TR32-Database: Database of Transregio 32

[715] - Backscatter differential phase - estimation and variability

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

Features
Citation
Troemel, S., Kumjian, M. R. ., Ryzhkov, A., Simmer, C., Diederich, M., 2013. Backscatter differential phase - estimation and variability. Journal of Atmospheric and Oceanic Technology, 52, 2529 - 2548. DOI: 10.1175/JAMC-D-13-0124.1.
Identification
Title(s):Main Title: Backscatter differential phase - estimation and variability
Description(s):Abstract: Based on simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase δ has been explored. δ has been identified as an important polarimetric variable, which should not be ignored in precipitation estimations based on KDP, especially at shorter radar wavelengths. Moreover, δ bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating δ in rain and in the melting layer are suggested. The method for estimating δ in rain is based on a modified version of the ZPHI algorithm, and provides reasonably robust estimates of δ and KDP in pure rain except in regions where the total measured differential phase DP behaves erratically, such as areas affected by nonuniform beam filling (NBF) or low signal-to noise ratio. The method for estimating δ in the melting layer results in reliable estimates of δ in stratiform precipitation and requires azimuthal averaging of radial profiles of DP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between δ and differential reflectivity ZDR. Because δ is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between ZDR and δ is of interest for quantitative precipitation estimation: δ and ZDR are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of δ can be utilized as an important calibration parameter for improving microphysical models of the melting layer.
Identifier(s):DOI: 10.1175/JAMC-D-13-0124.1
Responsible Party
Creator(s):Author: Silke Troemel
Author: Matthew R. Kumjian
Author: Alexander Ryzhkov
Author: Clemens Simmer
Author: Malte Diederich
Publisher:American Meteorological Society
Topic
TR32 Topic:Atmosphere
Subject(s):CRC/TR32 Keywords: Backscatter, Remote Sensing, Precipitation
File Details
File Name:2013_Troemel_JoAOT.pdf
Data Type:Text
Size(s):54 Pages
File Size:3488 kB (3.406 MB)
Date(s):Date Submitted: 2013-03-01
Issued: 2013-11-01
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:-no map data
East:-
South:-
West:-
Measurement Region:Other
Measurement Location:--Other--
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2013
Type:Article
Article Type:Journal
Source:Journal of Atmospheric and Oceanic Technology
Volume:52
Page Range:2529 - 2548
Metadata Details
Metadata Creator:Clemens Simmer
Metadata Created:2013-12-03
Metadata Last Updated:2013-12-03
Subproject:D5
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:152
Metadata Downloads:0
Dataset Downloads:4
Dataset Activity
Features