scholarly journals Coincident In-situ and Triple-Frequency Radar Airborne Observations in the Arctic

2021 ◽  
Author(s):  
Cuong M. Nguyen ◽  
Mengistu Wolde ◽  
Alessandro Battaglia ◽  
Leonid Nichman ◽  
Natalia Bliankinshtein ◽  
...  
Keyword(s):  
National Research Council ◽  
Characteristic Size ◽  
The Arctic ◽  
Dual Frequency ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
W Band ◽  
Modelling Studies ◽  
Frequency Ratios

Abstract. This paper describes X-Ka-W-band airborne radar observations and almost perfectly co-located in situ microphysical measurements on board the National Research Council Canada (NRC) Convair-580 aircraft from the Radar Snow Experiment (RadSnowExp). Over 12 hours of flight data with more than 3.4 hours in non-Rayleigh regions for at least one of the radar frequencies provide a unique opportunity for studying the relationship between cloud microphysical properties and radar dual-frequency ratios (DFR). The results from this study are consistent with the main findings of previous modelling studies with specific regions of the DFR plane associated with unique scattering properties of different ice habits, especially in riming conditions. Moreover, the datasets could be used to produce look-up-tables for retrieving cloud bulk density and characteristic size.

scholarly journals Triple-frequency radar retrieval of microphysical properties of snow

2021 ◽  
Vol 14 (11) ◽  
pp. 7243-7254
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Mean Square Errors

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.

Triple-Frequency Radar Reflectivity Signatures of Snow: Observations and Comparisons with Theoretical Ice Particle Scattering Models

2014 ◽  
Vol 53 (4) ◽  
pp. 1080-1098 ◽  
Author(s):  
Mark S. Kulie ◽  
Michael J. Hiley ◽  
Ralf Bennartz ◽  
Stefan Kneifel ◽  
Simone Tanelli
Keyword(s):  
Microwave Remote Sensing ◽  
Valuable Insight ◽  
Particle Scattering ◽  
Dual Frequency ◽  
Modeling Framework ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
W Band ◽  
Retrieval Algorithms ◽  
Wakasa Bay

AbstractAn observation-based study is presented that utilizes aircraft data from the 2003 Wakasa Bay Advanced Microwave Scanning Radiometer Precipitation Validation Campaign to assess recent advances in the modeling of microwave scattering properties of nonspherical ice particles in the atmosphere. Previous work has suggested that a triple-frequency (Ku–Ka–W band) reflectivity framework appears capable of identifying key microphysical properties of snow, potentially providing much-needed constraints on significant sources of uncertainty in current snowfall retrieval algorithms used for microwave remote sensing instruments. However, these results were based solely on a modeling framework. In contrast, this study considers the triple-frequency approach from an observational perspective using airborne radar observations from the Wakasa Bay field campaign. After accounting for several challenges with the observational dataset, such as beam mismatching and attenuation, observed dual-wavelength ratio results are presented that confirm both the utility of a multifrequency approach to snowfall retrieval and the validity of the unique signatures predicted by complex aggregate ice particle scattering models. This analysis provides valuable insight into the microphysics of frozen precipitation that can in turn be applied to more readily available single- and dual-frequency systems, providing guidance for future precipitation retrieval algorithms.

scholarly journals Triple frequency radar retrieval of microphysical properties of snow

2021 ◽  
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Ice Water

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterized by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment. During this campaign in-situ microphysical probes were mounted on the same airplane as the radars. This nearly perfectly collocated dataset of the remote and in-situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content and mean-mass-weighted diameters obtaining root-mean-square-error of 0.13 and 0.15, respectively for log10 IWC and log10 Dm. The retrieval of the degree of riming is more challenging and only the algorithm that uses Doppler information obtains results that are highly correlated with the in-situ data.

scholarly journals Retrieval of snowflake microphysical properties from multi-frequency radar observations

2018 ◽  
Author(s):  
Jussi Leinonen ◽  
Matthew D. Lebsock ◽  
Simone Tanelli ◽  
Ousmane O. Sy ◽  
Brenda Dolan ◽  
...  
Keyword(s):  
Single Frequency ◽  
Parameter Estimates ◽  
Dual Frequency ◽  
Snow Density ◽  
Radar Observations ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Multiple Frequencies ◽  
The Difference

Abstract. We have developed an algorithm that retrieves the microphysical properties of falling snow from multi-frequency radar observations. This work builds on previous studies that have indicated that three-frequency radars can provide information on snow density, potentially improving the accuracy of snow parameter estimates. The algorithm is based on a Bayesian framework, using lookup tables mapping the measurement space to the state space, which allows fast and robust retrieval. In the forward model, we calculate the radar reflectivities using recently published snow scattering databases. We demonstrate the algorithm using multi-frequency airborne radar observations from the OLYMPEX/RADEX field campaign, comparing the retrieval results to hydrometeor identification using ground-based polarimetric radar, and also to collocated in situ observations made using another aircraft. Using these data, we examine how the availability of multiple frequencies affects the retrieval accuracy, and test the sensitivity of the algorithm to the prior assumptions. The results suggest that multi-frequency radars are substantially better than single-frequency radars at retrieving snow microphysical properties. Meanwhile, triple-frequency radars can retrieve wider ranges of snow density than dual-frequency radars, and better locate regions of high-density snow such as graupel, although these benefits are relatively modest compared to the difference in retrieval performance between dual- and single-frequency radars.

scholarly journals Observational and Modeling Study of Ice Hydrometeor Radar Dual-Wavelength Ratios

2019 ◽  
Vol 58 (9) ◽  
pp. 2005-2017 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Maximilian Maahn ◽  
Gijs de Boer
Keyword(s):  
Rayleigh Scattering ◽  
Elevation Angle ◽  
Characteristic Size ◽  
Dual Wavelength ◽  
Spherical Particles ◽  
Nonspherical Particles ◽  
Dual Frequency ◽  
Weather Radars ◽  
W Band ◽  
Differential Reflectivity

AbstractThe influence of ice hydrometeor shape on the dual-wavelength ratio (DWR) of radar reflectivities at millimeter-wavelength frequencies is studied theoretically and on the basis of observations. Data from dual-frequency (Ka–W bands) radar show that, for vertically pointing measurements, DWR increasing trends with reflectivity Ze are very pronounced when Ka-band Ze is greater than about 0 dBZ and that DWR and Ze values are usually well correlated. This correlation is explained by strong relations between hydrometeor characteristic size and both of these radar variables. The observed DWR variability for a given level of reflectivity is as large as 8 dB, which is in part due to changes in mean hydrometeor shape as expressed in terms of the particle aspect ratio. Hydrometeors with a higher degree of nonsphericity exhibit lower DWR values when compared with quasi-spherical particles because of near-zenith reflectivity enhancements for particles outside the Rayleigh-scattering regime. When particle mass–size relations do not change significantly (e.g., for low-rime conditions), DWR can be used to differentiate between quasi-spherical and highly nonspherical hydrometeors because (for a given reflectivity value) DWR tends to increase as particles become more spherical. Another approach for differentiating among different degrees of nonsphericity for larger scatterers is based on analyzing DWR changes as a function of radar elevation angle. These changes are more pronounced for highly nonspherical particles and can exceed 10 dB. Measurements of snowfall spatiotemporally collocated with spaceborne CloudSat W-band radar and ground-based S-band operational weather radars also indicate that DWR values are generally smaller for ice hydrometeors with higher degrees of nonsphericity, which, for the same level of S-band reflectivity, exhibit greater differential reflectivity values.

scholarly journals How to estimate total differential attenuation due to hydrometeors with ground-based multi-frequency radars?

2020 ◽  
Author(s):  
Frédéric Tridon ◽  
Alessandro Battaglia ◽  
Stefan Kneifel
Keyword(s):  
Liquid Water ◽  
Microwave Radiometer ◽  
Particle Growth ◽  
Vertical Gradient ◽  
Liquid Droplets ◽  
Dual Frequency ◽  
Liquid Water Path ◽  
W Band ◽  
Frequency Ratios ◽  
Attenuation Corrected

Abstract. At millimeter wavelengths, attenuation by hydrometeors, such as liquid droplets or large snowflakes, is generally not negligible. When using multi-frequency ground-based radar measurements, it is common practice to use the Rayleigh targets at cloud top as a reference in order to derive attenuation-corrected reflectivities and meaningful dual-frequency ratios (DFR). By capitalizing on this idea, this study describes a new quality-controlled approach aiming at identifying regions of the cloud where particle growth is negligible. The core of the method is the identification of a Rayleigh plateau, i.e. a large enough region near cloud top where the vertical gradient of DFR remains small. By analyzing collocated Ka-W band radar and microwave radiometer (MWR) observations taken at two European sites under various meteorological conditions, it is shown how the resulting estimates of differential path-integrated attenuation (DeltaPIA) can be used to characterize hydrometeor properties. When the DeltaPIA is predominantly produced by cloud liquid droplets, this technique alone can provide accurate estimates of the liquid water path. When combined with MWR observations, this methodology paves the way towards profiling the cloud liquid water and/or quality flagging the MWR retrieval for rain/drizzle contamination and/or estimating the snow differential attenuation.

scholarly journals Microphysical properties of synoptic scale polar stratospheric clouds: in situ measurements of unexpectedly large HNO<sub>3</sub> containing particles in the Arctic vortex

2014 ◽  
Vol 14 (8) ◽  
pp. 12071-12120 ◽  
Author(s):  
S. Molleker ◽  
S. Borrmann ◽  
H. Schlager ◽  
B. Luo ◽  
W. Frey ◽  
...  
Keyword(s):  
Nitric Acid ◽  
Scattered Light ◽  
Stratospheric Ozone ◽  
The Arctic ◽  
Size Distributions ◽  
Synoptic Scale ◽  
Particle Composition ◽  
Mixing Ratios ◽  
Microphysical Properties

Abstract. In January 2010 and December 2011 synoptic scale PSC fields were probed during seven flights of the high altitude research aircraft M-55 Geophysica within the RECONCILE (Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interaction.) and the ESSenCe (ESSenCe: ESA Sounder Campaign) projects. Particle size distributions in a diameter range between 0.46 μm and 40 μm were recorded simultaneously by up to four different optical in situ instruments. Three of these particle instruments are based on the detection of forward scattered light by single particles. The fourth instrument is a grey scale optical array imaging probe. Optical particle diameters of up to 35 μm were detected with particle number densities and total particle volumes exceeding previous Arctic measurements. Also, gas phase and particle bound NOy were measured, as well as water vapor concentrations, and other variables. Two remote sensing particle instruments, the Miniature Aerosol Lidar (MAL) and the backscatter sonde (MAS, Multiwavelenght Aerosol Scatterometer) showed the synoptic scale of the encountered PSCs. The particle mode below 2 μm in size diameter has been identified as supercooled ternary solution droplets (STS). The PSC particles in the size range above 2 μm in diameter are considered to consist of nitric acid hydrates or ice, and the particles' high HNO3 content was confirmed by the NOy instrument. Assuming a particle composition of nitric acid trihydrate (NAT), the optically measured size distributions result in particle-phase HNO3 mixing ratios exceeding available stratospheric values. In particular, with respect to the denitrification by sedimentation of large HNO3-contaning particles, generally considered as NAT, our new measurements raise questions concerning composition, shape and nucleation pathways. Measurement uncertainties are discussed concerning probable overestimations of measured particle sizes and volumes. We hypothesize that either a strong asphericity or the particle composition (e.g. water-ice coated with NAT) could explain our observations.

In-situ airborne observations of the microphysical properties of the Arctic tropospheric aerosol during late spring and summer

Tellus B ◽  
2008 ◽  
Vol 60 (3) ◽  
Author(s):  
Ann-Christine Engvall ◽  
Radovan Krejci ◽  
Johan Ström ◽  
Andreas Minikin ◽  
Renate Treffeisen ◽  
...  
Keyword(s):  
Late Spring ◽  
The Arctic ◽  
Microphysical Properties ◽  
Tropospheric Aerosol

scholarly journals Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars

2020 ◽  
Vol 13 (9) ◽  
pp. 5065-5085
Author(s):  
Frédéric Tridon ◽  
Alessandro Battaglia ◽  
Stefan Kneifel
Keyword(s):  
Liquid Water ◽  
Microwave Radiometer ◽  
Particle Growth ◽  
Vertical Gradient ◽  
Liquid Droplets ◽  
Dual Frequency ◽  
Liquid Water Path ◽  
W Band ◽  
Frequency Ratios ◽  
Mixed Phase Clouds

Abstract. At millimeter wavelengths, attenuation by hydrometeors, such as liquid droplets or large snowflakes, is generally not negligible. When using multifrequency ground-based radar measurements, it is common practice to use the Rayleigh targets at cloud top as a reference in order to derive attenuation-corrected reflectivities and meaningful dual-frequency ratios (DFRs). By capitalizing on this idea, this study describes a new quality-controlled approach that aims at identifying regions of cloud where particle growth is negligible. The core of the method is the identification of a “Rayleigh plateau”, i.e., a large enough region near cloud top where the vertical gradient of DFR remains small. By analyzing co-located Ka–W band radar and microwave radiometer (MWR) observations taken at two European sites under various meteorological conditions, it is shown how the resulting estimates of differential path-integrated attenuation (ΔPIA) can be used to characterize hydrometeor properties. When the ΔPIA is predominantly produced by cloud liquid droplets, this technique alone can provide accurate estimates of the liquid water path. When combined with MWR observations, this methodology paves the way towards profiling the cloud liquid water, quality-flagging the MWR retrieval for rain and drizzle contamination, and/or estimating the snow differential attenuation.

scholarly journals Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset

2021 ◽  
Vol 13 (12) ◽  
pp. 2264
Author(s):  
F. Joseph Turk ◽  
Sarah E. Ringerud ◽  
Andrea Camplani ◽  
Daniele Casella ◽  
Randy J. Chase ◽  
...  
Keyword(s):  
Heavy Precipitation ◽  
Cold Season ◽  
Dual Frequency ◽  
Light Rain ◽  
Triple Frequency ◽  
W Band ◽  
Precipitation Measurement ◽  
Precipitation Structure ◽  
Global Precipitation Measurement ◽  
Global Precipitation

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects.

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