Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets

<p>The radar reflectivity factor is important for estimating cloud microphysical properties; thus, in this study, we determine the quantitative influence of microscale turbulent clustering of polydisperse droplets on the radar reflectivity factor. The theoretical solution for particulate Bragg...

Full description

Bibliographic Details
Main Authors: K. Matsuda, R. Onishi
Format: Article
Language:English
Published: Copernicus Publications 2019-02-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/19/1785/2019/acp-19-1785-2019.pdf
id doaj-5aad14f4fc294e3d92714cd609fe7855
record_format Article
spelling doaj-5aad14f4fc294e3d92714cd609fe78552020-11-24T23:58:07ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242019-02-01191785179910.5194/acp-19-1785-2019Turbulent enhancement of radar reflectivity factor for polydisperse cloud dropletsK. Matsuda0R. Onishi1Center for Earth Information Science and Technology (CEIST), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showa-machi, Kanazawa-ku, Yokohama 236-0001, JapanCenter for Earth Information Science and Technology (CEIST), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showa-machi, Kanazawa-ku, Yokohama 236-0001, Japan<p>The radar reflectivity factor is important for estimating cloud microphysical properties; thus, in this study, we determine the quantitative influence of microscale turbulent clustering of polydisperse droplets on the radar reflectivity factor. The theoretical solution for particulate Bragg scattering is obtained without assuming monodisperse droplet sizes. The scattering intensity is given by an integral function including the cross spectrum of number density fluctuations for two different droplet sizes. We calculate the cross spectrum based on turbulent clustering data, which are obtained by the direct numerical simulation (DNS) of particle-laden homogeneous isotropic turbulence. The results show that the coherence of the cross spectrum is close to unity for small wave numbers and decreases almost exponentially with increasing wave number. This decreasing trend is dependent on the combination of Stokes numbers. A critical wave number is introduced to characterize the exponential decrease of the coherence and parameterized using the Stokes number difference. Comparison with DNS results confirms that the proposed model can reproduce the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>r</mi><mi mathvariant="normal">p</mi><mn mathvariant="normal">3</mn></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="12pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="2faf24fba3b2758095fe0eaeb23475a2"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-1785-2019-ie00001.svg" width="12pt" height="17pt" src="acp-19-1785-2019-ie00001.png"/></svg:svg></span></span>-weighted power spectrum, which is proportional to the clustering influence on the radar reflectivity factor to a sufficiently high accuracy. Furthermore, the proposed model is extended to incorporate the gravitational settling influence by modifying the critical wave number based on the analytical equation derived for the bidisperse radial distribution function. The estimate of the modified model also shows good agreement with the DNS results for the case with gravitational droplet settling. The model is then applied to high-resolution cloud-simulation data obtained from a spectral-bin cloud simulation. The result shows that the influence of turbulent clustering can be significant inside turbulent clouds. The large influence is observed at the near-top of the clouds, where the liquid water content and the energy dissipation rate are sufficiently large.</p>https://www.atmos-chem-phys.net/19/1785/2019/acp-19-1785-2019.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. Matsuda
R. Onishi
spellingShingle K. Matsuda
R. Onishi
Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
Atmospheric Chemistry and Physics
author_facet K. Matsuda
R. Onishi
author_sort K. Matsuda
title Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
title_short Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
title_full Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
title_fullStr Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
title_full_unstemmed Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
title_sort turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2019-02-01
description <p>The radar reflectivity factor is important for estimating cloud microphysical properties; thus, in this study, we determine the quantitative influence of microscale turbulent clustering of polydisperse droplets on the radar reflectivity factor. The theoretical solution for particulate Bragg scattering is obtained without assuming monodisperse droplet sizes. The scattering intensity is given by an integral function including the cross spectrum of number density fluctuations for two different droplet sizes. We calculate the cross spectrum based on turbulent clustering data, which are obtained by the direct numerical simulation (DNS) of particle-laden homogeneous isotropic turbulence. The results show that the coherence of the cross spectrum is close to unity for small wave numbers and decreases almost exponentially with increasing wave number. This decreasing trend is dependent on the combination of Stokes numbers. A critical wave number is introduced to characterize the exponential decrease of the coherence and parameterized using the Stokes number difference. Comparison with DNS results confirms that the proposed model can reproduce the <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>r</mi><mi mathvariant="normal">p</mi><mn mathvariant="normal">3</mn></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="12pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="2faf24fba3b2758095fe0eaeb23475a2"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-1785-2019-ie00001.svg" width="12pt" height="17pt" src="acp-19-1785-2019-ie00001.png"/></svg:svg></span></span>-weighted power spectrum, which is proportional to the clustering influence on the radar reflectivity factor to a sufficiently high accuracy. Furthermore, the proposed model is extended to incorporate the gravitational settling influence by modifying the critical wave number based on the analytical equation derived for the bidisperse radial distribution function. The estimate of the modified model also shows good agreement with the DNS results for the case with gravitational droplet settling. The model is then applied to high-resolution cloud-simulation data obtained from a spectral-bin cloud simulation. The result shows that the influence of turbulent clustering can be significant inside turbulent clouds. The large influence is observed at the near-top of the clouds, where the liquid water content and the energy dissipation rate are sufficiently large.</p>
url https://www.atmos-chem-phys.net/19/1785/2019/acp-19-1785-2019.pdf
work_keys_str_mv AT kmatsuda turbulentenhancementofradarreflectivityfactorforpolydisperseclouddroplets
AT ronishi turbulentenhancementofradarreflectivityfactorforpolydisperseclouddroplets
_version_ 1725451714672197632