[1186] - 5th PhD report: Assimilation of 3D Radar Reflectivities with an Ensemble Kalman Filter on the Convective Scale

All available metadata of the dataset is listed below. Some features are available, e.g. download of dataset or additional description file.

By downloading files from this dataset you accept the license terms of TR32DB Data policy agreement and TR32DBData Protection Statement.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
VERY IMPORTANT!
Due to the speed of the filesystem and depending on the size of the archive and the file to be extracted, it may take up to thirty (!) minutes until a download is ready! Beware of that when confirming since you may not close the tab because otherwise, you will not get your file!
Features
Citation
Bick, T., 2015. 5th PhD report: Assimilation of 3D Radar Reflectivities with an Ensemble Kalman Filter on the Convective Scale. PhD Report, Meteorologisches Institut, Universität Bonn, Bonn. Accessed from https://www.tr32db.uni-koeln.de/data.php?dataID=1186 at 2019-07-20.
Citation Options
Export as: Select the file format for your download.Citation style: Select the displayed citation style.
Identification
Title(s):Main Title: 5th PhD report: Assimilation of 3D Radar Reflectivities with an Ensemble Kalman Filter on the Convective Scale
Description(s):Abstract: An ensemble data assimilation system for 3D radar reflectivity data on the convective scale is introduced for the convection permitting numerical weather prediction model COSMO. KENDA, developed by Deutscher Wetterdienst (DWD) and its partners, provides a state-of-the-art ensemble data assimilation system on the convective scale for operational data assimilation and forecasting based on a variant of the ensemble Kalman filter. In this study, the radar forward operator EMVORADO is applied for the assimilation of radar reflectivity data to improve short-term model predictions of precipitation. Both deterministic and ensemble forecasts have been carried out based on KENDA. A case study shows that the assimilation of 3D radar reflectivity data clearly improves precipitation location in the analysis and has a positive impact on the forecast for several hours following the analysis. The influence of different update rates on the noise in terms of surface pressure tendencies and on the forecast quality in general are investigated. For a period of seven consecutive days the results are compared to those of DWD’s current operational radar assimilation scheme based on the latent heat nudging.
Responsible Party
Creator(s):Author: Theresa Bick
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Atmosphere
Related Sub-project(s):C6
Subject(s):CRC/TR32 Keywords: Data Assimilation, Radar, COSMO
File Details
File Name:tbick_report5_2015.pdf
Data Type:Text
File Size:35280 kB (34.453 MB)
Date(s):Available: 2015-09-11
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:None
Measurement Location:--None--
Specific Informations - Report
Report Date:11th of September, 2015
Report Type:PhD Report
Report City:Bonn
Report Institution:Meteorologisches Institut, Universität Bonn
Metadata Details
Metadata Creator:Theresa Bick
Metadata Created:2015-09-18
Metadata Last Updated:2015-09-18
Subproject:C6
Funding Phase:3
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:338
Metadata Downloads:0
Dataset Downloads:5
Dataset Activity
Features