Analysis of Turbulence driving the Canopy-Atmosphere Exchange at CABINEX 2009
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Eric Jones , Shelley Pressley , Serena Chung , Stephen Edburg
Washington State University Laboratory for Atmospheric Research
Introduction
Turbulence Analysis
Plants emit biogenic volatile organic compounds (BVOCs)
which play a role in air quality and global climate change.
Turbulence effects how BVOCs impact ozone and particle
formation by allowing mixing of above-canopy and belowcanopy air masses. In this study, a burst and sweep analysis (Lu and Willmarth, 1973) is conducted to characterize
coherent structures in turbulent flows over a forested canopy. Detailed analysis of a one-week period during the
summer 2009 CABINEX campaign is used to evaluate the
performance of the one-dimensional canopy chemistry
model CACHE (Forkel et al., 2006). The overall goal is to
determine how turbulence affects transport out of the
canopy, improve the CACHE model, and improve understanding of how forest BVOC emissions impact air quality
and climate change at the regional and global scales.
The CACHE Model
Figures 4-6: Wind speed deviations for the 12:30 - 1:00pm period of each day, presented on the same scale. The magnitude of the deviations vary greatly, but this is
standardized by the hole size; for all analysis completed in this study H=1 is used. July
23 (day 204, figure 4) has the highest number of points pass the hole size filter to be
considered as part of a coherent structure.
CACHE is a one-dimensional canopy chemistry model
that uses K-theory for vertical transport and does not
consider transport via coherent structures, such as
bursts and sweeps (Forkel et al., 2006). For comparison
to observed data from CABINEX, the model was driven
using 1 minute data for temperature (6m,21m,33m),
pressure (6m), humidity (6m), and wind speed(33m),
and 30 minute data for above canopy PAR. Figures 11
through 13 show the model results for isoprene concentrations, and are on the same scale as Figures 8 through
10.
50m
33m
Methods
21m
Sweep: u’>0, w’<0
Figure 1: Defining bursts and sweeps
II I
III IV
Figure 2: Horizontal (u’) vs. Vertical (w’)
wind speed deviations from the mean for
July 28, with multiple hole size filters applied. Percentages indicate the percent of
points in each hole size that fall into the
burst (II) or sweep (IV) quadrants.
6m
Figure 7: Results of the burst and sweep analysis, along with common stability indicators. Day 204 appears more turbulent than other days and shows the greatest periods of instability. Day 209 is relatively stable, but shows high shear based on the high
u* value.
Hole size is used to
filter out the mean
wind and only analyze large deviations;
see Equation 1. In
order to differentiate bursts and
sweeps from one another, 0.5 seconds
must pass before an
event is counted as a
new burst or sweep.
Interpretation and Observations
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July 23 (Day 204) had a low mean wind speed, but also a lot of
deviation from the mean. This is shown by the high total burst and
sweep times. This amount of turbulence indicates that the canopy
would be flushed quickly.
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July 24 (Day 205) also had a low
mean wind speed, but much lower
burst and sweep times. Under these
conditions, a longer time to flush
the canopy is expected.
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July 28 (Day 209) had a high
mean wind speed, with moderate
total burst and sweep times. The
high mean wind contributes to
faster canopy flushing, and is aided
by the turbulence.
Figures 8 through 10 present the Figures 8-10: Observed Isoprene
observed isoprene concentrations, concentration profiles. Data were
which fluctuate with turbulence as collected at 6m, 21m, and 33m in
one
minute
averages,
for
10
minwell as emissions factors.
(Equation 1)
Isoprene, the most abundant BVOC emitted by plants to
the atmosphere, was used for model comparison. Isoprene is produced from the leaves of trees, and emissions increase as a function of temperature and photosynthetically active radiation (PAR). Figure 3 presents basic meteorological parameters for one week. Three days
(days 204, 205, and 209) were chose for further analysis.
utes at each height before cycling
to the next height. White indicates
missing data.
Figures 11-13: Modeled Isoprene
from CACHE. The model performs
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reasonably well on the 24 and
28th, but overestimates isoprene
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concentrations on the 23 .
Figure 14: an approximation
of the layers in the CACHE
model up to 50m, and indications (in bold) where measurements were taken during
CABINEX.
Conclusions and Future Work
The results presented here indicate that coherent structures such as bursts and sweeps play a role in vertical
transport by affecting concentrations of ozone and particle
precursors, such as isoprene, within the canopy and transport of these compounds out of the canopy. Such processes are not considered in traditional 1-D canopy chemistry models, limiting our ability to understand the impact of
forest canopies on air quality and climate change at regional and global scales. While the results presented here
represent just one week of data and one chemical species,
the analysis will be extended to other species and the full
time period of the CABINEX campaign. The extended
analysis, along with a wavelet analysis being completed at
the University of Michigan, will improve our understanding of chemical measurements taken during the CABINEX
campaign and in-canopy chemical processing, and will
lead to an improved canopy model in the future.
Acknowledgements
Figure 3: Meteorological and atmospheric stability parameters for day 203 (July 22) through day 210 (July 29). Mean u is
wind speed (m/s), and z/L is the Monin-Obukhov stability indicator (unitless) where z/L < 0 is unstable, z/L ≈ 0 is neutral,
and z/L > 0 is stable.
PROPHET Tower
Burst: u’<0, w’>0
References
Thanks to Allison Steiner4 and Alex Bryan4 for their work and support updating
the CACHE model and collaboration with the turbulence study, and to all the
members of the CABINEX campaign.
Baldocchi, D. D., and T.P. Meyers (1988). Turbulence structure in a deciduous forest,
Boundary-Layer Meteorology, 43 (4), 345-364.
Thanks to the Washington State University REU coordinators, especially David
Bahr2, Shelley Pressley2, and Brian Lamb2.
Forkel, R., O. Klemm, M. Graus, B. Rappengluck, W. Stockwell, W. Grabmer, A. Held, A.
Hansel, and R. Steinbrecher (2006), Trace gas exchange and gas phase chemistry in a
Norway spruce forest: A study with a coupled 1-dimensional canopy atmospheric chemistry emission model, Atmos. Environ., 40, S28-S42, doi:10.1016/
j.atmosenv.2005.11.070.
1
Olin College of Engineering
2
Washington State University
3
University of Idaho
4
University of Michigan
Edburg, S. (2006). Importance of Large-Scale Turbulent Structures on Trace Gas Fluxes
from Forest Canopies.
This work was supported by
the National Science Foundation’s REU program under
grant number ATM-0754990.
Lu, S., and W. W. Willmarth (1973), Measurements of the structure of the Reynolds
stress in a turbulent boundary layer, J. Fluid Mech., 60, 481 –511.