[1081] - Meso-scale eddies affect near-surface turbulent exchange: evidence from lidar and tower measurements

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
Eder, F., Schmidt, M., Thomas, D., Träumner, K., 2014. Meso-scale eddies affect near-surface turbulent exchange: evidence from lidar and tower measurements. Journal of Applied Meteorology and Climatology, (submitted manuscript), 1 - 54.
Citation Options
Export as: Select the file format for your download.Citation style: Select the displayed citation style.
Identification
Title(s):Main Title: Meso-scale eddies affect near-surface turbulent exchange: evidence from lidar and tower measurements
Description(s):Abstract: The eddy-covariance technique tends to underestimate the turbulent heat fluxes, which results in the non-closure of the surface energy balance. This study shows experimental evidence that meso-scale turbulent organized structures, which are inherently not captured by the standard eddy-covariance technique, can affect the near-surface turbulent exchange. Using a combined setup of three Doppler wind lidars above a cropland-dominated area in Germany, low-frequency turbulent structures were detected in the surface layer down to a few meters above ground. In addition, data from two micrometeorological stations in the study area were analyzed with respect to energy balance closure. In accordance with several previous studies, the data confirm a strong friction velocity dependence of the energy balance residual. At both stations, the energy balance residual was found to be positively correlated with the vertical moisture gradient in the lower atmospheric boundary layer, but at only one station with the temperature gradient. This indicates that meso-scale transport probably contributes more to the latent heat flux than to the sensible heat flux, but this depends largely on the measurement site. Moreover, flow distortion due to tower mountings and measurement devices affects the energy balance closure considerably for certain wind directions.
Responsible Party
Creator(s):Author: Fabian Eder
Author: Marius Schmidt
Author: Damian Thomas
Author: Katja Träumner
Publisher:Journal of Applied Meteorology and Climatology
Topic
TR32 Topic:Atmosphere
Subject(s):CRC/TR32 Keywords: Energy Balance Closure, Eddy Covariance, Microwave Radiometer, LIDAR
File Details
File Name:Eder_et_al_manuscript.docx
Data Type:Text
Size(s):54 Pages
File Size:2611 kB (2.55 MB)
Date(s):Modified: 2014-09-12
Mime Type:application/vnd.openxmlformats-officedocument.wordprocessingml.document
Data Format:PDF
Language:English
Status:In Process
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:50.9790517
East:6.5207905
South:50.8058035
West:6.2461323
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Publication
Status:Submitted
Review:PeerReview
Year:2014
Type:Article
Article Type:Journal
Source:Journal of Applied Meteorology and Climatology
Volume:(submitted manuscript)
Page Range:1 - 54
Metadata Details
Metadata Creator:Marius Schmidt
Metadata Created:2014-09-18
Metadata Last Updated:2014-09-18
Subproject:Z3
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:565
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Features