Why Mie?

Kollias, Pavlos; Albrecht, Bruce A.; Marks, Frank D.

doi:10.1175/bams-83-10-1471

Cited by 73 publications

(22 citation statements)

References 35 publications

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“…7). A similar feature occurs at 94 GHz for a diameter of 1.65 mm and a corresponding fall speed of 5.8 m s −1 and has been the basis for a vertical wind retrieval technique as proposed by Kollias et al (2002) which has been implemented into an operational wind retrieval scheme by Giangrande et al (2010). Preliminary computations demonstrate that the first minimum in the 220 GHz Doppler spectrum can be detected for drizzle/light rain with D 0 > 0.23 mm, and for turbulence broadening lower than 0.2 m s −1 , thus extending the range of applicability beyond that of the 94 GHz vertical wind technique.…”

Section: Boundary Layer Cloud Profilingmentioning

confidence: 75%

“…When this approximation is no longer valid (usually referred to as the "Mie regime") backscattering cross sections do not monotonically increase with the sixth power of the particle diameter, rather they exhibit an oscillatory behaviour with minima and maxima corresponding to resonant sizes (Kollias et al, 2002). Lhermitte (1990) provides a comprehensive review of radar reflectivity, Doppler spectra and absorption coefficients for ice and water spherical particles in the millimetre-wavelength domain.…”

Section: Mie and Non-spherical Backscattering Effectsmentioning

confidence: 99%

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G band atmospheric radars: new frontiers in cloud physics

et al. 2014

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Abstract. Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals.The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

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Section: Boundary Layer Cloud Profilingmentioning

confidence: 75%

Section: Mie and Non-spherical Backscattering Effectsmentioning

confidence: 99%

G band atmospheric radars: new frontiers in cloud physics

et al. 2014

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“…In the Mie scattering regime, the backscattering cross section as a function of the raindrop diameter oscillates due to resonant electromagnetic multipoles effects. Under precipitating conditions at 94 GHz, these oscillations are apparent in the observed Doppler spectrum and can be used as reference points for the retrieval of the vertical air motion (w air ) and subsequently the PSD [Lhermitte, 1988;Kollias et al, 2002;Giangrande et al, 2010]. Finally, another example where the deconvolution of the microphysical and dynamical effects is assisted by the observations is the case of bimodal (well separated peaks) Doppler spectra, where one of the spectral peaks corresponds to liquid cloud droplets and the other to either drizzle or ice particles.…”

Section: Introductionmentioning

confidence: 99%

Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications

et al. 2011

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[1] Several aspects of spectral broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloud-scale observations of microphysics and dynamics are essential to guide and evaluate corresponding modeling efforts. Profiling, millimeter-wavelength (cloud) radars can provide such observations. In particular, the first three moments of the recorded cloud radar Doppler spectra, the radar reflectivity, mean Doppler velocity, and spectrum width, are often used to retrieve cloud microphysical and dynamical properties. Such retrievals are subject to errors introduced by the assumptions made in the inversion process. Here, we introduce two additional morphological parameters of the radar Doppler spectrum, the skewness and kurtosis, in an effort to reduce the retrieval uncertainties. A forward model that emulates observed radar Doppler spectra is constructed and used to investigate these relationships. General, analytical relationships that relate the five radar observables to cloud and drizzle microphysical parameters and cloud turbulence are presented. The relationships are valid for cloud-only, cloud mixed with drizzle, and drizzle-only particles in the radar sampling volume and provide a seamless link between observations and cloud microphysics and dynamics. The sensitivity of the five observed parameters to the radar operational parameters such as signal-to-noise ratio and Doppler spectra velocity resolution are presented. The predicted values of the five observed radar parameters agree well with the output of the forward model. The novel use of the skewness of the radar Doppler spectrum as an early qualitative predictor of drizzle onset in clouds is introduced. It is found that skewness is a parameter very sensitive to early drizzle generation. In addition, the significance of the five parameters of the cloud radar Doppler spectrum for constraining drizzle microphysical retrievals is discussed.

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“…One important aspect is related to the space-time variation of the microstructure of precipitation. The polarimetric variables measured by IDRA (e.g., Seliga and Bringi 1976;Gorgucci et al 2008), vertically pointing Doppler radar (e.g., Hauser andAmayenc 1981, 1983;Kollias et al 2002), and a combination thereof (Unal and Moisseev 2004;Moisseev et al 2006;Spek et al 2008;Unal 2009) can be used to obtain information on the microphysics of precipitation with unprecedented extent and resolution.…”

Section: Discussionmentioning

confidence: 99%

Precipitation Measurement at CESAR, the Netherlands

Leijnse

Uijlenhoet

Beek

et al. 2010

Journal of Hydrometeorology

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The Cabauw Experimental Site for Atmospheric Research (CESAR) observatory hosts a unique collection of instruments related to precipitation measurement. The data collected by these instruments are stored in a database that is freely accessible through a Web interface. The instruments present at the CESAR site include three disdrometers (two on the ground and one at 200 m above ground level), a dense network of rain gauges, three profiling radars (1.3, 3.3, and 35 GHz), and an X-band Doppler polarimetric scanning radar. In addition to these instruments, operational weather radar data from the nearby (;25 km) De Bilt C-band Doppler radar are also available. The richness of the datasets available is illustrated for a rainfall event, where the synergy of the different instruments provides insight into precipitation at multiple spatial and temporal scales. These datasets, which are freely available to the scientific community, can contribute greatly to our understanding of precipitation-related atmospheric and hydrologic processes.

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Why Mie?

Cited by 73 publications

References 35 publications

G band atmospheric radars: new frontiers in cloud physics

G band atmospheric radars: new frontiers in cloud physics

Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications

Precipitation Measurement at CESAR, the Netherlands

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