[774] - 1st PhD Report: High-resolution radar data assimilation using the LETKF

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., 2013. 1st PhD Report: High-resolution radar data assimilation using the LETKF. PhD Report, Meteorological Institute, University Bonn, Bonn, Germany. Accessed from https://www.tr32db.uni-koeln.de/data.php?dataID=774 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: 1st PhD Report: High-resolution radar data assimilation using the LETKF
Subtitle: -
Description(s):Abstract: The prediction of convective events is a dicult task due to the nonlinear and chaotic behaviour of the atmosphere on this scale. Observation-based nowcasting methods are useful for very short-range forecasts, but after a lead time of approximately 2 hours, uncertainties become too large. Another approach of forecasting is given by numerical weather prediction (NWP) models. NWP forecasts are, mathematically speaking, an initial value problem. For an intial state given on the 3-dimensional discrete model grid, a forecast can be obtained by the forward integration of the set of (typically nonlinear) model equations describing the dynamics of the atmosphere. However, since the number of observations available is typically much smaller than the dimension of the model state vector, this intial value problem is extremely underdetermined. Data assimilation alleviates this problem by the use of additional information, for example given by error statististics of both model and observations. Thus, a possible enhancement of short-term model forecasts of high-impact weather events could be given by the assimilation of 3 dimensional radar reflectivity data. In this report, the plans for this PhD project will be introduced and discussed in more detail.
Responsible Party
Creator(s):Author: Theresa Bick
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Remote Sensing
Related Sub-project(s):C6
Subject(s):CRC/TR32 Keywords: Data Assimilation, Atmosphere
File Details
File Name:report1_tbick_2013.pdf
Data Type:Text
File Size:962 kB (0.939 MB)
Date(s):Available: 2013-06-14
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Geographic
North:51.5915435
East:7.4236328
South:50.2058789
West:5.2263672
Measurement Region:None
Measurement Location:--None--
Specific Informations - Report
Report Date:14th of June, 2013
Report Type:PhD Report
Report City:Bonn, Germany
Report Institution:Meteorological Institute, University Bonn
Number Of Pages:9
Period of Pages:1 - 9
Further Informations:TR32 Student Report Phase II
Metadata Details
Metadata Creator:Theresa Bick
Metadata Created:2013-12-06
Metadata Last Updated:2013-12-13
Subproject:C6
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:289
Metadata Downloads:0
Dataset Downloads:2
Dataset Activity
Features