uni-leipzig-open-access/json/amt-16-1683-2023

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T04:35:46Z","timestamp":1680150946399},"reference-count":39,"publisher":"Copernicus GmbH","issue":"6","license":[{"start":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T00:00:00Z","timestamp":1680048000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["FO 1285\/2-1"]},{"DOI":"10.13039\/501100004895","name":"European Social Fund","doi-asserted-by":"publisher","award":["100339509","100602743"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Atmos. Meas. Tech."],"abstract":"<jats:p>Abstract. Continuous long-term ground-based remote-sensing observations combined with vertically pointing cloud radar and ceilometer measurements are well suited for identifying precipitation evaporation fall streaks (so-called virga). Here we introduce the functionality and workflow of a new open-source tool, the Virga-Sniffer, which was developed within the framework of RV\u00a0Meteor observations during the ElUcidating the RolE of Cloud\u2013Circulation Coupling in ClimAte (EUREC4A) field experiment in January\u2013February 2020 in the tropical western Atlantic. The Virga-Sniffer Python package is highly modular and configurable and can be applied to multilayer cloud situations. In the simplest approach, it detects virga from time\u2013height fields of cloud radar reflectivity and time series of ceilometer cloud base height. In addition, optional parameters like lifting condensation level, a surface rain flag, and time\u2013height fields of cloud radar mean Doppler velocity can be added to refine virga event identifications. The netCDF-output files consist of Boolean flags of virga and cloud detection, as well as base and top heights and depth for the detected clouds and virga. The sensitivity of the Virga-Sniffer results to different settings is explored (in the Appendix).\nThe performance of the Virga-Sniffer was assessed by comparing its results to the CloudNet target classification resulting from using the CloudNet processing chain. A total of 86\u2009% of pixels identified as virga correspond to CloudNet target classifications of precipitation. The remaining 14\u2009% of virga pixels correspond to CloudNet target classifications of aerosols and insects (about 10\u2009%), cloud droplets (about 2\u2009%), or clear sky (2\u2009%). Some discrepancies of the virga identification and the CloudNet target classification can be attributed to temporal smoothing that was applied. Additionally, it was found that CloudNet mostly classified aerosols and insects at virga edges, which points to a misclassification caused by CloudNet internal thresholds.\nFor the RV\u00a0Meteor observations in the downstream winter trades during EUREC4A, about 42\u2009% of all detected clouds with bases below the trade inversion were found to produce precipitation that fully evaporates before reaching the ground.\nA proportion of 56\u2009% of the detected virga originated from trade wind cumuli. Virga with depths less than 0.2\u2009km most frequently occurred from shallow clouds with depths less than 0.5\u2009km, while virga depths larger than 1\u2009km were mainly associated with clouds of larger depths, ranging between 0.5 and 1\u2009km. The presented results substantiate the importance of complete low-level precipitation evaporation in the downstream winter trades. Possible applications of the Virga-Sniffer within the framework of EUREC4A include detailed studies of precipitation evaporation with a focus on cold pools or cloud organization or distinguishing moist processes based on water vapor isotopic observations. However, we envision extended use of the Virga-Sniffer for other cloud regimes or scientific foci as well.\n                    <\/jats:p>","DOI":"10.5194\/amt-16-1683-2023","type":"journal-article","created":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T11:35:37Z","timestamp":1680089737000},"page":"1683-1704","source":"Crossref","is-referenced-by-count":0,"title":["The Virga-Sniffer \u2013 a new tool to identify precipitation evaporation using ground-based remote-sensing observations"],"prefix":"10.5194","volume":"16","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-6699-7040","authenticated-orcid":false,"given":"Heike","family":"Kalesse-Los","sequence":"first","affiliation":[]},{"given":"Anton","family":"K\u00f6tsche","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-1164-3576","authenticated-orcid":false,"given":"Andreas","family":"Foth","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6205-6016","authenticated-orcid":false,"given":"Johannes","family":"R\u00f6ttenbacher","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-6696-4967","authenticated-orcid":false,"given":"Teresa","family":"Vogl","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4818-5011","authenticated-orcid":false,"given":"Jonas","family":"Witthuhn","sequence":"additional","affiliation":[]}],"member":"3145","published-online":{"date-parts":[[2023,3,29]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","unstructured":"Acquistapace, C., Coulter, R., Crewell, S., Garcia-Benadi, A., Gierens, R., Labbri, G., Myagkov, A., Risse, N., and Schween, J. H.: EUREC4A's Maria S. Merian ship-based cloud and micro rain radar observations of clouds and precipitation, Earth Syst. Sci. Data, 14, 33\u201355, https:\/\/doi.org\/10.5194\/essd-14-33-2022, 2022.\u2002a, b","DOI":"10.5194\/essd-14-33-2022"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Austin, P., Wang, Y., Kujala, V., and Pincus, R.: Precipitation in stratocumulus clouds: Observational and modeling results, J. Atmos. Sci., 52, 2329\u20132352, 1995.\u2002a","DOI":"10.1175\/1520-0469(1995)052<2329:PISCOA>2.0.CO;2"},{"key":"ref3","doi-asserted-by":"crossref","unstructured":"Bailey, A., Aemisegger, F., Villiger, L., Los, S. A., Reverdin, G., Qui\u00f1ones Mel\u00e9ndez, E., Acquistapace, C., Baranowski, D. B., B\u00f6ck, T., Bony, S., Bordsdorff, T., Coffman, D., de Szoeke, S. P., Diekmann, C. J., D\u00fctsch, M., Ertl, B., Galewsky, J., Henze, D., Makuch, P., Noone, D., Quinn, P. K., R\u00f6sch, M., Schneider, A., Schneider, M., Speich, S., Stevens, B., and Thompson, E. J.: Isotopic measurements in water vapor, precipitation, and seawater during EUREC4A, Earth Syst. Sci. Data, 15, 465\u2013495, https:\/\/doi.org\/10.5194\/essd-15-465-2023, 2023.\u2002a","DOI":"10.5194\/essd-15-465-2023"},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"Baker, M.: Trade cumulus observations, in: The Representation of Cumulus Convection in Numerical Models, Springer, 29\u201337, ISBN\u00a0978-1-935704-13-3, 1993.\u2002a","DOI":"10.1007\/978-1-935704-13-3_3"},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"Bony, S., Stevens, B., Ament, F., Bigorre, S., Chazette, P., Crewell, S., Delano\u00eb, J., Emanuel, K., Farrell, D., Flamant, C., Gross, S., Hirsch, L., Karstensen, J., Mayer, B., Nuijens, L., Ruppert, J.\u00a0H., Sandu, I., Siebesma,\nP., Speich, S., Szczap, F., Totems, J., Vogel, R., Wendisch, M., and Wirth,\nM.: EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds,\nConvection and Circulation, Surv. Geophys., 38, 1529\u20131568,\nhttps:\/\/doi.org\/10.1007\/s10712-017-9428-0, 2017.\u2002a","DOI":"10.1007\/s10712-017-9428-0"},{"key":"ref6","unstructured":"B\u00fchl, J., Radenz, M., Schimmel, W., Vogl, T., R\u00f6ttenbacher, J., and Lochmann, M.: pyLARDA v3.2, Zenodo [code], https:\/\/doi.org\/10.5281\/zenodo.4721311, 2021.\u2002a, b"},{"key":"ref7","doi-asserted-by":"crossref","unstructured":"Dawson, D.\u00a0T., Xue, M., Milbrandt, J.\u00a0A., and Yau, M.: Comparison of evaporation and cold pool development between single-moment and multimoment bulk microphysics schemes in idealized simulations of tornadic thunderstorms,\nMon. Weather Rev., 138, 1152\u20131171, 2010.\u2002a","DOI":"10.1175\/2009MWR2956.1"},{"key":"ref8","doi-asserted-by":"crossref","unstructured":"Emanuel, K.\u00a0A., David\u00a0Neelin, J., and Bretherton, C.\u00a0S.: On large-scale\ncirculations in convecting atmospheres, Q. J. Roy. Meteor. Soc., 120, 1111\u20131143, 1994.\u2002a","DOI":"10.1002\/qj.49712051902"},{"key":"ref9","doi-asserted-by":"crossref","unstructured":"Illingworth, A.\u00a0J., Hogan, R.\u00a0J., O'Connor, E., Bouniol, D., Brooks, M.\u00a0E., Delano\u00e9, J., Donovan, D.\u00a0P., Eastment, J.\u00a0D., Gaussiat, N., Goddard, J. W.\u00a0F., Haeffelin, M., Baltink, H.\u00a0K., Krasnov, O.\u00a0A., Pelon, J., Piriou, J.-M., Protat, A., Russchenberg, H. W.\u00a0J., Seifert, A., Tompkins, A.\u00a0M., van\nZadelhoff, G.-J., Vinit, F., Will\u00e9n, U., Wilson, D.\u00a0R., and Wrench,\nC.\u00a0L.: Cloudnet: Continuous Evaluation of Cloud Profiles in Seven\nOperational Models Using Ground-Based Observations, B. Am. Meteorol. Soc.,\n88, 883\u2013898, https:\/\/doi.org\/10.1175\/BAMS-88-6-883, 2007.\u2002a","DOI":"10.1175\/BAMS-88-6-883"},{"key":"ref10","unstructured":"Jansen, F.: Ceilometer Measurements RV Meteor, EUREC4A, medium: NetCDF, ASCII, AERIS Portal [data set], https:\/\/doi.org\/10.25326\/53, 2020.\u2002a"},{"key":"ref11","unstructured":"Kalesse-Los, H., R\u00f6ttenbacher, J., Sch\u00e4fer, M., and Emmanouilidis, A.: Microwave Radiometer Measurements RV Meteor, EUREC4A,\nmedium: NetCDF, AERIS Portal [data set], https:\/\/doi.org\/10.25326\/77, 2020.\u2002a"},{"key":"ref12","unstructured":"Kalesse-Los, H., R\u00f6ttenbacher, J., and Sch\u00e4fer, M.: W-Band Radar\nMeasurements RV Meteor, EUREC4A, medium: NetCDF, Version Number: 1.0, AERIS Portal [data set], https:\/\/doi.org\/10.25326\/164, 2021.\u2002a"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"K\u00fcchler, N., Kneifel, S., L\u00f6hnert, U., Kollias, P., Czekala, H., and Rose, T.: A W-Band Radar\u2013Radiometer System for Accurate and Continuous Monitoring of Clouds and Precipitation, J. Atmos. Ocean. Tech., 34, 2375\u20132392, https:\/\/doi.org\/10.1175\/jtech-d-17-0019.1, 2017.\u2002a","DOI":"10.1175\/JTECH-D-17-0019.1"},{"key":"ref14","doi-asserted-by":"crossref","unstructured":"Langhans, W. and Romps, D.\u00a0M.: The origin of water vapor rings in tropical\noceanic cold pools, Geophys. Res. Lett., 42, 7825\u20137834, 2015.\u2002a","DOI":"10.1002\/2015GL065623"},{"key":"ref15","doi-asserted-by":"crossref","unstructured":"Li, X. and Srivastava, R.\u00a0C.: An analytical solution for raindrop evaporation\nand its application to radar rainfall measurements, J. Appl. Meteor., 40,\n1607\u20131616, 2001.\u2002a","DOI":"10.1175\/1520-0450(2001)040<1607:AASFRE>2.0.CO;2"},{"key":"ref16","doi-asserted-by":"crossref","unstructured":"L\u00f6hnert, U. and Crewell, S.: Accuracy of Cloud Liquid Water Path from\nGround-Based Microwave Radiometry 1. Dependency on Cloud Model\nStatistics, Radio Sci., 38, 8041, https:\/\/doi.org\/10.1029\/2002RS002654, 2003.\u2002a","DOI":"10.1029\/2002RS002654"},{"key":"ref17","doi-asserted-by":"crossref","unstructured":"Maahn, M., Burgand, C., Crewell, S., Gorodetskaya, I.\u00a0V., Kneifel, S., Lhermitte, S., Tricht, K.\u00a0V., and van Lipzig, N.\u00a0P.: How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions?, J. Geophys. Res., 119, 13604\u201313620\u200b\u200b\u200b\u200b\u200b\u200b\u200b, https:\/\/doi.org\/10.1002\/2014JD022079, 2014.\u2002a","DOI":"10.1002\/2014JD022079"},{"key":"ref18","doi-asserted-by":"crossref","unstructured":"Nuijens, L., Serikov, I., Hirsch, L., Lonitz, K., and Stevens, B.: The distribution and variability of low-level cloud in the North Atlantic trades, Q. J. Roy. Meteor. Soc., 140, 2364\u20132374, 2014.\u2002a","DOI":"10.1002\/qj.2307"},{"key":"ref19","doi-asserted-by":"crossref","unstructured":"Nuijens, L., Medeiros, B., Sandu, I., and Ahlgrimm, M.: The behavior of trade-wind cloudiness in observations and models: The major cloud components\nand their variability, J. Adv. Model. Earth Sy., 7, 600\u2013616, 2015.\u2002a","DOI":"10.1002\/2014MS000390"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Reiche, C.\u00a0H. and Lasher-Trapp, S.: The minor importance of giant aerosol to\nprecipitation development within small trade wind cumuli observed during\nRICO, Atmos. Res., 95, 386\u2013399, 2010.\u2002a","DOI":"10.1016\/j.atmosres.2009.11.002"},{"key":"ref21","doi-asserted-by":"crossref","unstructured":"Romps, D.\u00a0M.: Exact Expression for the Lifting Condensation Level, J. Atmos. Sci., 74, 3891\u20133900, https:\/\/doi.org\/10.1175\/JAS-D-17-0102.1, 2017.\u2002a","DOI":"10.1175\/JAS-D-17-0102.1"},{"key":"ref22","doi-asserted-by":"crossref","unstructured":"Rosenfeld, D. and Mintz, Y.: Evaporation of Rain Falling from Convective Clouds as Derived from Radar Measurements, J. Appl. Meteorol., 27,\n209\u2013215, https:\/\/doi.org\/10.1175\/1520-0450(1988)027&amp;lt;0209:eorffc&amp;gt;2.0.co;2, 1988.\u2002a","DOI":"10.1175\/1520-0450(1988)027<0209:EORFFC>2.0.CO;2"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Schimmel, W., Kalesse-Los, H., Maahn, M., Vogl, T., Foth, A., Garfias, P. S., and Seifert, P.: Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks, Atmos. Meas. Tech., 15, 5343\u20135366, https:\/\/doi.org\/10.5194\/amt-15-5343-2022, 2022.\u2002a","DOI":"10.5194\/amt-15-5343-2022"},{"key":"ref24","doi-asserted-by":"crossref","unstructured":"Schlemmer, L. and Hohenegger, C.: The formation of wider and deeper clouds as a result of cold-pool dynamics, J. Atmos. Sci., 71, 2842\u20132858, 2014.\u2002a","DOI":"10.1175\/JAS-D-13-0170.1"},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"Snodgrass, E.\u00a0R., Di\u00a0Girolamo, L., and Rauber, R.\u00a0M.: Precipitation characteristics of trade wind clouds during RICO derived from radar, satellite, and aircraft measurements, J. Appl. Meteorol. Clim., 48, 464\u2013483, 2009.\u2002a","DOI":"10.1175\/2008JAMC1946.1"},{"key":"ref26","doi-asserted-by":"crossref","unstructured":"Stevens, B., Farrell, D., Hirsch, L., Jansen, F., Nuijens, L., Serikov, I., Br\u00fcgmann, B., Forde, M., Linne, H., Lonitz, K., and Properso, J. M.: The Barbados Cloud Observatory: Anchoring investigations of clouds and circulation on the edge of the ITCZ, B. Am. Meteorol. Soc., 97, 787\u2013801, 2016.\u2002a","DOI":"10.1175\/BAMS-D-14-00247.1"},{"key":"ref27","doi-asserted-by":"crossref","unstructured":"Stevens, B., Bony, S., Brogniez, H., Hentgen, L., Hohenegger, C., Kiemle, C., L'Ecuyer, T.\u00a0S., Naumann, A.\u00a0K., Schulz, H., Siebesma, P.\u00a0A., Vial, J., Winker, D.\u00a0M., and Zuidema, P.: Sugar, gravel, fish and flowers: Mesoscale cloud patterns in the trade winds, Q. J. Roy. Meteor. Soc., 146, 141\u2013152, https:\/\/doi.org\/10.1002\/qj.3662, 2019.\u2002a","DOI":"10.1002\/qj.3662"},{"key":"ref28","doi-asserted-by":"crossref","unstructured":"Stevens, B., Bony, S., Farrell, D., Ament, F., Blyth, A., Fairall, C., Karstensen, J., Quinn, P. K., Speich, S., Acquistapace, C., Aemisegger, F., Albright, A. L., Bellenger, H., Bodenschatz, E., Caesar, K.-A., Chewitt-Lucas, R., de Boer, G., Delano\u00eb, J., Denby, L., Ewald, F., Fildier, B., Forde, M., George, G., Gross, S., Hagen, M., Hausold, A., Heywood, K. J., Hirsch, L., Jacob, M., Jansen, F., Kinne, S., Klocke, D., K\u00f6lling, T., Konow, H., Lothon, M., Mohr, W., Naumann, A. K., Nuijens, L., Olivier, L., Pincus, R., P\u00f6hlker, M., Reverdin, G., Roberts, G., Schnitt, S., Schulz, H., Siebesma, A. P., Stephan, C. C., Sullivan, P., Touz\u00e9-Peiffer, L., Vial, J., Vogel, R., Zuidema, P., Alexander, N., Alves, L., Arixi, S., Asmath, H., Bagheri, G., Baier, K., Bailey, A., Baranowski, D., Baron, A., Barrau, S., Barrett, P. A., Batier, F., Behrendt, A., Bendinger, A., Beucher, F., Bigorre, S., Blades, E., Blossey, P., Bock, O., B\u00f6ing, S., Bosser, P., Bourras, D., Bouruet-Aubertot, P., Bower, K., Branellec, P., Branger, H., Brennek, M., Brewer, A., Brilouet , P.-E., Br\u00fcgmann, B., Buehler, S. A., Burke, E., Burton, R., Calmer, R., Canonici, J.-C., Carton, X., Cato Jr., G., Charles, J. A., Chazette, P., Chen, Y., Chilinski, M. T., Choularton, T., Chuang, P., Clarke, S., Coe, H., Cornet, C., Coutris, P., Couvreux, F., Crewell, S., Cronin, T., Cui, Z., Cuypers, Y., Daley, A., Damerell, G. M., Dauhut, T., Deneke, H., Desbios, J.-P., D\u00f6rner, S., Donner, S., Douet, V., Drushka, K., D\u00fctsch, M., Ehrlich, A., Emanuel, K., Emmanouilidis, A., Etienne, J.-C., Etienne-Leblanc, S., Faure, G., Feingold, G., Ferrero, L., Fix, A., Flamant, C., Flatau, P. J., Foltz, G. R., Forster, L., Furtuna, I., Gadian, A., Galewsky, J., Gallagher, M., Gallimore, P., Gaston, C., Gentemann, C., Geyskens, N., Giez, A., Gollop, J., Gouirand, I., Gourbeyre, C., de Graaf, D., de Groot, G. E., Grosz, R., G\u00fcttler, J., Gutleben, M., Hall, K., Harris, G., Helfer, K. C., Henze, D., Herbert, C., Holanda, B., Ibanez-Landeta, A., Intrieri, J., Iyer, S., Julien, F., Kalesse, H., Kazil, J., Kellman, A., Kidane, A. T., Kirchner, U., Klingebiel, M., K\u00f6rner, M., Kremper, L. A., Kretzschmar, J., Kr\u00fcger, O., Kumala, W., Kurz, A., L'H\u00e9garet, P., Labaste, M., Lachlan-Cope, T., Laing, A., Landsch\u00fctzer, P., Lang, T., Lange, D., Lange, I., Laplace, C., Lavik, G., Laxenaire, R., Le Bihan, C., Leandro, M., Lefevre, N., Lena, M., Lenschow, D., Li, Q., Lloyd, G., Los, S., Losi, N., Lovell, O., Luneau, C., Makuch, P., Malinowski, S., Manta, G., Marinou, E., Marsden, N., Masson, S., Maury, N., Mayer, B., Mayers-Als, M., Mazel, C., McGeary, W., McWilliams, J. C., Mech, M., Mehlmann, M., Meroni, A. N., Mieslinger, T., Minikin, A., Minnett, P., M\u00f6ller, G., Morfa Avalos, Y., Muller, C., Musat, I., Napoli, A., Neuberger, A., Noisel, C., Noone, D., Nordsiek, F., Nowak, J. L., Oswald, L., Parker, D. J., Peck, C., Person, R., Philippi, M., Plueddemann, A., P\u00f6hlker, C., P\u00f6rtge, V., P\u00f6schl, U., Pologne, L., Posyniak, M., Prange, M., Qui\u00f1ones Mel\u00e9ndez, E., Radtke, J., Ramage, K., Reimann, J., Renault, L., Reus, K., Reyes, A., Ribbe, J., Ringel, M., Ritschel, M., Rocha, C. B., Rochetin, N., R\u00f6ttenbacher, J., Rollo, C., Royer, H., Sadoulet, P., Saffin, L., Sandiford, S., Sandu, I., Sch\u00e4fer, M., Schemann, V., Schirmacher, I., Schlenczek, O., Schmidt, J., Schr\u00f6der, M., Schwarzenboeck, A., Sealy, A., Senff, C. J., Serikov, I., Shohan, S., Siddle, E., Smirnov, A., Sp\u00e4th, F., Spooner, B., Stolla, M. K., Szk\u00f3\u0142ka, W., de Szoeke, S. P., Tarot, S., Tetoni, E., Thompson, E.,&lt;span id=&quot;page1705&quot;\/&gt; Thomson, J., Tomassini, L., Totems, J., Ubele, A. A., Villiger, L., von Arx, J., Wagner, T., Walther, A., Webber, B., Wendisch, M., Whitehall, S., Wiltshire, A., Wing, A. A., Wirth, M., Wiskandt, J., Wolf, K., Worbes, L., Wright, E., Wulfmeyer, V., Young, S., Zhang, C., Zhang, D., Ziemen, F., Zinner, T., and Z\u00f6ger, M.: EUREC4A, Earth Syst. Sci. Data, 13, 4067\u20134119, https:\/\/doi.org\/10.5194\/essd-13-4067-2021, 2021.\u2002a, b, c","DOI":"10.5194\/essd-13-4067-2021"},{"key":"ref29","doi-asserted-by":"crossref","unstructured":"Touz\u00e9-Peiffer, L., Vogel, R., and Rochetin, N.: Cold Pools Observed during EUREC4A: Detection and Characterization from Atmospheric Soundings, J. Appl. Meteorol. Clim., 61, 593\u2013610, https:\/\/doi.org\/10.1175\/JAMC-D-21-0048.1, 2022.\n\u2002a","DOI":"10.1175\/JAMC-D-21-0048.1"},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Tridon, F., Battaglia, A., and Watters, D.: Evaporation in action sensed by multiwavelength Doppler radars, J. Geophys. 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Clim., 61,\n441\u2013456, https:\/\/doi.org\/10.1175\/jamc-d-20-0211.1, 2022.\u2002a, b","DOI":"10.1175\/JAMC-D-20-0211.1"},{"key":"ref34","doi-asserted-by":"crossref","unstructured":"van der Velden, E.: CMasher: Scientific colormaps for making accessible,\ninformative and \u201ccmashing\u201d plots, J. Open Source Softw., 5,\n2004, https:\/\/doi.org\/10.21105\/joss.02004, 2020.\u2002a","DOI":"10.21105\/joss.02004"},{"key":"ref35","doi-asserted-by":"crossref","unstructured":"Vial, J., Vogel, R., Bony, S., Stevens, B., Winker, D.\u00a0M., Cai, X., Hohenegger, C., Naumann, A.\u00a0K., and Brogniez, H.: A new look at the daily cycle of trade wind cumuli, J. Adv. Model. Earth Sy., 11, 3148\u20133166, 2019.\u2002a","DOI":"10.1029\/2019MS001746"},{"key":"ref36","doi-asserted-by":"crossref","unstructured":"Vogel, R., Konow, H., Schulz, H., and Zuidema, P.: A climatology of trade-wind cumulus cold pools and their link to mesoscale cloud organization, Atmos. Chem. Phys., 21, 16609\u201316630, https:\/\/doi.org\/10.5194\/acp-21-16609-2021, 2021.\u2002a","DOI":"10.5194\/acp-21-16609-2021"},{"key":"ref37","doi-asserted-by":"crossref","unstructured":"Vogl, T., Maahn, M., Kneifel, S., Schimmel, W., Moisseev, D., and Kalesse-Los, H.: Using artificial neural networks to predict riming from Doppler cloud radar observations, Atmos. Meas. Tech., 15, 365\u2013381, https:\/\/doi.org\/10.5194\/amt-15-365-2022, 2022.\u2002a","DOI":"10.5194\/amt-15-365-2022"},{"key":"ref38","unstructured":"Witthuhn, J., R\u00f6ttenbacher, J., and Kalesse-Los, H.: Virga-Sniffer (v1.0.0), Zenodo [code], https:\/\/doi.org\/10.5281\/zenodo.7433405, 2022.\u2002a, b, c, d"},{"key":"ref39","doi-asserted-by":"crossref","unstructured":"Xie, X., Evaristo, R., Troemel, S., Saavedra, P., Simmer, C., and Ryzhkov, A.: Radar observation of evaporation and implications for quantitative precipitation and cooling rate estimation, J. Atmos. Ocean. 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