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FESSTVaL: the Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg
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2023
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Source: Bulletin of the American Meteorological Society (2023)
[PDF-5.51 MB]
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Journal Title:Bulletin of the American Meteorological Society
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Description: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 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 8 Doppler lidars and 4 microwave radiometers distributed at 3 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 four-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly-resolved spatio-temporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.
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Source:Bulletin of the American Meteorological Society (2023)
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ISSN:0003-0007;1520-0477;
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