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Doppler Lidar Observations of the Mixing Height in Indianapolis Using an Automated Composite Fuzzy Logic Approach
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2018
Source: Journal of Atmospheric and Oceanic Technology, 35(3), 473-490.
Details:
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Journal Title:Journal of Atmospheric and Oceanic Technology
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Personal Author:
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NOAA Program & Office:
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Description:A Halo Photonics Stream Line XR Doppler lidar has been deployed for the Indianapolis Flux Experiment (INFLUX) to measure profiles of the mean horizontal wind and the mixing layer height for quantification of greenhouse gas emissions from the urban area. To measure the mixing layer height continuously and autonomously, a novel composite fuzzy logic approach has been developed that combines information from various scan types, including conical and vertical-slice scans and zenith stares, to determine a unified measurement of the mixing height and its uncertainty. The composite approach uses the strengths of each measurement strategy to overcome the limitations of others so that a complete representation of turbulent mixing is made in the lowest approximate to 2 km, depending on clouds and aerosol distribution. Additionally, submeso nonturbulent motions are identified from zenith stares and removed from the analysis, as these motions can lead to an overestimate of the mixing height. The mixing height is compared with in situ profile measurements from a research aircraft for validation. To demonstrate the utility of the measurements, statistics of the mixing height and its diurnal and annual variability for 2016 are also presented. The annual cycle is clearly captured, with the largest and smallest afternoon mixing heights observed at the summer and winter solstices, respectively. The diurnal cycle of the mixing layer is affected by the mean wind, growing slower in the morning and decaying more rapidly in the evening with lighter winds.
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Source:Journal of Atmospheric and Oceanic Technology, 35(3), 473-490.
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Rights Information:Other
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Compliance:Submitted
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Main Document Checksum:urn:sha256:44b16dac44cce94169bd229cfe7a05e5c68b454b522a2af10cda62a39f28119f
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