Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1...
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Transcript of Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1...
![Page 1: Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1 Howard University, Washington, DC, USA 2 UCAR, Boulder,](https://reader035.fdocuments.in/reader035/viewer/2022070414/5697c0141a28abf838ccd2b7/html5/thumbnails/1.jpg)
Analysis of PBL Turbulent and Non-turbulent Fluxes
M. Hicks1, S. Kang2, B. Demoz1, E. Joseph1,
1 Howard University, Washington, DC, USA2 UCAR, Boulder, CO, USA
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Outline
• Overview
• HUBC Characteristics
• Methodology
• Preliminary Results
• Future Work
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Motivation• Previous (observational and model) studies have
suggested that strong heterogeneous CBLs can produce non-turbulent fluxes at scales with magnitudes comparable to turbulent fluxes (Kang and Davis 2008, Kang et al. 2007, LeMone et al. 2002, Mahrt et al. 1994a,b)
• Implying turbulent theory may fail under these conditions
From (Kang, 2008)
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Objective & Purpose
• Objective– Examine the importance of non-turbulent to turbulent
heat and moisture transport in a heterogeneous CBL.• Look at the importance of presenting a proper timescale
• Purpose– Analyze the non-turbulent and turbulent
characteristics of fluxes at HUBC through tower observation
• No one has used tower observations to examine non-turbulent flux exchanges
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Howard University Beltsville, MD Research Campus
http://meiyu.atmphys.howard.edu/beltsville/inde3.html
• Site Characteristics – Located 12 miles NE of Washington, DC– Heterogeneous landscape – Experiences a wide range of water vapor and aerosol
concentrations
HU Beltsville Campus
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Methodology1. Apply FFT and MR Spectra analysis to find
timescale, , needed to separate turbulent and non-turbulent fluxes
– The traditional 30 minute may not be sufficient in eliminating non-turbulent fluxes for heterogeneous cases. (Vickers and Mahrt 2003)
2. Examine the contribution of non-turbulent fluxes to total flux
XTot=X-<X>, XNT=[X]-<X>, XT=X-[X]
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Case Study
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Preliminary Results
• Vertical velocity energy pass 100 sec is small as expected
• WVMR has strong energy exchanges around 1000 sec
• A timescale less much less than 30mins is needed to separate T and NT fluxes
• The NT fluxes are not very strong
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Separating Fluxes
•Green~ Instantaneous timeseries
•red ~mesoscale averaged timeseries, [X]
• blue ~domain averaged timeseries,<X>
X’=X-<X>
XNT=[X]-<X>,
XT=X-[X]
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Preliminary Results
The intensity of WT transport of non-turbulent heat is clearly seen
The lack of intensity from pure non-turbulent mesoscale flux is seen
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Summary
• We showed that a 30 minute timescale average may not always represent pure turbulence.– It is believed that including non-turbulence
can give a bias to CBL parameterizations
• Interscale flux maybe able to explain intense moments of non-turbulence
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Future Work
• Make Further progress with analysis surface layer CBL turbulent and non-turbulent fluxes
• Expand diagnosis to examine flux characteristics of the well mixed and inversion layers of the heterogeneous CBL.– Summer 2010 HUBC Field Campaign
• Tethersonde Balloon• HURL ~1min• MDE wind profiler ~1min• Microwave Radiometer (r,T) ~2min• Leosphere lidar ~10s• Radiosondes
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Acknowledgements
• I thank all supporters of this work, – Dr. Songlak Kang for suggestions– Dr. Belay Demoz – Dr. Everette Joseph– Dr. Demetrius Venable and HURL team – NCAS for support
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Backup Slides
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Overview• Why Study PBL Fluxes???
– Fluxes play a critical role in the development of the height of the PBL
• Operational obs of PBL heights are not taken to validate forecast model parameterizations
– Models at time can significantly over or under estimate PBL heights
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From Kang et al., 2007
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Monin-Obukov Similarity theory
Businger et al. 1971
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Kang and Davis 2008
Weak heterogeneous case
Strong heterogeneous case
Turbulent flux
Interscale flux
Non-Turbulent flux
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Preliminary Results
• Green line is instantaneous timeseries, X
• red line is mesoscale averaged timeseries, [X]
• blue line is domain averaged timeseries,<X>
F(sec-1)
XNT=[X]-<X>, XT=X-[X]
07092007
F(sec-1)