-10-85-2007, 2007. a
Schuur, T. J., Ryzhkov, A. V., Forsyth, D. E., Zhang, P., and Reeves, H. D.:
Precipitation Observations with NSSL's X-Band Polarimetric
Radar during the SNOW-V10 Campaign, Pure Appl. Geophys.,
171, 95–112, https://doi.org/10.1007/s00024-012-0569-2, 2014. a
Shupe, M. D., Turner, D. D., Walden, V. P., Bennartz, R., Cadeddu, M. P.,
Castellani, B. B., Cox, C. J., Hudak, D. R., Kulie, M. S., Miller, N. B.,
Neely, R. R., Neff, W. D., and Rowe, P. M.: High and Dry: New
Observations of Tropospheric and Cloud Properties above the
Greenland Ice Sheet, B. Am. Meteorol. Soc., 94,
169–186, https://doi.org/10.1175/BAMS-D-11-00249.1, 2013. a
Stoelinga, M., Hobbs, P. V., and Mass, C. F.: Improvement of Microphysical
Observational Verification Parameterization through Experiment, B. Am.
Meterol. Soc., 84, 1807–1826, https://doi.org/10.1175/BAMS-84-12-1807, 2003. a
Thériault, J. M., Rasmussen, R., Smith, T., Mo, R., Milbrandt, J. A.,
Brugman, M. M., Joe, P., Isaac, G. A., Mailhot, J., and Denis, B.: A Case
Study of Processes Impacting Precipitation Phase and Intensity
during the Vancouver 2010 Winter Olympics, Weather Forecast.,
27, 1301–1325, https://doi.org/10.1175/WAF-D-11-00114.1, 2012. a
Verlinde, J., Zak, B. D., Shupe, M. D., Ivey, M. D., and Stamnes, K.: The ARM
North Slope of Alaska (NSA) Sites, Meteorological Monographs,
57, 1–13, https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0023.1, 2016. a
von Lerber, A., Moisseev, D., Bliven, L. F., Petersen, W., Harri, A. M., and
Chandrasekar, V.: Microphysical Properties of Snow and Their Link to
Ze-S Relations during BAECC 2014, J. Appl. Meteorol. Clim., 56, 1561–1582, https://doi.org/10.1175/JAMC-D-16-0379.1, 2017. a
Zagrodnik, J. P., Mcmurdie, L. A., Houze, R. A., and Tanelli, S.: Vertical
Structure and Microphysical Characteristics of Frontal Systems Passing over a
Three-Dimensional Coastal Mountain Range, J. Atmos.
Sci., 76, 1521–1546, https://doi.org/10.1175/JAS-D-18-0279.1, 2019. a
Short summary
This article describes a dataset of precipitation and cloud measurements collected from November 2017 to March 2018 in Pyeongchang, South Korea. The dataset includes weather radar data and images of snowflakes. It allows for studying the snowfall intensity; wind conditions; and shape, size and fall speed of snowflakes. Classifications of the types of snowflakes show that aggregates of ice crystals were dominant. This dataset represents a unique opportunity to study snowfall in this region.
This article describes a dataset of precipitation and cloud measurements collected from November...
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