Characterization of S-Band Dual-Polarized Radar Data for the Convective Rain Melting Layer Detection in A Tropical Region

In the tropical region, convective rain is a dominant rain event. However, very little information is known about the convective rain melting layer. In this paper, S-band dual-polarized radar data is studied in order to identify both the stratiform and convective rain melting layers in the tropical region, with a focus on the convective events. By studying and analyzing the above-mentioned two types of rain events, amongst three radar measurements of reflectivity ( Z ), differential reflectivity ( Z DR ), and cross correlation coefficient ( ρ HV ), the latter one is the best indicator for convective rain melting layer detection. From two years (2014 and 2015) of radar and radiosonde observations, 13 convective rain melting layers are identified with available 0 °C isothermal heights which are derived from radiosonde vertical profiles. By comparing the melting layer top heights with the corresponding 0 °C isothermal heights, it is found that for convective rain events, the threshold to detect melting layer should be modified to ρ HV = 0.95 for the tropical region. The melting layer top and bottom heights are then estimated using the proposed threshold, and it is observed from this study that the thickness of convective rain melting layer is around 2 times that of stratiform rain melting layer which is detected by using the conventional ρ HV = 0.97 .

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Polarimetric radar observations during an orographic rain event and the performance of a hydrometeor classification scheme

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8845-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8845-8877

Author(s):

M. Frech ◽

J. Steinert

Keyword(s):

Classification Scheme ◽

Ground Level ◽

Radar Data ◽

Precipitation Event ◽

Orographic Precipitation ◽

Rain Event ◽

Melting Layer ◽

Surface Observation ◽

Meteorological Observatory ◽

Radar Sensing

Abstract. An intense orographic precipitation event is analysed using two polarimetric C-Band radars situated north of the Alps on 5 January 2013. One radar is operated at DWD's meteorological observatory Hohenpeißenberg (MHP, 1006 m a.s.l. – above sea level) and the Memmingen (MEM, 65 km west of MHP, 600 m a.s.l.) radar is part of DWD's operational radar network. The event lasted about 1.5 days and in total 44 mm precipitation was measured at Hohenpeißenberg. Detailed high resolution observation on the vertical structure of this event is obtained through a birdbath scan at 90° elevation which is part of the operational scanning. This scan is acquired every 5 min and provides meteorological profiles at high spatial resolution. In the course of this event, the melting layer (ML) descends until the transition from rain into snow is observed at ground level. This transition from rain into snow is well documented by local weather observers and a present-weather sensor. The orographic precipitation event reveals mesoscale variability above the melting layer which is unexpected from a meteorological point of view. It corresponds to a substantial increase in rain rate at the surface. The performance of the newly developed hydrometeor classification scheme "Hymec" using Memmingen radar data over Hohenpeißenberg is analyzed. The detection in location and timing of the ML agrees well with the Hohenpeißenberg radar data. Considering the size of the Memmingen radar sensing volume, the detected hydrometeor (HM) types are consistent for measurements at or in a ML, even though surface observation indicate for example rain whereas the predominant HM is classified as wet snow. To better link the HM classification with the surface observation, either better thermodynamic input is needed for Hymec or a statistical correction of the HM classification similar to a model output statistics (MOS) approach may be needed.

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Scattering Calculations for Asymmetric Raindrops during a Line Convection Event: Comparison with Radar Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0196.1 ◽

2018 ◽

Vol 35 (6) ◽

pp. 1169-1180 ◽

Cited By ~ 3

Author(s):

Sanja B. Manić ◽

Merhala Thurai ◽

V. N. Bringi ◽

Branislav M. Notaroš

Keyword(s):

Rain Event ◽

Size Distributions ◽

Surface Integral ◽

Azimuthal Dependence ◽

Industry Standard ◽

Standard Code ◽

Radar Measurements ◽

Linear Depolarization Ratio ◽

Drop Size Distributions ◽

Differential Reflectivity

AbstractTwo-dimensional video disdrometer (2DVD) data from a line convection rain event are analyzed using the method of moments surface integral equation (MoM-SIE) via drop-by-drop polarimetric scattering calculations at C band that are compared with radar measurements. Drop geometry of asymmetric drop shapes is reconstructed from 2DVD measurements, and the MoM-SIE model is created by meshing the surface of the drop. The differential reflectivity Zdr calculations for an example asymmetric drop are validated against an industry standard code solution at C band, and the azimuthal dependence of results is documented. Using the MoM-SIE analysis on 2DVD drop-by-drop data (also referred to as simply MoM-SIE), the radar variables [Zh, Zdr, Kdp, ρhv] are computed as a function of time (with 1-min resolution) and compared to C-band radar measurements. The importance of shape variability of asymmetric drops is demonstrated by comparing with the traditional (or “bulk”) method, which uses 1-min averaged drop size distributions and equilibrium oblate shapes. This was especially pronounced for ρhv, where the MoM-SIE method showed lowered values (dip) during the passage of the line convection consistent with radar measurements, unlike the bulk method. The MoM-SIE calculations of [Zh, Zdr, Kdp] agree very well with the radar measurements, whereas linear depolarization ratio (LDR) calculations from the drop-by-drop method are found to be larger than the values from the bulk method, which is consistent with the dip in simulated and radar-measured ρhv. Our calculations show the importance of the variance of shapes resulting from asymmetric drops in the calculation of ρhv and LDR.

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A Variational Approach for Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements in the Presence of Attenuation

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0101.1 ◽

2013 ◽

Vol 52 (1) ◽

pp. 169-185 ◽

Cited By ~ 12

Author(s):

Qing Cao ◽

Guifu Zhang ◽

Ming Xue

Keyword(s):

Variational Approach ◽

Simulated Data ◽

Real Data ◽

Radar Data ◽

Polarimetric Radar ◽

University Of Oklahoma ◽

Raindrop Size Distribution ◽

Radar Measurements ◽

Raindrop Size ◽

Differential Reflectivity

AbstractThis study presents a two-dimensional variational approach to retrieving raindrop size distributions (DSDs) from polarimetric radar data in the presence of attenuation. A two-parameter DSD model, the constrained-gamma model, is used to represent rain DSDs. Three polarimetric radar measurements—reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP—are optimally used to correct for the attenuation and retrieve DSDs by taking into account measurement error effects. Retrieval results with simulated data demonstrate that the proposed algorithm performs well. Applications to real data collected by the X-band Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars and the C-band University of Oklahoma–Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) also demonstrate the efficacy of this approach.

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Can a Unique Model Describe the Raindrop Shape–Size Relation? A Clue from Polarimetric Radar Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2009jtecha1183.1 ◽

2009 ◽

Vol 26 (9) ◽

pp. 1829-1842 ◽

Cited By ~ 9

Author(s):

Eugenio Gorgucci ◽

V. Chandrasekar ◽

Luca Baldini

Keyword(s):

Axial Ratio ◽

Radar Data ◽

Polarimetric Radar ◽

Drop Shape ◽

Climatic Regions ◽

Unique Shape ◽

Initial Drop ◽

Radar Measurements ◽

Differential Reflectivity ◽

Size Relation

Abstract A method is proposed to retrieve raindrop shape–size relations from the radar measurements of reflectivity factor Zh, differential reflectivity Zdr, and specific differential phase Kdp at S band. This procedure is obtained using a domain defined by the two variables Kdp/Zh and Zdr where the drop size distribution (DSD) variability is collapsed onto a line and any variation is essentially due to the drop shape variability. To obtain information on the raindrop shape–size relation underlying a set of radar observations, this domain is studied in conjunction with another domain describing the relation between the drop axial ratio (or shape) and its equivolumetric diameter. Using an initial drop shape and choosing a set of DSDs described by a normalized gamma model, polarimetric radar measurements are produced by simulation. An averaged curve of Kdp/Zh versus Zdr is obtained and compared with the same curve obtained from the radar data. By changing the initial axial ratio relation, a procedure of minimization between the two curves is developed to derive the underlying drop shape–size relation governing the radar measurements under consideration. Three sets of radar data collected in different climatic regions are analyzed to evaluate whether there is a unique shape–size relation.

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Ground Clutter Filtering Dual-Polarized, Staggered PRT Sequences

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1904.1 ◽

2006 ◽

Vol 23 (8) ◽

pp. 1114-1130 ◽

Cited By ~ 5

Author(s):

M. Sachidananda ◽

Dusan S. Zrnic

Keyword(s):

Radar Data ◽

Differential Phase ◽

Ground Clutter ◽

Spectral Coefficients ◽

Repetition Time ◽

Dual Polarized ◽

Differential Reflectivity ◽

Simulated Time ◽

Simulated Time Series ◽

Position Indicator

Abstract A procedure to filter the ground clutter from a dual-polarized, staggered pulse repetition time (PRT) sequence and recover the complex spectral coefficients of the weather signal is presented. While magnitude spectra are sufficient for estimation of the spectral moments from staggered PRT sequences, computation of differential phase in dual-polarized radars requires recovery of the complex spectra. Herein a method is given to recover the complex spectral coefficients after the ground clutter is filtered. Under the condition of “narrow” spectra, it is possible to recover the differential phase, ΦDP, and the copolar correlation coefficient, ρhv, accurately, in addition to the differential reflectivity, ZDR. The technique is tested on simulated time series and on actual radar data. The efficacy of the method is demonstrated on plan position indicator (PPI) plots of polarimetric variables.

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Correction of Radar Reflectivity and Differential Reflectivity for Rain Attenuation at X Band. Part II: Evaluation and Application

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1804.1 ◽

2005 ◽

Vol 22 (11) ◽

pp. 1633-1655 ◽

Cited By ~ 117

Author(s):

S-G. Park ◽

M. Maki ◽

K. Iwanami ◽

V. N. Bringi ◽

V. Chandrasekar

Keyword(s):

Drop Size ◽

Earth Science ◽

Radar Data ◽

Rain Gauge ◽

Radar Rainfall ◽

X Band ◽

Rain Events ◽

Differential Reflectivity ◽

Rainfall Estimates ◽

Good Agreement

Abstract In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) ZH produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected ZH does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase KDP, with the R(ZH_cor) estimates being used for low rainfall rates (KDP ≤ 0.3° km−1 or ZH_cor ≤ 35 dBZ). This improvement in accuracy of rainfall estimation based on KDP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The ZH, ZDR, and KDP data are also used to infer the parameters (median volume diameter D0 and normalized intercept parameter Nw) of a normalized gamma DSD. The retrieval of D0 and Nw from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

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Data-driven clustering of rain events: microphysics information derived from macro-scale observations

Atmospheric Measurement Techniques ◽

10.5194/amt-10-1557-2017 ◽

2017 ◽

Vol 10 (4) ◽

pp. 1557-1574 ◽

Cited By ~ 6

Author(s):

Mohamed Djallel Dilmi ◽

Cécile Mallet ◽

Laurent Barthes ◽

Aymeric Chazottes

Keyword(s):

Rain Rate ◽

Dimensional Space ◽

Hierarchical Cluster ◽

Rate Variation ◽

Rain Event ◽

Self Organizing Maps ◽

Macro Scale ◽

Minimal Subset ◽

Rain Events

Abstract. Rain time series records are generally studied using rainfall rate or accumulation parameters, which are estimated for a fixed duration (typically 1 min, 1 h or 1 day). In this study we use the concept of rain events. The aim of the first part of this paper is to establish a parsimonious characterization of rain events, using a minimal set of variables selected among those normally used for the characterization of these events. A methodology is proposed, based on the combined use of a genetic algorithm (GA) and self-organizing maps (SOMs). It can be advantageous to use an SOM, since it allows a high-dimensional data space to be mapped onto a two-dimensional space while preserving, in an unsupervised manner, most of the information contained in the initial space topology. The 2-D maps obtained in this way allow the relationships between variables to be determined and redundant variables to be removed, thus leading to a minimal subset of variables. We verify that such 2-D maps make it possible to determine the characteristics of all events, on the basis of only five features (the event duration, the peak rain rate, the rain event depth, the standard deviation of the rain rate event and the absolute rain rate variation of the order of 0.5). From this minimal subset of variables, hierarchical cluster analyses were carried out. We show that clustering into two classes allows the conventional convective and stratiform classes to be determined, whereas classification into five classes allows this convective–stratiform classification to be further refined. Finally, our study made it possible to reveal the presence of some specific relationships between these five classes and the microphysics of their associated rain events.

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Lidar and radar measurements of the melting layer: observations of dark and bright band phenomena

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-4143-2012 ◽

2012 ◽

Vol 12 (9) ◽

pp. 4143-4157 ◽

Cited By ~ 21

Author(s):

P. Di Girolamo ◽

D. Summa ◽

M. Cacciani ◽

E. G. Norton ◽

G. Peters ◽

...

Keyword(s):

Rain Event ◽

Melting Layer ◽

Bright Band ◽

Lidar Measurements ◽

Multi Wavelength ◽

Radar Measurements ◽

Uhf Wind Profiler ◽

The University ◽

University Of Manchester

Abstract. Multi-wavelength lidar measurements in the melting layer revealing the presence of dark and bright bands have been performed by the University of BASILicata Raman lidar system (BASIL) during a stratiform rain event. Simultaneously radar measurements have been also performed from the same site by the University of Hamburg cloud radar MIRA 36 (35.5 GHz), the University of Hamburg dual-polarization micro rain radar (24.15 GHz) and the University of Manchester UHF wind profiler (1.29 GHz). Measurements from BASIL and the radars are illustrated and discussed in this paper for a specific case study on 23 July 2007 during the Convective and Orographically-induced Precipitation Study (COPS). Simulations of the lidar dark and bright band based on the application of concentric/eccentric sphere Lorentz-Mie codes and a melting layer model are also provided. Lidar and radar measurements and model results are also compared with measurements from a disdrometer on ground and a two-dimensional cloud (2DC) probe on-board the ATR42 SAFIRE. Measurements and model results are found to confirm and support the conceptual microphysical/scattering model elaborated by Sassen et al. (2005).

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Polarimetric radar observations during an orographic rain event

Hydrology and Earth System Sciences ◽

10.5194/hess-19-1141-2015 ◽

2015 ◽

Vol 19 (3) ◽

pp. 1141-1152 ◽

Cited By ~ 2

Author(s):

M. Frech ◽

J. Steinert

Keyword(s):

Ground Level ◽

Radar Data ◽

Precipitation Event ◽

Orographic Precipitation ◽

Rain Event ◽

Melting Layer ◽

Warm Front ◽

Meteorological Observatory ◽

Wet Snow ◽

Radar Sensing

Abstract. An intense orographic precipitation event on 5 January 2013 is analyzed using a polarimetric C-band radar situated north of the Alps. The radar is operated at the meteorological observatory Hohenpeißenberg (MHP, 1006 m a.s.l. – above sea level) of the German Meteorological Service (DWD). The event lasted about 1.5 days and in total 44 mm precipitation was measured at Hohenpeißenberg. Detailed high resolution observation on the vertical structure of this event is obtained through a birdbath scan at 90° elevation which is part of the operational scanning. This scan is acquired every 5 min and provides meteorological profiles at high spatial resolution which are often not available in other radar networks. In the course of this event, the melting layer (ML) descends until the transition from rain into snow is observed at ground level. This transition from rain into snow is well documented by local weather observers and a present-weather sensor. The orographic precipitation event reveals mesoscale variability above the melting layer which can be attributed to a warm front. This variability manifests itself through substantially increased hydrometeor fall velocities. Radiosounding data indicate a layered structure in the thermodynamic field with increased moisture availability in relation to warm air advection. Rimed snowflakes and aggregation in a relatively warm environment lead to a signature in the radar data which is attributed to wet snow. The passage of the warm front leads to a substantial increase in rain rate at the surface. We use the newly implemented hydrometeor classification scheme "Hymec" to illustrate issues when relating radar products to local observations. For this, we employ data from the radar near Memmingen (MEM, 65 km west of MHP, 600 m a.s.l.) which is part of DWD's operational radar network. The detection, in location and timing, of the ML agrees well with the Hohenpeißenberg radar data. Considering the size of the Memmingen radar sensing volume, the detected hydrometeor (HM) types are consistent for measurements at or in a ML, even though surface observations indicate for example rain whereas the predominant HM is classified as wet snow. To better link the HM classification with the surface observation, either better thermodynamic input for Hymec or a statistical correction of the HM classification similar to a model output statistics (MOS) approach may be needed.

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Cold pool collisions as a triggering mechanism of convection

10.5194/egusphere-egu2020-12367 ◽

2020 ◽

Author(s):

Gustav Halvorsen ◽

Bettina Meyer ◽

Jan Härter

Keyword(s):

Deep Convection ◽

Radar Data ◽

Spatial Distance ◽

Cold Pool ◽

Rain Event ◽

Radar Images ◽

Cold Pools ◽

Object Based ◽

Rain Events ◽

Atmospheric Phenomena

Cold pools are produced by rain evaporation from convective thunderstorms and play an important role&#160; in many atmospheric phenomena (e.g. transition to deep convection and convective self-aggregation). From observational and numerical studies, it has been found that intersecting cold pools increase the likelihood of triggering convection. We test this hypothesis by combining observational radar data from Darwin (Australia) with a simple conceptual model.We identify precipitation objects in the radar data. It is assumed that each rain event produces a cold pool that is initialized at the center of the precipitation cell. Cold pools are simulated with a stochastic surface growth model. The spatial coordinate of each collision event is recorded.&#160; Collectively these points take the shape of a Voronoi diagram.&#160; According to our hypothesis, the probability of new rain events should decay with spatial distance to the Voronoi.Our preliminary results suggest that rain events cluster in the vicinity of the Voronoi with a higher frequency that one would expect if cold pool collisions did not stimulate convection.&#160; To conclude, our findings suggest that dynamic collisions between cold pools increase the likelihood of convection in the surrounding area. This work allows us to study the effect of cold pools from radar data, despite cold pools being invisible to the radar images, using a simple object-based model of convective cold pools.&#160;

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