{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T06:01:41Z","timestamp":1773381701247,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T00:00:00Z","timestamp":1635292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The detection and characterisation of the radar Bright Band (BB) are essential for many applications of weather radar quantitative precipitation estimates, such as heavy rainfall surveillance, hydrological modelling or numerical weather prediction data assimilation. This study presents a new technique to detect the radar BB levels (top, peak and bottom) for Doppler radar spectral moments from the vertically pointing radars applied here to a K-band radar, the MRR-Pro (Micro Rain Radar). The methodology includes signal and noise detection and dealiasing schemes to provide realistic vertical Doppler velocities of precipitating hydrometeors, subsequent calculation of Doppler moments and associated parameters and BB detection and characterisation. Retrieved BB properties are compared with the melting level provided by the MRR-Pro manufacturer software and also with the 0 \u00b0C levels for both dry-bulb temperature (freezing level) and wet-bulb temperature from co-located radio soundings in 39 days. In addition, a co-located Parsivel disdrometer is used to analyse the equivalent reflectivity of the lowest radar height bins confirming consistent results of the new signal and noise detection scheme. The processing methodology is coded in a Python program called RaProM-Pro which is freely available in the GitHub repository.<\/jats:p>","DOI":"10.3390\/rs13214323","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T23:24:42Z","timestamp":1635377082000},"page":"4323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A New Methodology to Characterise the Radar Bright Band Using Doppler Spectral Moments from Vertically Pointing Radar Observations"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5560-4392","authenticated-orcid":false,"given":"Albert","family":"Garcia-Benad\u00ed","sequence":"first","affiliation":[{"name":"SARTI, Universitat Polit\u00e8cnica de Catalunya, 08800 Vilanova i la Geltr\u00fa, Spain"},{"name":"Department of Applied Physics-Meteorology, University of Barcelona, 08028 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3597-7439","authenticated-orcid":false,"given":"Joan","family":"Bech","sequence":"additional","affiliation":[{"name":"Department of Applied Physics-Meteorology, University of Barcelona, 08028 Barcelona, Spain"},{"name":"Water Research Institute (IdRA), University of Barcelona, 08028 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2505-2435","authenticated-orcid":false,"given":"Sergi","family":"Gonzalez","sequence":"additional","affiliation":[{"name":"DT Catalonia, Agencia Estatal de Meteorolog\u00eda (AEMET), 08071 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8024-3293","authenticated-orcid":false,"given":"Mireia","family":"Udina","sequence":"additional","affiliation":[{"name":"Department of Applied Physics-Meteorology, University of Barcelona, 08028 Barcelona, Spain"}]},{"given":"Bernat","family":"Codina","sequence":"additional","affiliation":[{"name":"Department of Applied Physics-Meteorology, University of Barcelona, 08028 Barcelona, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.atmosres.2018.09.010","article-title":"Empirical values and assumptions in the microphysics of numerical models","volume":"215","author":"Tapiador","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1017\/S1350482701003139","article-title":"Aspects of melting and the radar bright band","volume":"8","author":"Gray","year":"2001","journal-title":"Meteorol. Appl."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1175\/1520-0426(2002)019<0687:AABHDA>2.0.CO;2","article-title":"An Automated Brightband Height Detection Algorithm for Use with Doppler Radar Spectral Moments","volume":"19","author":"White","year":"2002","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Fabry, F., and Zawadzki, I. (1995). Long-term radar observations of the melting layer of precipitation and their interpretation. J. Atmos. Sci.","DOI":"10.1175\/1520-0469(1995)052<0838:LTROOT>2.0.CO;2"},{"key":"ref_5","unstructured":"Fabry, F. (2018). Radar Meteorology Principles and Practice, Cambridge University Press."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2902","DOI":"10.1175\/JAS-D-14-0363.1","article-title":"Observations of Ice Microphysics through the Melting Layer","volume":"72","author":"Heymsfield","year":"2015","journal-title":"J. Atmos. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bordoy, R., Bech, J., Rigo, T., and Pineda, N. (2010). Analysis of a method for radar rainfall estimation considering the freezing level height. Tethys J. Weather Clim. West. Mediterr., 25\u201339.","DOI":"10.3369\/tethys.2010.7.03"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.jhydrol.2015.06.011","article-title":"Classification and correction of the bright band using an operational C-band polarimetric radar","volume":"531","author":"Hall","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Diezma, R., Zawadzki, I., and Sempere-Torres, D. (2000). Identification of the bright band through the analysis of volumetric radar data. J. Geophys. Res. Atmos.","DOI":"10.1029\/1999JD900310"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.atmosres.2012.06.021","article-title":"Remote sensing analysis of a Mediterranean thundersnow and low-altitude heavy snowfall event","volume":"123","author":"Bech","year":"2013","journal-title":"Atmos. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"125780","DOI":"10.1016\/j.jhydrol.2020.125780","article-title":"Surface precipitation phase discrimination in complex terrain","volume":"592","author":"Casellas","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3135","DOI":"10.1002\/qj.4121","article-title":"Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts","volume":"147","author":"Casellas","year":"2021","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.envsoft.2013.08.009","article-title":"Towards an integrated Flood Information System: Centralized data access, analysis, and visualization","volume":"50","author":"Demir","year":"2013","journal-title":"Environ. Model. Softw."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1002\/asl.274","article-title":"Propagation of uncertainty from observing systems into NWP: COST-731 Working Group 1","volume":"11","author":"Rossa","year":"2010","journal-title":"Atmos. Sci. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"104791","DOI":"10.1016\/j.envsoft.2020.104791","article-title":"Statewide real-time quantitative precipitation estimation using weather radar and NWP model analysis: Algorithm description and product evaluation","volume":"132","author":"Seo","year":"2020","journal-title":"Environ. Model. Softw."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1175\/JTECH-D-15-0020.1","article-title":"Quasi-Vertical Profiles\u2014A New Way to Look at Polarimetric Radar Data","volume":"33","author":"Ryzhkov","year":"2016","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tokay, A., Hartmann, P., Battaglia, A., Gage, K.S., Clark, W.L., and Williams, C.R. (2009). A field study of reflectivity and Z-R relations using vertically pointing radars and disdrometers. J. Atmos. Ocean. Technol.","DOI":"10.1175\/2008JTECHA1163.1"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1016\/j.asr.2010.01.001","article-title":"Investigation of vertical profile of rain microstructure at Ahmedabad in Indian tropical region","volume":"45","author":"Das","year":"2010","journal-title":"Adv. Sp. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2723","DOI":"10.1175\/JHM-D-17-0005.1","article-title":"The Chilean Coastal Orographic Precipitation Experiment: Observing the Influence of Microphysical Rain Regimes on Coastal Orographic Precipitation","volume":"18","author":"Massmann","year":"2017","journal-title":"J. Hydrometeorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1127\/metz\/2014\/0605","article-title":"Detection of the bright band with a vertically pointing K-band radar","volume":"23","author":"Pfaff","year":"2014","journal-title":"Meteorol. Z."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wang, H., Lei, H., and Yang, J. (2017). Microphysical processes of a stratiform precipitation event over eastern China: Analysis using Micro Rain Radar data. Adv. Atmos. Sci.","DOI":"10.1007\/s00376-017-7005-6"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2020GL087499","DOI":"10.1029\/2020GL087499","article-title":"Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications","volume":"47","author":"Li","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Romatschke, U. (2021). Melting Layer Detection and Observation with the NCAR Airborne W-Band Radar. Remote Sens., 13.","DOI":"10.3390\/rs13091660"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Benarroch, A., Siles, G.A., Riera, J.M., and Perez-Pena, S. (2020, January 15\u201320). Heights of the 0 \u00b0C Isotherm and the Bright Band in Madrid: Comparison and Variability. Proceedings of the 14th European Conference on Antennas and Propagation, EuCAP 2020, Copenhagen, Denmark.","DOI":"10.23919\/EuCAP48036.2020.9135509"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1175\/JHM-D-19-0085.1","article-title":"Relating the Radar Bright Band and Its Strength to Surface Rainfall Rate Using an Automated Approach","volume":"21","author":"Lin","year":"2020","journal-title":"J. Hydrometeorol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"112177","DOI":"10.1016\/j.rse.2020.112177","article-title":"A note on radar signatures of hydrometeors in the melting layer as inferred from Sentinel-1 SAR data acquired over the ocean","volume":"253","author":"Alpers","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"112355","DOI":"10.1016\/j.rse.2021.112355","article-title":"Automatic detection and classification of low-level orographic precipitation processes from space-borne radars using machine learning","volume":"257","author":"Arulraj","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_28","first-page":"353","article-title":"Rain observations with a vertically looking Micro Rain Radar (MRR)","volume":"7","author":"Peters","year":"2002","journal-title":"Boreal Environ. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1175\/JTECH-D-13-00174.1","article-title":"Evaluation of the New Version of the Laser-Optical Disdrometer, OTT Parsivel2","volume":"31","author":"Tokay","year":"2014","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_30","unstructured":"Metek MRR-Pro (2010). Description of Products. Valid for MRR-PRO Firmware VS \u2265 01, Metek Meteorologische Messtechnik GmbH."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Garcia-Benadi, A., Bech, J., Gonzalez, S., Udina, M., Codina, B., and Georgis, J.F. (2020). Precipitation type classification of Micro Rain Radar data using an improved Doppler spectral processing methodology. Remote Sens., 12.","DOI":"10.3390\/rs12244113"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1175\/1520-0450(1974)013<0808:ODOTNL>2.0.CO;2","article-title":"Objective Determination of the Noise Level in Doppler Spectra","volume":"13","author":"Hildebrand","year":"1974","journal-title":"J. Appl. Meteorol."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Adirosi, E., Baldini, L., and Tokay, A.L.I. (2020). Rainfall and DSD parameters comparison between Micro Rain Radar, two-dimensional video and Parsivel2 disdrometers, and S-band dual-polarization radar. J. Atmos. Ocean. Technol.","DOI":"10.1175\/JTECH-D-19-0085.1"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.5194\/amt-5-2661-2012","article-title":"Improved Micro Rain Radar snow measurements using Doppler spectra post-processing","volume":"5","author":"Maahn","year":"2012","journal-title":"Atmos. Meas. Tech."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/RG011i001p00001","article-title":"Doppler radar characteristics of precipitation at vertical incidence","volume":"11","author":"Atlas","year":"1973","journal-title":"Rev. Geophys."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1175\/2009JTECHA1342.1","article-title":"Rain Attenuation of Radar Echoes Considering Finite-Range Resolution and Using Drop Size Distributions","volume":"27","author":"Peters","year":"2010","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_37","unstructured":"Prahl, S. (2021, July 01). Miepython. Available online: https:\/\/miepython.readthedocs.io\/."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1364\/AO.19.001505","article-title":"Improved Mie scattering algorithms","volume":"19","author":"Wiscombe","year":"1980","journal-title":"Appl. Opt."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s00376-009-0211-0","article-title":"Comparison of the bright band characteristics measured by Micro Rain Radar (MRR) at a mountain and a coastal site in South Korea","volume":"26","author":"Cha","year":"2009","journal-title":"Adv. Atmos. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.eswa.2016.12.034","article-title":"Generalized exponential moving average (EMA) model with particle filtering and anomaly detection","volume":"73","author":"Nakano","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"6645","DOI":"10.5194\/amt-13-6645-2020","article-title":"Detecting the Melting Layer with a Micro Rain Radar Using a Neural Network Approach","volume":"13","author":"Brast","year":"2020","journal-title":"Atmos. Meas. Tech."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Lee, J.-E., Jung, S.-H., and Kwon, S. (2020). Characteristics of the Bright Band Based on Quasi-Vertical Profiles of Polarimetric Observations from an S-Band Weather Radar Network. Remote Sens., 12.","DOI":"10.3390\/rs12244061"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kneifel, S., Maahn, M., Peters, G., and Simmer, C. (2011). Observation of snowfall with a low-power FM-CW K-band radar (Micro Rain Radar). Meteorol. Atmos. Phys.","DOI":"10.1007\/s00703-011-0142-z"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"D11203","DOI":"10.1029\/2010JD015430","article-title":"A triple-frequency approach to retrieve microphysical snowfall parameters","volume":"116","author":"Kneifel","year":"2011","journal-title":"J. Geophys. Res. Atmos."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4323\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:21:27Z","timestamp":1760167287000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4323"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,27]]},"references-count":44,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214323"],"URL":"https:\/\/doi.org\/10.3390\/rs13214323","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,27]]}}}