On the Forward Modeling of Radar Doppler Spectrum Width From LES

Implications for Model Evaluation

Y. S. Chen, Johannes Verlinde, Eugene Edmund Clothiaux, A. S. Ackerman, A. M. Fridlind, M. Chamecki, P. Kollias, M. P. Kirkpatrick, B. C. Chen, G. Yu, A. Avramov

Research output: Contribution to journalArticle

Abstract

Large-eddy simulations of an observed single-layer Arctic mixed-phase cloud are analyzed to study the value of forward modeling of profiling millimeter wave cloud radar Doppler spectral width for model evaluation. Individual broadening terms and their uncertainties are quantified for the observed spectral width and compared to modeled broadening terms. Modeled turbulent broadening is narrower than the observed values when the turbulent kinetic energy dissipation rate from the subgrid scale model is used in the forward model. The total dissipation rates, estimated with the subgrid scale dissipation rates and the numerical dissipation rates, agree much better with both the retrieved dissipation rates and those inferred from the power spectra of the simulated vertical air velocity. The comparison of the microphysical broadening provides another evaluative measure of the ice properties in the simulation. To accurately retrieve dissipation rates as well as each broadening term from the observations, we suggest a few modifications to previously presented techniques. First, we show that the inertial subrange spectrum filtered with the radar sampling volume is a better underlying model than the unfiltered −5/3 law for the retrieval of the dissipation rate from the power spectra of the mean Doppler velocity. Second, we demonstrate that it is important to filter out turbulence and remove the layer-mean reflectivity-weighted mean fall speed from the observed mean Doppler velocity to avoid overestimation of shear broadening. Finally, we provide a method to quantify the uncertainty in the retrieved dissipation rates, which eventually propagates to the uncertainty in the microphysical broadening.

Original languageEnglish (US)
Pages (from-to)7444-7461
Number of pages18
JournalJournal of Geophysical Research: Atmospheres
Volume123
Issue number14
DOIs
StatePublished - Jul 27 2018

Fingerprint

Doppler radar
forward modeling
dissipation
evaluation
Power spectrum
uncertainty
Ice
Large eddy simulation
Millimeter waves
Kinetic energy
radar
power spectra
Energy dissipation
Radar
Turbulence
shear stress
Arctic region
Sampling
ice
rate

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Space and Planetary Science
  • Earth and Planetary Sciences (miscellaneous)
  • Palaeontology

Cite this

Chen, Y. S. ; Verlinde, Johannes ; Clothiaux, Eugene Edmund ; Ackerman, A. S. ; Fridlind, A. M. ; Chamecki, M. ; Kollias, P. ; Kirkpatrick, M. P. ; Chen, B. C. ; Yu, G. ; Avramov, A. / On the Forward Modeling of Radar Doppler Spectrum Width From LES : Implications for Model Evaluation. In: Journal of Geophysical Research: Atmospheres. 2018 ; Vol. 123, No. 14. pp. 7444-7461.
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abstract = "Large-eddy simulations of an observed single-layer Arctic mixed-phase cloud are analyzed to study the value of forward modeling of profiling millimeter wave cloud radar Doppler spectral width for model evaluation. Individual broadening terms and their uncertainties are quantified for the observed spectral width and compared to modeled broadening terms. Modeled turbulent broadening is narrower than the observed values when the turbulent kinetic energy dissipation rate from the subgrid scale model is used in the forward model. The total dissipation rates, estimated with the subgrid scale dissipation rates and the numerical dissipation rates, agree much better with both the retrieved dissipation rates and those inferred from the power spectra of the simulated vertical air velocity. The comparison of the microphysical broadening provides another evaluative measure of the ice properties in the simulation. To accurately retrieve dissipation rates as well as each broadening term from the observations, we suggest a few modifications to previously presented techniques. First, we show that the inertial subrange spectrum filtered with the radar sampling volume is a better underlying model than the unfiltered −5/3 law for the retrieval of the dissipation rate from the power spectra of the mean Doppler velocity. Second, we demonstrate that it is important to filter out turbulence and remove the layer-mean reflectivity-weighted mean fall speed from the observed mean Doppler velocity to avoid overestimation of shear broadening. Finally, we provide a method to quantify the uncertainty in the retrieved dissipation rates, which eventually propagates to the uncertainty in the microphysical broadening.",
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Chen, YS, Verlinde, J, Clothiaux, EE, Ackerman, AS, Fridlind, AM, Chamecki, M, Kollias, P, Kirkpatrick, MP, Chen, BC, Yu, G & Avramov, A 2018, 'On the Forward Modeling of Radar Doppler Spectrum Width From LES: Implications for Model Evaluation', Journal of Geophysical Research: Atmospheres, vol. 123, no. 14, pp. 7444-7461. https://doi.org/10.1029/2017JD028104

On the Forward Modeling of Radar Doppler Spectrum Width From LES : Implications for Model Evaluation. / Chen, Y. S.; Verlinde, Johannes; Clothiaux, Eugene Edmund; Ackerman, A. S.; Fridlind, A. M.; Chamecki, M.; Kollias, P.; Kirkpatrick, M. P.; Chen, B. C.; Yu, G.; Avramov, A.

In: Journal of Geophysical Research: Atmospheres, Vol. 123, No. 14, 27.07.2018, p. 7444-7461.

Research output: Contribution to journalArticle

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T1 - On the Forward Modeling of Radar Doppler Spectrum Width From LES

T2 - Implications for Model Evaluation

AU - Chen, Y. S.

AU - Verlinde, Johannes

AU - Clothiaux, Eugene Edmund

AU - Ackerman, A. S.

AU - Fridlind, A. M.

AU - Chamecki, M.

AU - Kollias, P.

AU - Kirkpatrick, M. P.

AU - Chen, B. C.

AU - Yu, G.

AU - Avramov, A.

PY - 2018/7/27

Y1 - 2018/7/27

N2 - Large-eddy simulations of an observed single-layer Arctic mixed-phase cloud are analyzed to study the value of forward modeling of profiling millimeter wave cloud radar Doppler spectral width for model evaluation. Individual broadening terms and their uncertainties are quantified for the observed spectral width and compared to modeled broadening terms. Modeled turbulent broadening is narrower than the observed values when the turbulent kinetic energy dissipation rate from the subgrid scale model is used in the forward model. The total dissipation rates, estimated with the subgrid scale dissipation rates and the numerical dissipation rates, agree much better with both the retrieved dissipation rates and those inferred from the power spectra of the simulated vertical air velocity. The comparison of the microphysical broadening provides another evaluative measure of the ice properties in the simulation. To accurately retrieve dissipation rates as well as each broadening term from the observations, we suggest a few modifications to previously presented techniques. First, we show that the inertial subrange spectrum filtered with the radar sampling volume is a better underlying model than the unfiltered −5/3 law for the retrieval of the dissipation rate from the power spectra of the mean Doppler velocity. Second, we demonstrate that it is important to filter out turbulence and remove the layer-mean reflectivity-weighted mean fall speed from the observed mean Doppler velocity to avoid overestimation of shear broadening. Finally, we provide a method to quantify the uncertainty in the retrieved dissipation rates, which eventually propagates to the uncertainty in the microphysical broadening.

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