scholarly journals High-Resolution Vertical Profiles of X-Band Polarimetric Radar Observables during Snowfall in the Swiss Alps

2013 ◽  
Vol 52 (2) ◽  
pp. 378-394 ◽  
Author(s):  
Marc Schneebeli ◽  
Nicholas Dawes ◽  
Michael Lehning ◽  
Alexis Berne
Keyword(s):  
Water Vapor ◽  
High Water ◽  
Snow Accumulation ◽  
Swiss Alps ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
High Accumulation ◽  
Melting Layer ◽  
Mountainous Regions ◽  
X Band

AbstractAn X-band polarimetric radar was deployed in the eastern Swiss Alps at an altitude of 2133 m. Radar measurements were complemented with several weather stations deployed in an altitude range from 1500 to 3100 m as well as with a fixed GPS ground station that was used to infer integrated water vapor estimates. Around 8000 vertical profiles of polarimetric radar observables above the melting layer collected during two months are analyzed. First, the behavior of the mean profiles of reflectivity at horizontal polarization Zh, differential reflectivity Zdr, copolar cross correlation ρhv, and specific differential phase shift Kdp are interpreted from a microphysical point of view. It is shown that the whole evolution of snowflakes, from pristine crystals at temperatures around −30°C to dendritic crystals around −15°C, to large aggregates around 0°C, is well captured by the polarimetric radar variables. In a second step, the profiles are analyzed as functions of high and low water vapor and snow accumulation conditions. It is found that the vertical profiles of polarimetric radar variables have distinct features in low versus high water vapor conditions. High water vapor conditions appear to favor the occurrence of crystal aggregates at high altitudes/low temperatures. It is shown with a hydrometeor identification scheme that graupel-like particles are found to be dominant right above the melting layer for snow events with high accumulation intensities. The present analyses show that measurements from X-band dual-polarization radar can be useful to characterize the dominant microphysical processes during precipitation in mountainous regions.

scholarly journals Characterisation of the melting layer variability in an Alpine valley based on polarimetric X-band radar scans

2018 ◽  
Author(s):  
Floor van den Heuvel ◽  
Marco Gabella ◽  
Urs Germann ◽  
Alexis Berne
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Swiss Alps ◽  
Spatial And Temporal Variability ◽  
Polarimetric Radar ◽  
Melting Layer ◽  
Alpine Valley ◽  
Space And Time ◽  
X Band ◽  
Profile Correction

Abstract. The melting layer designates the transition region from solid to liquid precipitation, and is a typical feature of the vertical structure of stratiform precipitation. As it is characterised by a well-known signature in polarimetric radar variables, it can be identified by automatic detection algorithms. Though often assumed to be uniform in space and time for applications such as vertical profile correction, the spatial variability of the melting layer remains poorly documented. This work undertakes to characterise and quantify the spatial and temporal variability of the melting layer using a method based on the Fourier transform, which is applied to high resolution X-band polarimetric radar data from two measurement campaigns in Switzerland. It is first demonstrated that the proposed method can accurately and concisely describe the spatial variability of the melting layer and may therefore be used as a tool for comparison. The method is then used to characterise the melting layer variability in summer precipitation on the relatively flat Swiss plateau and in winter precipitation in a large inner Alpine valley (the Rhone valley in the Swiss Alps). Results indicate a higher contribution of smaller spatial scales to the total melting layer variability in the case of the Alpine environment. The same method is also applied on data from vertical scans in order to study the temporal variability of the melting layer. The variability in space and time is then compared to investigate the spatio-temporal coherence of the melting layer variability in the two study areas, which was found to be more consistent with the assumption of pure advection for the case of the plateau.

scholarly journals Characterisation of the melting layer variability in an Alpine valley based on polarimetric X-band radar scans

2018 ◽  
Vol 11 (9) ◽  
pp. 5181-5198 ◽  
Author(s):  
Floor van den Heuvel ◽  
Marco Gabella ◽  
Urs Germann ◽  
Alexis Berne
Keyword(s):  
Spatial Variability ◽  
Temporal Variability ◽  
Swiss Alps ◽  
Spatial And Temporal Variability ◽  
Polarimetric Radar ◽  
Melting Layer ◽  
Alpine Valley ◽  
Space And Time ◽  
X Band ◽  
Profile Correction

Abstract. The melting layer designates the transition region from solid to liquid precipitation, and is a typical feature of the vertical structure of stratiform precipitation. As it is characterised by a well-known signature in polarimetric radar variables, it can be identified by automatic detection algorithms. Though often assumed to be uniform in space and time for applications such as vertical profile correction, the spatial variability of the melting layer remains poorly documented. This work aims to characterise and quantify the spatial and temporal variability of the melting layer using a method based on the Fourier transform, which is applied to high-resolution X-band polarimetric radar data from two measurement campaigns in Switzerland. It is first demonstrated that the proposed method can accurately and concisely describe the spatial variability of the melting layer and may therefore be used as a tool for comparison. The method is then used to characterise the melting layer variability in summer precipitation on the relatively flat Swiss Plateau and in winter precipitation in a large inner Alpine valley (the Rhone valley in the Swiss Alps). Results indicate a higher contribution of smaller spatial scales to the total melting layer variability in the case of the Alpine environment. The same method is also applied to data from vertical scans in order to study the temporal variability of the melting layer. The variability in space and time is then compared to investigate the spatio-temporal coherence of the melting layer variability in the two study areas, which was found to be more consistent with the assumption of pure advection for the case of the plateau.

scholarly journals Polarimetric Signatures above the Melting Layer in Winter Storms: An Observational and Modeling Study

2013 ◽  
Vol 52 (3) ◽  
pp. 682-700 ◽  
Author(s):  
Jelena Andrić ◽  
Matthew R. Kumjian ◽  
Dušan S. Zrnić ◽  
Jerry M. Straka ◽  
Valery M. Melnikov
Keyword(s):  
Electromagnetic Scattering ◽  
Vertical Profiles ◽  
Polarimetric Radar ◽  
Winter Storm ◽  
Differential Phase Shift ◽  
Winter Storms ◽  
One Dimensional ◽  
Melting Layer ◽  
Differential Reflectivity ◽  
General Profile

AbstractPolarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.

X-band Polarimetric Radar for Precise Precipitation Measurments

2013 ◽  
Vol 133 (3) ◽  
pp. 150-152
Author(s):  
Ikuya KAKIMOTO ◽  
Hisamitsu FUJIMOTO
Keyword(s):  
Polarimetric Radar ◽  
X Band

scholarly journals Torrefaction of Woody and Agricultural Biomass: Influence of the Presence of Water Vapor in the Gaseous Atmosphere

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 30
Author(s):  
María González Martínez ◽  
Estéban Hélias ◽  
Gilles Ratel ◽  
Sébastien Thiéry ◽  
Thierry Melkior
Keyword(s):  
Water Vapor ◽  
Water Content ◽  
Wheat Straw ◽  
Beech Wood ◽  
High Water ◽  
High Water Content ◽  
Biomass Degradation ◽  
Moist Atmosphere ◽  
Thermochemical Transformation ◽  
Degradation Reactions

Biomass preheating in torrefaction at an industrial scale is possible through a direct contact with the hot gases released. However, their high water-content implies introducing moisture (around 20% v/v) in the torrefaction atmosphere, which may impact biomass thermochemical transformation. In this work, this situation was investigated for wheat straw, beech wood and pine forest residue in torrefaction in two complementary experimental devices. Firstly, experiments in chemical regime carried out in a thermogravimetric analyzer (TGA) showed that biomass degradation started from lower temperatures and was faster under a moist atmosphere (20% v/v water content) for all biomass samples. This suggests that moisture might promote biomass components’ degradation reactions from lower temperatures than those observed under a dry atmosphere. Furthermore, biomass inorganic composition might play a role in the extent of biomass degradation in torrefaction in the presence of moisture. Secondly, torrefaction experiments on a lab-scale device made possible to assess the influence of temperature and residence time under dry and 100% moist atmosphere. In this case, the difference in solid mass loss between dry and moist torrefaction was only significant for wheat straw. Globally, an effect of water vapor on biomass transformation through torrefaction was observed (maximum 10%db), which appeared to be dependent on the biomass type and composition.

scholarly journals Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

2016 ◽  
Vol 9 (9) ◽  
pp. 4425-4445 ◽  
Author(s):  
Nikola Besic ◽  
Jordi Figueras i Ventura ◽  
Jacopo Grazioli ◽  
Marco Gabella ◽  
Urs Germann ◽  
...  
Keyword(s):  
Polarimetric Radar ◽  
Statistical Framework ◽  
X Band ◽  
Different Types ◽  
Unsupervised Approach ◽  
Radar Measurements ◽  
Supervised Classification Methods ◽  
Operational Potential ◽  
Statistical Clustering

Abstract. Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.

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