Radar Observations and Simulation of the Melting Layer of Precipitation

Klaassen, Wim

doi:10.1175/1520-0469(1988)045<3741:roasot>2.0.co;2

Cited by 145 publications

(107 citation statements)

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“…The question of deciding whether wet snow is modeled better by water inclusions in a dry snow (i.e., ice plus air) matrix or by dry snow in water has been on the table for a while, and there is no definite answer yet. However, there is a growing consensus, supported also by the comparison of radar measurements with theoretical predictions [Klaassen, 1988], that wet snow is better this will be the model we will adopt in this work.…”

Section: Modeling the Melting Layermentioning

confidence: 97%

“…(dp,•/dT)lr=To • 0.332 [Zhang, 1994]. We have also assumed with Klaassen [1988] As said, the shape of the melting hydrometeors can be extremely complex; as often happens when a model has to be developed, we have to simplify the reality and assume a shape that can be analytically treatable. In particular, at the top of the melting layer the ellipticity is supposed to be maximum (i.e., the particles are more distorted), and it decreases to the standard value for rain [Oguchi, 1983] …”

Section: Modeling the Melting Layermentioning

confidence: 99%

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An anisotropic model of the melting layer

D’Amico¹,

Holt²,

Capsoni³

1998

Radio Science

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Abstract. There is current interest in the effects of the melting layer on the propagation of electromagnetic waves, in the radar, remote sensing, and telecommunication communities. In this work a microphysical model of the melting layer is presented for the prediction of the electromagnetic behavior of this important region of the atmosphere. The model is anisotropic to be able to take into account the depolarization effects. The model is also tested against Doppler, duM-frequency measurements, and duM-polarization measurements collected by modern multiparameter radar systems.

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Section: Modeling the Melting Layermentioning

confidence: 97%

Section: Modeling the Melting Layermentioning

confidence: 99%

An anisotropic model of the melting layer

D’Amico¹,

Holt²,

Capsoni³

1998

Radio Science

View full text Add to dashboard Cite

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“…The algorithm works by exploiting the characteristic shape of a reflectivity profile containing a bright band. The algorithm is adapted from one described in Klaassen (1988). If no melting layer is found to exist, the profile is labeled as convective.…”

Section: Algorithm To Estimate Dsdmentioning

confidence: 99%

“…The other models are in between. The value for the snow density is truncated at 0.9 and 0.005 g cm Ϫ3 as suggested by Klaassen (1988). Battaglia et al (2003) provides a parameterization for the velocity of a melting particle derived from Mitra et al's (1990) experimental work and shows that the output of the melting layer model is not very sensitive to the parameterization for the fall velocity.…”

Section: A Melting Layer Thermodynamic Modelmentioning

confidence: 99%

Validation and Development of Melting Layer Models Using Constraints by Active/Passive Microwave Observations of Rain and the Wind-Roughened Ocean Surface

Brown

Ruf

2007

Journal of Atmospheric and Oceanic Technology

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A physically based method is developed to estimate the microphysical structure of the melting layer in stratiform rain using airborne observations by a dual-frequency radar and a 10.7-GHz radiometer. The method employs a nonlinear optimal estimation approach to find two parameters of the gamma drop size distribution (DSD) at each radar range gate from the Ku/Ka-band reflectivities. The DSD profile is used to determine the atmospheric absorption/extinction profile, which enables the surface contribution to the measured brightness temperature to be estimated. The surface wind speed is estimated from the surface emissivity by inverting the forward model, which relates the two. Retrievals in stratiform precipitation require a model to describe the thermodynamic and electromagnetic properties of melting hydrometeors. The melting layer can contribute a majority of the total atmospheric absorption, making it a key component for accurate retrievals in stratiform rain. Several melting layer models were evaluated based on their fit to the dual-frequency reflectivity measurements in the melting layer. A candidate model is selected and tuned to match the radar measurements. The melting layer model is then incorporated into the full forward model for the brightness temperature observed by the radiometer. The surface wind speed assumed in the forward model is forced by the radiometer observations. If the actual surface wind speed is known, this approach provides a powerful constraint on the possible melting layer model. A case study is presented from an airborne campaign over areas of precipitation off the coast of Vancouver Island, British Columbia, Canada. The estimated wind speeds are found to be uncorrelated with the reflectivity and their average value is within 1 m s Ϫ1 of that retrieved in a clear area adjacent to the rain.

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“…Microwave radiation is sensitive to the presence of liquid water on ice-phase precipitation (e.g., Klassen, 1988), due, primarily, to the large difference in the dielectric constants of the two materials at microwave frequencies. However, the relationship between the early stages of melting and incident microwave radiation has not been well described in the literature.…”

Section: Introductionmentioning

confidence: 99%

The microwave properties of simulated melting precipitation particles: sensitivity to initial melting

2016

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Abstract.A simplified approach is presented for assessing the microwave response to the initial melting of realistically shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM), a heuristic melting simulation for ice-phase precipitation particles of any shape or size (SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass), and (2) the computation of the singleparticle microwave scattering and extinction properties of these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, and 94.0 GHz for radar applications and 89, 165.0, and 183.31 GHz for radiometer applications. These selected frequencies are consistent with current microwave remotesensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

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Radar Observations and Simulation of the Melting Layer of Precipitation

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Cited by 145 publications

References 0 publications

An anisotropic model of the melting layer

An anisotropic model of the melting layer

Validation and Development of Melting Layer Models Using Constraints by Active/Passive Microwave Observations of Rain and the Wind-Roughened Ocean Surface

The microwave properties of simulated melting precipitation particles: sensitivity to initial melting

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