In:
Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 14, No. 2 ( 2021-02-18), p. 1253-1266
Abstract:
Abstract. Fast-response infrared gas analyzers (IRGAs) have been widely used
over 3 decades in many ecosystems for long-term monitoring of water
vapor fluxes in the surface layer of the atmosphere. While some of the early
IRGA sensors are still used in these national and/or regional eco-flux
networks, optically improved IRGA sensors are newly employed in the same
networks. The purpose of this study was to evaluate the performance of water
vapor density and flux data from three generations of IRGAs – LI-7500,
LI-7500A, and LI-7500RS (LI-COR Bioscience, Inc., Nebraska, USA) – over the
course of a growing season in Bushland, Texas, USA, in an irrigated maize
canopy for 90 d. Water vapor density measurements were in generally good
agreement, but temporal drift occurred in different directions and
magnitudes. Means exhibited mostly shift changes that did not impact the
flux magnitudes, while their variances of water vapor density fluctuations
were occasionally in poor agreement, especially following rainfall events.
LI-7500 cospectra were largest compared to LI-7500RS and LI-7500A, especially
under unstable and neutral static stability. Agreement among the sensors was
best under the typical irrigation-cooled boundary layer, with a 14 %
interinstrument coefficient of variability under advective conditions.
Generally, the smallest variances occurred with the LI-7500RS, and
high-frequency spectral corrections were larger for these measurements,
resulting in similar fluxes between the LI-7500A and LI-7500RS. Fluxes from
the LI-7500 were best representative of growing season ET based on a
world-class lysimeter reference measurement, but using the energy balance
ratio as an estimate of systematic bias corrected most of the differences
among measured fluxes.
Type of Medium:
Online Resource
ISSN:
1867-8548
DOI:
10.5194/amt-14-1253-2021
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2021
detail.hit.zdb_id:
2505596-3
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