Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data
Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) O...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/10/7/384 |
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| author | Hubert Luce Lakshmi Kantha Hiroyuki Hashiguchi Dale Lawrence |
| author_facet | Hubert Luce Lakshmi Kantha Hiroyuki Hashiguchi Dale Lawrence |
| author_sort | Hubert Luce |
| collection | DOAJ |
| description | Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula> and temperature structure function parameter <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> from one-dimensional wind and temperature frequency spectra are first described in detail. Both are based on the identification of inertial (−5/3) subranges in respective spectra. Using a formulation relating <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> valid for Kolmogorov turbulence in steady state, the flux Richardson number <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi>f</mi> </msub> </mrow> </semantics> </math> </inline-formula> and the mixing efficiency <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>χ</mi> <mi>m</mi> </msub> </mrow> </semantics> </math> </inline-formula> are then estimated. The statistical analysis confirms the variability of <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi>f</mi> </msub> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>χ</mi> <mi>m</mi> </msub> </mrow> </semantics> </math> </inline-formula> around <inline-formula> <math display="inline"> <semantics> <mrow> <mo>~</mo> <mn>0.13</mn> <mo>−</mo> <mn>0.14</mn> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <mo>~</mo> <mn>0.16</mn> <mo>−</mo> <mn>0.17</mn> </mrow> </semantics> </math> </inline-formula>, respectively, values close to the canonical values found from some earlier experimental and theoretical studies of both the atmosphere and the oceans. The relevance of the interpretation of the inertial subranges in terms of Kolmogorov turbulence is confirmed by assessing the consistency of additional parameters, the Ozmidov length scale <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>L</mi> <mi>O</mi> </msub> </mrow> </semantics> </math> </inline-formula>, the buoyancy Reynolds number <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <msub> <mi>e</mi> <mi>b</mi> </msub> </mrow> </semantics> </math> </inline-formula>, and the gradient Richardson number <i>Ri</i>. Finally, a case study is presented showing altitude differences between the peaks of <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>N</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula>, suggesting turbulent stirring at the margin of a stable temperature gradient sheet. The possible contribution of this sheet and layer structure on clear air radar backscattering mechanisms is examined. |
| first_indexed | 2024-04-12T11:20:44Z |
| format | Article |
| id | doaj.art-1a93f8008d914c479314039b0eeb0d99 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-04-12T11:20:44Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
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| series | Atmosphere |
| spelling | doaj.art-1a93f8008d914c479314039b0eeb0d992022-12-22T03:35:22ZengMDPI AGAtmosphere2073-44332019-07-0110738410.3390/atmos10070384atmos10070384Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV DataHubert Luce0Lakshmi Kantha1Hiroyuki Hashiguchi2Dale Lawrence3Université de Toulon, Aix-Marseille University, CNRS IRD, MIO, UM110, 83041 Toulon, FranceDepartment of Aerospace Engineering Sciences, University of Colorado, Boulder, CO 80309, USAResearch Institute for Sustainable Humanosphere, Kyoto University, Kyoto 611-0011, JapanDepartment of Aerospace Engineering Sciences, University of Colorado, Boulder, CO 80309, USATurbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula> and temperature structure function parameter <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> from one-dimensional wind and temperature frequency spectra are first described in detail. Both are based on the identification of inertial (−5/3) subranges in respective spectra. Using a formulation relating <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> valid for Kolmogorov turbulence in steady state, the flux Richardson number <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi>f</mi> </msub> </mrow> </semantics> </math> </inline-formula> and the mixing efficiency <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>χ</mi> <mi>m</mi> </msub> </mrow> </semantics> </math> </inline-formula> are then estimated. The statistical analysis confirms the variability of <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi>f</mi> </msub> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>χ</mi> <mi>m</mi> </msub> </mrow> </semantics> </math> </inline-formula> around <inline-formula> <math display="inline"> <semantics> <mrow> <mo>~</mo> <mn>0.13</mn> <mo>−</mo> <mn>0.14</mn> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <mo>~</mo> <mn>0.16</mn> <mo>−</mo> <mn>0.17</mn> </mrow> </semantics> </math> </inline-formula>, respectively, values close to the canonical values found from some earlier experimental and theoretical studies of both the atmosphere and the oceans. The relevance of the interpretation of the inertial subranges in terms of Kolmogorov turbulence is confirmed by assessing the consistency of additional parameters, the Ozmidov length scale <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>L</mi> <mi>O</mi> </msub> </mrow> </semantics> </math> </inline-formula>, the buoyancy Reynolds number <inline-formula> <math display="inline"> <semantics> <mrow> <mi>R</mi> <msub> <mi>e</mi> <mi>b</mi> </msub> </mrow> </semantics> </math> </inline-formula>, and the gradient Richardson number <i>Ri</i>. Finally, a case study is presented showing altitude differences between the peaks of <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>N</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>C</mi> <mi>T</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mi>ε</mi> </semantics> </math> </inline-formula>, suggesting turbulent stirring at the margin of a stable temperature gradient sheet. The possible contribution of this sheet and layer structure on clear air radar backscattering mechanisms is examined.https://www.mdpi.com/2073-4433/10/7/384turbulenceenergy dissipation ratetemperature structure functioneddy diffusivityouter scalemixing efficiencyOzmidov length scaleKolmogorov turbulence |
| spellingShingle | Hubert Luce Lakshmi Kantha Hiroyuki Hashiguchi Dale Lawrence Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data Atmosphere turbulence energy dissipation rate temperature structure function eddy diffusivity outer scale mixing efficiency Ozmidov length scale Kolmogorov turbulence |
| title | Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data |
| title_full | Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data |
| title_fullStr | Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data |
| title_full_unstemmed | Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data |
| title_short | Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data |
| title_sort | estimation of turbulence parameters in the lower troposphere from shurex 2016 2017 uav data |
| topic | turbulence energy dissipation rate temperature structure function eddy diffusivity outer scale mixing efficiency Ozmidov length scale Kolmogorov turbulence |
| url | https://www.mdpi.com/2073-4433/10/7/384 |
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