2nd PhD report: High-resolution radar data assimilation using the LETKF

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Title:Main Title: 2nd PhD report: High-resolution radar data assimilation using the LETKF
Description:Abstract: The prediction of convective events is a difficult task due to the nonlinear and chaotic behaviour of the atmosphere on this scale. Therefore, data assimilation (DA) is crucial to enhance numerical weather prediction (NWP). Radar observations seem very promising for convective scale DA because of their capability to capture the 3D spatial and temporal evolution of a convective system. In recent years, much work has been investigated in Ensemble Kalman filter approaches. Ensemble methods do not consider a single, deterministic forecast but an ensemble of forecasts and estimate (flow dependent) covariances from the ensemble. Since the maximum number of ensemble members is limited by the available machine power, it is usually not possible to run an ensemble of more than 50 ensemble members in real-data NWP applications. The model state space has yet a much higher dimension, hence the ensemble covariance provides only a low rank approximation. Especially in regions close to the radar, the measurement is much denser than the grid of the numerical model, thus a sophisticated preprocessing of the observations might be necessary. The concept of superobservations will be explained and applied to two case studies.
Responsible Party
Creator:Theresa Bick (Author)
Publisher:CRC/TR32 Database (TR32DB)
Publication Year:2013
Topic
TR32 Topic:Remote Sensing
Related Subproject:C6
Subjects:Keywords: Atmosphere, Data Assimilation
File Details
Filename:report2_tbick_2013.pdf
Data Type:Text - Text
File Size:14.7 MB
Date:Created: 31.10.2013
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
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
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Specific Information - Report
Report Date:31st of October, 2013
Report Type:PhD Report
Report City:Bonn, Germany
Report Institution:Meteorological Institute, University of Bonn
Metadata Details
Metadata Creator:Theresa Bick
Metadata Created:13.12.2013
Metadata Last Updated:13.12.2013
Subproject:C6
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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