Assimilation of Dual-Polarization Radar Observations in Mixed- and Ice-Phase Regions of Convective Storms: Information Content and Forward Model Errors

Abstract Dual-polarization Doppler radar has proven useful for the estimation of hydrometeor content and the classification of hydrometeor type. Recent studies have leveraged dual-polarization-specific information to produce improved assimilated cloud and precipitation fields from the warm rain (above freezing) portion of deep convective storms. While the strengths of dual-polarization radar observations have been conclusively shown for rain and hail hydrometeors, it is less clear how much information is provided in mixed-phase and ice-only regions. In this paper, a Markov chain Monte Carlo (MCMC) algorithm is used to examine the information content of dual-polarization-specific variables in the ice-phase region of a convective storm. Results are used to quantify how much information is added by specific differential phase and radar correlation coefficient, as well as how this information is degraded when the assumed particle size distribution and particle density are allowed to vary. It is found that dual-polarization-specific observations (Kdp and ρhv) provide significant information on rimed ice content, and moderate information on pristine ice, especially where snow mass is more than 10% of the total volume hydrometeor mass. There is a significant reduction in information content for rain and a near-complete loss of information for graupel–hail and snow when the particle size distribution and ice particle densities are not well known, and there are systematic changes in radar information gain and loss with changes in hydrometeor mass. The results highlight the need for a thorough exploration of forward model sensitivities prior to performing radar data assimilation.

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On the Information Content of Coarse Data with Respect to the Particle Size Distribution of Complex Granular Media: Rationale Approach and Testing

Entropy ◽

10.3390/e21060601 ◽

2019 ◽

Vol 21 (6) ◽

pp. 601 ◽

Cited By ~ 1

Author(s):

Carlos García-Gutiérrez ◽

Miguel Ángel Martín ◽

Yakov Pachepsky

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Information Content ◽

Granular Media ◽

Initial Conditions ◽

Physical Property ◽

Conceptual Approach ◽

Grain Sizes ◽

Andersen Model

The particle size distribution (PSD) of complex granular media is seen as a mathematical measure supported in the interval of grain sizes. A physical property characterizing granular products used in the Andreasen and Andersen model of 1930 is re-interpreted in Information Entropy terms leading to a differential information equation as a conceptual approach for the PSD. Under this approach, measured data which give a coarse description of the distribution may be seen as initial conditions for the proposed equation. A solution of the equation agrees with a selfsimilar measure directly postulated as a PSD model by Martín and Taguas almost 80 years later, thus both models appear to be linked. A variant of this last model, together with detailed soil PSD data of 70 soils are used to study the information content of limited experimental data formed by triplets and its ability in the PSD reconstruction. Results indicate that the information contained in certain soil triplets is sufficient to rebuild the whole PSD: for each soil sample tested there is always at least a triplet that contains enough information to simulate the whole distribution.

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Ground Observation of Tephra Particles: On the Use of Weather Radar for Estimating Volcanic Ash Distribution

Journal of Disaster Research ◽

10.20965/jdr.2019.p0151 ◽

2019 ◽

Vol 14 (1) ◽

pp. 151-159 ◽

Cited By ~ 1

Author(s):

Ratih Indri Hapsari ◽

Masahiro Iida ◽

Masahide Muranishi ◽

Mariko Ogawa ◽

Magfira Syarifuddin ◽

...

Keyword(s):

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Volcanic Ash ◽

Continuous Distribution ◽

Practical Method ◽

Radar Observations ◽

Analytical Results ◽

X Band ◽

Deposit Weight

This paper reports a preliminary attempt to determine volcanic ash particle size distribution using the video drop size detector (VDSD) for estimating volcanic ash amount with X-band radar. The VDSD records an image showing the size and number of particles falling into the aperture by a charge coupled device camera. Size distribution spectra of a range of particles from fine ash to small lapilli were derived in discrete form from the VDSD observation. The parameterization of the particle size distribution following Gamma function was done using volcanic ash of eruptions at the Sakurajima Volcano between December 13–21, 2014. Three Gamma distribution parameters were determined analytically. The analytical results revealed a continuous distribution of particles characterized by shape, intercept, and slope. The distribution was used to determine volcanic mass concentration, ground deposit weight, and reflectivity. Verification of these results with X-band radar observations showed that the reflectivity obtained from analytical results is similar to that from radar observation. However, the ground deposit weight from analysis was overestimated, compared with the real weight of ash deposit on the ground. The algorithm proposed in this study is expected to provide a practical method for estimating ash distribution in the aftermath of a volcanic eruption using radar-reflectivity for cases where direct measurement at the location is not possible. An overview of the algorithm for volcanic ash retrieval from X-band radar observations is also presented.

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