Melting Layer Attenuation at Ka‐ and W‐Bands as Derived From Multifrequency Radar Doppler Spectra Observations

Li, Haoran; Moisseev, Dmitri

doi:10.1029/2019jd030316

Cited by 41 publications

(55 citation statements)

References 68 publications

(125 reference statements)

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“…Therefore, relatively large aggregates are prevalent snow types close to the ML, and are better represented by DWR(X,Ka) than DWR(Ka,W) (see the comparison by Barrett et al, 2019). The use of lower radar frequency (X-and Kabands) avoids estimating the non-neglectable W-band attenuation caused by ML as well as supercooled liquid water (Li and Moisseev, 2019). Therefore, the potential link between FR and simulated Doppler radar measurements at X-and Ka bands was accessed, with the utilization of in-situ snowfall observations from BAECC to the winters of 2014-2018.…”

Section: Diagnosing Snowflake Rime Mass Fractionmentioning

confidence: 99%

“…As Ka-band reflectivity can be significantly affected by the attenuation from ML, rain as well as a wet radome (Li and Moisseev, 2019). To mitigate this, the relative calibration was made at cloud top where the Rayleigh assumption can apply at Ka-and X-bands.…”

Section: Ka-band Ldr and Reflectivitymentioning

confidence: 99%

“…W-band reflectivity can be heavily affected by a wet radome, rain, ML, supercooled liquid water and gaseous attenuation (Kneifel et al, 2015;Li and Moisseev, 2019). Such attenuation coupled with precipitation microphysical processes as well as the change of particle scattering regimes can modulate the W-band reflectivity profiles.…”

Section: W-band Reflectivitymentioning

confidence: 99%

See 2 more Smart Citations

Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

Li¹,

Tiira²,

Lerber³

et al. 2020

Preprint

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Abstract. In stratiform rainfall, the melting layer is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the melting layer and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured melting layer properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide an additional constraint on the retrieval of ice cloud microphysical properties, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to devise a method for classifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. In the second part, this classification is used in combination with multi-frequency and dual-polarization radar observations to investigate the impact of precipitation intensity, aggregation, riming, and dendritic growth on melting layer properties. The radar-observed melting layer characteristics show strong dependence on precipitation intensity as well as detectable differences between unrimed and rimed snow. This study is based on the data collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment, that took place in 2014 in Hyytiala, Finland.

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Section: Diagnosing Snowflake Rime Mass Fractionmentioning

confidence: 99%

Section: Ka-band Ldr and Reflectivitymentioning

confidence: 99%

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Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

Li¹,

Tiira²,

Lerber³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Additional constraints on e.g. the assumed PSD or terminal velocity-size relation used in a microphysics scheme can be provided by multi-frequency Doppler spectra (Li and Moisseev, 2019;Kneifel et al, 2016). Finally, the passive observations add information on temperature and humidity profile as well as on vertically integrated liquid water and ice content (Kneifel et al, 2010).…”

Section: Ground-based Perspectivementioning

confidence: 99%

PAMTRA 1.0: A Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Mech¹,

Maahn²,

Kneifel³

et al. 2020

Preprint

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Abstract. Forward models are a key tool to generate synthetic observations given the knowledge of the atmospheric state. In this way they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud resolving models (CRMs). Herein, CRMs profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for up- and downward looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing up- and down-welling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications, interfaces to many different formats of in- and output type, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh--Gans Approximation (SSRGA) both for active and passive applications which becomes especially important for the investigation of frozen hydrometeors.

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“…A method to address this challenge is described in (Li et al, 2019) and it will be used for the EarthCare studies in the future.…”

Section: Satellite Data Validationmentioning

confidence: 99%

Integrative and comprehensive Understanding on Polar Environments (iCUPE): the concept and initial results

Petäj̈ä¹,

Duplissy²,

Tabakova³

et al. 2020

Preprint

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The role of polar regions increases in terms of megatrends such as globalization, new transport routes, demography and use of natural resources consequent effects of regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project "iCUPE -integrative and Comprehensive Understanding on Polar Environments" to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining 55 in situ observations, satellite remote sensing Earth Observations (EO) and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns and satellites to deliver data products, metrics and indicators to the stakeholders concerning the environmental status, availability and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and provision of novel data in atmospheric pollution, local sources and transboundary transport, characterization of arctic surfaces and their changes, assessment of concentrations and impacts 60 of heavy metals and persistent organic pollutants and their cycling, quantification of emissions from natural resource extraction and validation and optimization of satellite Earth Observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of integration of comprehensive in situ observations, satellite remote sensing and multiscale modeling in the Arctic context. 65

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Melting Layer Attenuation at Ka‐ and W‐Bands as Derived From Multifrequency Radar Doppler Spectra Observations

Cited by 41 publications

References 68 publications

Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

PAMTRA 1.0: A Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Integrative and comprehensive Understanding on Polar Environments (iCUPE): the concept and initial results

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