guest ::
| Home > Publications database > A Rainfall Data Intercomparison Dataset of RADKLIM, RADOLAN, and Rain Gauge Data for Germany > print |
| Home > Publications database > A Rainfall Data Intercomparison Dataset of RADKLIM, RADOLAN, and Rain Gauge Data for Germany > print |
| 001 | 873453 | ||
| 005 | 20210130004430.0 | ||
| 024 | 7 | _ | |a 10.3390/data4030118 |2 doi |
| 024 | 7 | _ | |a 2128/24147 |2 Handle |
| 024 | 7 | _ | |a altmetric:64484442 |2 altmetric |
| 024 | 7 | _ | |a WOS:000487958500036 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-00730 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Kreklow, J. |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a A Rainfall Data Intercomparison Dataset of RADKLIM, RADOLAN, and Rain Gauge Data for Germany |
| 260 | _ | _ | |a Basel |c 2019 |b MDPI |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1580733418_825 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Quantitative precipitation estimates (QPE) derived from weather radars provide spatially and temporally highly resolved rainfall data. However, they are also subject to systematic and random bias and various potential uncertainties and therefore require thorough quality checks before usage. The dataset described in this paper is a collection of precipitation statistics calculated from the hourly nationwide German RADKLIM and RADOLAN QPEs provided by the German Weather Service (Deutscher Wetterdienst (DWD)), which were combined with rainfall statistics derived from rain gauge data for intercomparison. Moreover, additional information on parameters that can potentially influence radar data quality, such as the height above sea level, information on wind energy plants and the distance to the next radar station, were included in the dataset. The resulting two point shapefiles are readable with all common GIS and constitutes a spatially highly resolved rainfall statistics geodataset for the period 2006 to 2017, which can be used for statistical rainfall analyses or for the derivation of model inputs. Furthermore, the publication of this data collection has the potential to benefit other users who intend to use precipitation data for any purpose in Germany and to identify the rainfall dataset that is best suited for their application by a straightforward comparison of three rainfall datasets without any tedious data processing and georeferencing |
| 536 | _ | _ | |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) |0 G:(DE-HGF)POF3-255 |c POF3-255 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Tetzlaff, Björn |0 P:(DE-Juel1)129578 |b 1 |
| 700 | 1 | _ | |a Kuhnt, G. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Burkhard, B. |0 P:(DE-HGF)0 |b 3 |
| 773 | _ | _ | |a 10.3390/data4030118 |g Vol. 4, no. 3, p. 118 - |0 PERI:(DE-600)2856531-9 |n 3 |p 118 - |t Data |v 4 |y 2019 |x 2306-5729 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/873453/files/Kreklow%20et%20al.%202019_data-04-00118-v2.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/873453/files/Kreklow%20et%20al.%202019_data-04-00118-v2.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:873453 |p openaire |p open_access |p driver |p VDB:Earth_Environment |p VDB |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)129578 |
| 913 | 1 | _ | |a DE-HGF |l Terrestrische Umwelt |1 G:(DE-HGF)POF3-250 |0 G:(DE-HGF)POF3-255 |2 G:(DE-HGF)POF3-200 |v Terrestrial Systems: From Observation to Prediction |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |b Erde und Umwelt |
| 914 | 1 | _ | |y 2019 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0112 |2 StatID |b Emerging Sources Citation Index |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Blind peer review |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-3-20101118 |k IBG-3 |l Agrosphäre |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-3-20101118 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|