000864348 001__ 864348
000864348 005__ 20241126210225.0
000864348 0247_ $$2doi$$a10.5194/essd-11-845-2019
000864348 0247_ $$2ISSN$$a1866-3508
000864348 0247_ $$2ISSN$$a1866-3516
000864348 0247_ $$2Handle$$a2128/22582
000864348 0247_ $$2altmetric$$aaltmetric:62054957
000864348 0247_ $$2WOS$$aWOS:000471617400001
000864348 037__ $$aFZJ-2019-04144
000864348 082__ $$a550
000864348 1001_ $$0P:(DE-HGF)0$$aDias Neto, José$$b0$$eCorresponding author
000864348 245__ $$aThe TRIple-frequency and Polarimetric radar Experiment for improving process observations of winter precipitation
000864348 260__ $$aKatlenburg-Lindau$$bCopernics Publications$$c2019
000864348 3367_ $$2DRIVER$$aarticle
000864348 3367_ $$2DataCite$$aOutput Types/Journal article
000864348 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1732613712_788
000864348 3367_ $$2BibTeX$$aARTICLE
000864348 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000864348 3367_ $$00$$2EndNote$$aJournal Article
000864348 520__ $$aThis paper describes a 2-month dataset of ground-based triple-frequency (X, Ka, and W band) Doppler radar observations during the winter season obtained at the Jülich ObservatorY for Cloud Evolution Core Facility (JOYCE-CF), Germany. All relevant post-processing steps, such as re-gridding and offset and attenuation correction, as well as quality flagging, are described. The dataset contains all necessary information required to recover data at intermediate processing steps for user-specific applications and corrections (https://doi.org/10.5281/zenodo.1341389; Dias Neto et al., 2019). The large number of ice clouds included in the dataset allows for a first statistical analysis of their multifrequency radar signatures. The reflectivity differences quantified by dual-wavelength ratios (DWRs) reveal temperature regimes where aggregation seems to be triggered. Overall, the aggregation signatures found in the triple-frequency space agree with and corroborate conclusions from previous studies. The combination of DWRs with mean Doppler velocity and linear depolarization ratio enables us to distinguish signatures of rimed particles and melting snowflakes. The riming signatures in the DWRs agree well with results found in previous triple-frequency studies. Close to the melting layer, however, we find very large DWRs (up to 20 dB), which have not been reported before. A combined analysis of these extreme DWR with mean Doppler velocity and a linear depolarization ratio allows this signature to be separated, which is most likely related to strong aggregation, from the triple-frequency characteristics of melting particles.
000864348 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
000864348 588__ $$aDataset connected to CrossRef
000864348 7001_ $$0P:(DE-HGF)0$$aKneifel, Stefan$$b1
000864348 7001_ $$00000-0002-9964-2200$$aOri, Davide$$b2
000864348 7001_ $$0P:(DE-HGF)0$$aTrömel, Silke$$b3
000864348 7001_ $$0P:(DE-HGF)0$$aHandwerker, Jan$$b4
000864348 7001_ $$0P:(DE-Juel1)2693$$aBohn, Birger$$b5
000864348 7001_ $$0P:(DE-Juel1)129470$$aHermes, Normen$$b6
000864348 7001_ $$0P:(DE-HGF)0$$aMühlbauer, Kai$$b7
000864348 7001_ $$0P:(DE-HGF)0$$aLenefer, Martin$$b8
000864348 7001_ $$00000-0003-3001-8642$$aSimmer, Clemens$$b9
000864348 773__ $$0PERI:(DE-600)2475469-9$$a10.5194/essd-11-845-2019$$gVol. 11, no. 2, p. 845 - 863$$n2$$p845 - 863$$tEarth system science data$$v11$$x1866-3516$$y2019
000864348 8564_ $$uhttps://juser.fz-juelich.de/record/864348/files/essd-11-845-2019.pdf$$yOpenAccess
000864348 8564_ $$uhttps://juser.fz-juelich.de/record/864348/files/essd-11-845-2019.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000864348 909CO $$ooai:juser.fz-juelich.de:864348$$pdnbdelivery$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire
000864348 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)2693$$aForschungszentrum Jülich$$b5$$kFZJ
000864348 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129470$$aForschungszentrum Jülich$$b6$$kFZJ
000864348 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
000864348 9141_ $$y2019
000864348 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000864348 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000864348 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000864348 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bEARTH SYST SCI DATA : 2017
000864348 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bEARTH SYST SCI DATA : 2017
000864348 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000864348 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000864348 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000864348 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000864348 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000864348 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000864348 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences
000864348 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000864348 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000864348 9201_ $$0I:(DE-Juel1)ICE-3-20101013$$kICE-3$$lTroposphäre$$x1
000864348 9201_ $$0I:(DE-Juel1)IEK-8-20101013$$kIEK-8$$lTroposphäre$$x2
000864348 980__ $$ajournal
000864348 980__ $$aVDB
000864348 980__ $$aI:(DE-Juel1)IBG-3-20101118
000864348 980__ $$aI:(DE-Juel1)ICE-3-20101013
000864348 980__ $$aI:(DE-Juel1)IEK-8-20101013
000864348 980__ $$aUNRESTRICTED
000864348 9801_ $$aFullTexts