ICOS Science Conference, Session 9

1. Comparison of large eddy simulation of a point source methane plume in
a slightly convective atmosphere with measurements from MEMO2
campaign
Raˇznjevi´c Anja, van Heerwaarden Chiel, Krol Maarten, Hensen Arjan, van den Bulk Pim,
Velzeboer Ilona
15. 09. 2020.
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2. Outline
1 Geographic setting of the measurement site
2 Measured data
3 Meteorology on the measurement day
4 Simulation set-up
5 Results
Meteorology in simulation and available data (ERA5)
6 Results
2D plume from LES
1D plume comparison
7 Conclusions
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3. Geographic setting of the measurement site
Figure 1: Measurement area on the experiment day. Actual measured source not shown.
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4. Geographic setting of the measurement site
Location of the measurement road
Figure 2: Location of the source and the adjacent road on which the measurements were taken.
The source is an oil well (red marker on the Figure) with leak assumed to be on ground level.
Measurements performed on the adjacent road NW from the source.
Measurements were performed in the afternoon, 14.30 - 17.30 LT (UTC + 3h). 4 / 14

5. Available data from the campaign
Figure 3: (Up) One minute averages of wind speed measured with a 3D sonic
anemometer in vicinity of the source. (Down) Plumes measured during the campaign.
The dataset consist of 40 plumes in total.
Figure 4: Wind rose for the
duration of the measurements.
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6. Meteorology on the measurement day, ERA5 data
Synoptic situation over Europe on 17th October, 2019.
ERA5: ECMWFs database of various meteorological variables for the Earth.
Horizontal: 30 × 30 km, Vertical: 25 hPa (close to surface) - 100 hPa (top of the
atmosphere), Temporal: 1 h.
Global estimates using historical observations and modelling.
Figure 5: Geopotential height (m) and temperature (K) of the 500 hPa pressure level at 12 UTC. ERA5 reanalysis data.
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7. Meteorology on the measurement day, ERA5 data
Meteorological conditions on the measurement site
Figure 6: ERA5 data for surface net solar radiation, sensible and latent heat fluxes, 2 m temperature and the boundary layer
height for the location of the measurements on the day of the campaign.
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8. Simulation set-up
Domain size 4.8 × 4.8 × 3.0 km
Horizontal resolution: 960 × 960
Vertical resolution: 480, stretched grid
with 2 m resolution at the surface and 40
m at the top
Temporal resolution: 10 s
Simulation nudged with vertical profiles
from ERA5.
Simulation time: 7 - 14 UTC
Gaussian shaped source placed at the
surface.
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9. Results
Figure 7: Snapshot of the 3D plume 2 h and 15 min from the start of the simulation, corresponding to 13:15 UTC.
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10. Results
Meteorology in simulation and available data (ERA5)
Figure 8: Comparison of vertical profiles from ERA5 and LES of (a) temperature, (b) specific humidity, (c) U component of
wind, and (d) V component of wind.
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11. Results
Meteorology in simulation and available data (measurements)
Figure 9: Comparison of wind speed (up) and horizontal wind direction (down) from measurements taken with 3D sonic and
wind sampled at the release point in the simulation at 3 m height.
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12. Results
2D plume from LES
LES allows for detailed study of plumes spatial position in time.
Figure 10: Snapshots of instantaneous plume through a vertical plane north from the source. The distance from source is 108 m
and time step between each transect is 1 min. x is shown in relation to the source position.
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13. Results
1D plume comparison
Figure 11: Half hour averages of the measured plumes
during the whole measurement experiment. Note that not
every half hour average consists of the same number of
plumes, due to the measurement process.
Figure 12: Half hour averages of LES plumes. The distance
from the source is 78 m centerline from source. Each averaged
plume consists of 30 instantaneous plumes.
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14. Conclusions
LES simulations provide plumes spatial and temporal extent in great detail.
Easily reproducible measurement process which allows for more accurate statistical analysis
of the plume.
The measurement campaign is a good LES case study since all the relevant processes for
plume dispersion have originated in the BL (no large scale advection).
The measurement site is characterized by flat terrain without obstacles that can affect
dispersion.
LES is capable of reproducing the meteorological conditions of the measurement campaign
relatively accurate.
To improve the understanding and reproducibility of field measurements in different
modelling tools (not only LES) good measurements of meteorological variables are needed.
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