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  FESSTVaL: The Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg

Hohenegger, C., Ament, F., Beyrich, F., Löhnert, U., Rust, H., Bange, J., et al. (2023). FESSTVaL: The Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg. Bulletin of the American Meteorological Society, 104, E1875-E1892. doi:10.1175/BAMS-D-21-0330.1.

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2023
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The data of the FESSTVaL measurement campaign (Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg) from 2021
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Miscellaneous

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 Creators:
Hohenegger, Cathy1, 2, Author                 
Ament, Felix2, 3, Author           
Beyrich, F.4, Author
Löhnert, U.2, 5, Author
Rust, H.2, 6, Author
Bange, J.7, Author
Böck, T.5, Author
Böttcher, C.2, 6, Author
Boventer, J.7, Author
Burgemeister, F.3, Author
Clemens, M.3, Author
Detring, C.4, Author
Detring, I.8, Author
Dewani, N.2, 9, Author
Bastak-Duran, I.2, 9, Author
Fiedler, S.2, 5, Author
Göber, M.2, Author
van Heerwaarden, C.10, Author
Heusinkveld, B.10, Author
Kirsch, B.2, 3, Author
Klocke, Daniel2, 11, Author                 Knist, C.4, AuthorLange, I.3, AuthorLauermann, F.4, AuthorLehmann, V.4, AuthorLehmke, J.2, 6, AuthorLeinweber, R.4, AuthorLundgren, K2, 3, AuthorMasbou, M.2, 8, AuthorMauder, M.12, AuthorMol, W.10, AuthorNevermann, H.13, AuthorNomokonova, T.5, AuthorPäschke, E.4, AuthorPlatis, A.7, AuthorReichardt, J.4, AuthorRochette, L.14, AuthorSakradzija, M.2, AuthorSchlemmer, L.8, AuthorSchmidli, J.2, 9, AuthorShokri, N.13, AuthorSobottke, V.2, 6, AuthorSpeidel, J.15, AuthorSteinheuer, J.2, 5, AuthorTurner, D. D.16, AuthorVogelmann, H.15, AuthorWedemeyer, C.5, AuthorWeide-Luiz, E.2, 5, AuthorWiesner, S.2, 3, AuthorWildmann, N.17, AuthorWolz, K.15, AuthorWetz, T.17, Author more..
Affiliations:
1Climate Surface Interaction, Department Climate Physics, MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_3001851              
2Hans Ertel Centre for Weather Research, ou_persistent22              
3Meteorological Institute, Center for Earth System Research and Sustainability, University of Hamburg, External Organizations, Hamburg, DE, ou_3495875              
4Meteorological Observatory Lindenberg, ou_persistent22              
5Institute for Geophysics and Meteorology, University of Cologne, ou_persistent22              
6Institute for Meteorology, Freie Universität Berlin, ou_persistent22              
7Environmental Physics, GUZ, University of Tübingen, ou_persistent22              
8Deutscher Wetterdienst, External Organizations, Offenbach, DE, ou_3495849              
9Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, ou_persistent22              
10Meteorology and Air Quality Group, Wageningen University, ou_persistent22              
11Computational Infrastructure and Model Development (CIMD), Scientific Computing Lab (ScLab), MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_2129638              
12TU Dresden, ou_persistent22              
13Institute of Geo-Hydroinformatics, Hamburg University of Technology, ou_persistent22              
14LR Tech Inc., Lévis, Quebec, ou_persistent22              
15Institute of Meteorology and Climate Research–Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, ou_persistent22              
16National Oceanic and Atmospheric Administration (NOAA), Boulder, Colorado, ou_persistent22              
17Institute of Atmospheric Physics, Deutsches Zentrum für Luft- und Raumfahrt e.V., Oberpfaffenhofen, ou_persistent22              

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 Abstract: Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools,
forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale,
with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s
measurement strategy and show first observational results including unprecedented highly resolved
spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.

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Language(s): eng - English
 Dates: 2023-082023-09-062023-10
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: BibTex Citekey: HoheneggerAmentEtAl2023
DOI: 10.1175/BAMS-D-21-0330.1
 Degree: -

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Title: Bulletin of the American Meteorological Society
Source Genre: Journal
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Publ. Info: American Meteorological Society
Pages: - Volume / Issue: 104 Sequence Number: - Start / End Page: E1875 - E1892 Identifier: ISSN: 0003-0007
CoNE: https://pure.mpg.de/cone/journals/resource/954925377920