A general database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths

Eriksson, Patrick; Ekelund, Robin; Mendrok, Jana; Brath, Manfred; Hodnebrog, Øivind; Buehler, Stefan A.

doi:10.5194/essd-2018-23

Cited by 2 publications

(4 citation statements)

References 40 publications

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“…Notice that we include some of the single crystals (p‐13, p‐29, and p‐44) from K16 (dark gray upward triangles) to demonstrate that the measured values toward the upper left part of the diagram could be explained by single crystals in random orientation. Some of the single crystals in Eriksson et al () also occupy this area (not shown here). The physical aggregate models (upper left panel) seem to propagate to the upper middle part of the diagram as the size increases, and showing a maximum in DFR Ka / W at 7–9 dB.…”

Section: Resultsmentioning

confidence: 63%

“…"> 7.J16: Johnson et al () (available from the Author): melted aggregates of dendrites with melted mass fraction 0% (J16a), 10% (J16b), and 70% (J16c) E18: Eriksson et al () (available at ARTS database ()): aggregates of hexagonal columns with 100 (E18a) and 350 (E18b)‐μm‐sized monomers aggregates of hexagonal plates with 100 (E18c) and 350 (E18d)‐μm‐sized monomers aggregates of hexagonal blocks with 100 (E18e) and 350 (E18f)‐μm‐sized monomers 9.T18: This study (available at FMI ()): fractals with f d = 1.6 (T18a), 2.0 (T18b), 2.4 (T18c), and 2.8 (T18d)…”

Section: Microphysical Models Of Snowmentioning

confidence: 99%

“…E18: Eriksson et al () (available at ARTS database ()): aggregates of hexagonal columns with 100 (E18a) and 350 (E18b)‐μm‐sized monomers aggregates of hexagonal plates with 100 (E18c) and 350 (E18d)‐μm‐sized monomers aggregates of hexagonal blocks with 100 (E18e) and 350 (E18f)‐μm‐sized monomers …”

Section: Microphysical Models Of Snowmentioning

confidence: 99%

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Validation of Microphysical Snow Models Using In Situ, Multifrequency, and Dual‐Polarization Radar Measurements in Finland

Tyynelä

Lerber

2019

JGR Atmospheres

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As complex forward models for snow have become common in radar‐based retrievals, there is a demand to validate these models in different environments. In this study, we perform a qualitative, general validation for nine different snow models that have been published and are available to users. The chosen models span a variety of different snow types, such as aggregates, rimed aggregates, melted aggregates, graupel, and single crystals, mainly because these particles are commonly observed in the Finnish climate. Fitted power law formulas for mass, fall velocity, aspect ratio, and area ratio are compared between the models and 5‐year winter measurements in the Hyytiälä forestry field station in Finland. We also compare the backscattering properties of the models to triple‐frequency dual‐polarization radar measurements during the Biogenic Aerosols Effects on Clouds and Climate campaign in 2014. We find that the denser models, regardless of the exact shapes, fit the in situ measurements best due to the prevalence of rime in the falling snow. However, when comparing also to the triple‐frequency radar measurements at X, Ka, and W bands, and the linear depolarization ratio at Ka band, the physical snow models fit overall better than the empirical ones.

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Section: Resultsmentioning

confidence: 63%

Section: Microphysical Models Of Snowmentioning

confidence: 99%

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Validation of Microphysical Snow Models Using In Situ, Multifrequency, and Dual‐Polarization Radar Measurements in Finland

Tyynelä

Lerber

2019

JGR Atmospheres

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“…In the RT for MW, a different Table 9. Modification introduced in the radiative transfer model settings for microwave instruments in terms of particle shape (Scattering type) from database ARTS (Eriksson et al, 2018).…”

mentioning

confidence: 99%

Synergistic approach of hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework

Villeneuve

Chambon

Fourrié

2023

Preprint

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Abstract. In cloudy situations, infrared and microwave observations are complementary, with infrared observations being sensitive to the small cloud droplets and ice particles and microwave observations sensitive to precipitation. This complementarity can lead to fruitful synergies in precipitation science (e.g. Kidd and Levizzani, 2022). However, several sources of errors do exist in the treatment of infrared and microwave data that could prevent such synergy. This paper studies several of these sources to estimate their impact on retrievals. To do so, simulations from the radiative transfer model RTTOV v13 are used to build simulated observations. Indeed, we make use of a fully simulated framework to explain the impacts of the identified errors. A combination of infrared and microwave frequencies is built within a Bayesian inversion framework. Synergy is studied using different experiments: (i) with several sources of errors eliminated; (ii) with only one source of errors considered at a time; (iii) with all sources of errors together. The derived retrievals of frozen hydrometeors for each experiment are examined in a statistical study of fifteen days in summer and fifteen days in winter over the Atlantic ocean. One of the main outcomes of the study is that the combination of infrared and microwave frequencies takes advantage of both spectral range strengths leading to accurate retrievals. Each source of error has more or less impact depending on the type of hydrometeor. Another outcome of the study is that even though the errors may decrease the magnitude of benefits generated by the combination of infrared and microwave frequencies, in all cases explored, their combination remains beneficial.

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A general database of hydrometeor single scattering properties at microwave and sub-millimetre wavelengths

Cited by 2 publications

References 40 publications

Validation of Microphysical Snow Models Using In Situ, Multifrequency, and Dual‐Polarization Radar Measurements in Finland

Validation of Microphysical Snow Models Using In Situ, Multifrequency, and Dual‐Polarization Radar Measurements in Finland

Synergistic approach of hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework

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