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Abstract
The present paper deals with the adaptation of the Multiple Analytical Doppler (MANDOP) analysis to Doppler radar observations over complex orography. The objective, in the context of the Mesoscale Alpine Programme (MAP), is to design a reliable and flexible tool able to process any kind of radar data (airborne/ground based) in order to retrieve mesoscale three-dimensional wind fields over complex terrain with a convective-scale resolution. The various effects of the orography on the wind field (slope winds) and on the radar sampling (ground clutter, shadowing effect) are considered and taken into account in each step of the wind synthesis. In addition to these specific aspects, some numerical improvements are presented that make the method quicker and more objective. The method is validated with quasi-real simulated data, and three different boundary conditions are compared (bottom, top, and both). The analysis is eventually applied to real data gathered during IOP2b of the MAP special observing period (SOP) by the C-band Ronsard and Monte Lema Doppler radars, allowing interpretation of the reflectivity and velocity patterns in close correlation with the orography.
Abstract
The present paper deals with the adaptation of the Multiple Analytical Doppler (MANDOP) analysis to Doppler radar observations over complex orography. The objective, in the context of the Mesoscale Alpine Programme (MAP), is to design a reliable and flexible tool able to process any kind of radar data (airborne/ground based) in order to retrieve mesoscale three-dimensional wind fields over complex terrain with a convective-scale resolution. The various effects of the orography on the wind field (slope winds) and on the radar sampling (ground clutter, shadowing effect) are considered and taken into account in each step of the wind synthesis. In addition to these specific aspects, some numerical improvements are presented that make the method quicker and more objective. The method is validated with quasi-real simulated data, and three different boundary conditions are compared (bottom, top, and both). The analysis is eventually applied to real data gathered during IOP2b of the MAP special observing period (SOP) by the C-band Ronsard and Monte Lema Doppler radars, allowing interpretation of the reflectivity and velocity patterns in close correlation with the orography.
Abstract
In 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase K dp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results.
Abstract
In 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase K dp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results.
Abstract
The influence of ground clutter contamination on the estimation of polarimetric radar parameters, horizontal reflectivity (Zh ), differential reflectivity (Z dr), correlation coefficient (ρ hυ ), and differential propagation phase (ϕ dp) was examined. This study aims to derive the critical level of ground clutter contamination for Zh , Z dr, ρ hυ , and ϕ dp at which ground clutter influence exceeds predefined precision thresholds. Reference data with minimal ground clutter contamination consist of eight precipitation fields measured during three rain events characterized by stratiform and convective precipitation. Data were collected at an elevation angle of 0.8° by the Météo-France operational, polarimetric Doppler C-band weather radar located in Trappes, France, ∼30 km southwest of Paris. Nine different ground clutter signatures, ranging from point targets to more complex signatures typical for mountain ranges or urban obstacles, were added to the precipitation fields. This is done at the level of raw in-phase and quadrature component data in the two polarimetric channels. For each ground clutter signature, 30 simulations were conducted in which the mean reflectivity of ground clutter within the resolution volume varied between being 30 dB higher to 30 dB lower than the mean reflectivity of precipitation. Differences in Zh, Z dr, ρυ , and ϕ dp between simulation and reference were shown as a function of ratio between ground clutter and precipitation intensities.
As a result of this study, horizontal reflectivity showed the lowest sensitivity to ground clutter contamination. Furthermore, a precision of 1.7 dBZ in Zh is achieved on average when the precipitation and ground clutter intensities are equal. Requiring a precision of 0.2 dB in Z dr and 3° in ϕ dp, the reflectivity of precipitation needs to be on average ∼5.5 and ∼6 dB, respectively, higher compared to the reflectivity of ground clutter. The analysis also indicates that the highest sensitivity to the nine clutter signatures was derived for ρ hυ . To meet a predefined precision threshold of 0.02, reflectivity of precipitation needs to be ∼13.5 dB higher than the reflectivity of ground clutter.
Abstract
The influence of ground clutter contamination on the estimation of polarimetric radar parameters, horizontal reflectivity (Zh ), differential reflectivity (Z dr), correlation coefficient (ρ hυ ), and differential propagation phase (ϕ dp) was examined. This study aims to derive the critical level of ground clutter contamination for Zh , Z dr, ρ hυ , and ϕ dp at which ground clutter influence exceeds predefined precision thresholds. Reference data with minimal ground clutter contamination consist of eight precipitation fields measured during three rain events characterized by stratiform and convective precipitation. Data were collected at an elevation angle of 0.8° by the Météo-France operational, polarimetric Doppler C-band weather radar located in Trappes, France, ∼30 km southwest of Paris. Nine different ground clutter signatures, ranging from point targets to more complex signatures typical for mountain ranges or urban obstacles, were added to the precipitation fields. This is done at the level of raw in-phase and quadrature component data in the two polarimetric channels. For each ground clutter signature, 30 simulations were conducted in which the mean reflectivity of ground clutter within the resolution volume varied between being 30 dB higher to 30 dB lower than the mean reflectivity of precipitation. Differences in Zh, Z dr, ρυ , and ϕ dp between simulation and reference were shown as a function of ratio between ground clutter and precipitation intensities.
As a result of this study, horizontal reflectivity showed the lowest sensitivity to ground clutter contamination. Furthermore, a precision of 1.7 dBZ in Zh is achieved on average when the precipitation and ground clutter intensities are equal. Requiring a precision of 0.2 dB in Z dr and 3° in ϕ dp, the reflectivity of precipitation needs to be on average ∼5.5 and ∼6 dB, respectively, higher compared to the reflectivity of ground clutter. The analysis also indicates that the highest sensitivity to the nine clutter signatures was derived for ρ hυ . To meet a predefined precision threshold of 0.02, reflectivity of precipitation needs to be ∼13.5 dB higher than the reflectivity of ground clutter.
Abstract
Doppler radar measurements provide the radial wind within an unambiguous interval due to the limited value of the sampling frequency (pulse repetition frequency). Many algorithms have been developed to retrieve true wind velocities from measured aliased wind velocities. However, these algorithms are time consuming, which can be a constraint in an operational context. Besides, most of them need independent information on the wind generally provided by complementary neighbor measurements such as radiosonde or wind profiler. This paper describes a new method aimed at providing an estimate of the real wind directly from aliased wind measurements without prior dealiasing, allowing the method to be used in real time by operational radars without additional information from other instruments. A potential application of the method is to provide a reference wind profile that can be used, in a second step, to dealias radial velocities.
Abstract
Doppler radar measurements provide the radial wind within an unambiguous interval due to the limited value of the sampling frequency (pulse repetition frequency). Many algorithms have been developed to retrieve true wind velocities from measured aliased wind velocities. However, these algorithms are time consuming, which can be a constraint in an operational context. Besides, most of them need independent information on the wind generally provided by complementary neighbor measurements such as radiosonde or wind profiler. This paper describes a new method aimed at providing an estimate of the real wind directly from aliased wind measurements without prior dealiasing, allowing the method to be used in real time by operational radars without additional information from other instruments. A potential application of the method is to provide a reference wind profile that can be used, in a second step, to dealias radial velocities.
Abstract
The recent deployment of an innovative triple pulse rise time (PRT) scheme within the French operational radar network allows for the simultaneous collection of reflectivity and radial velocity measurements up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of operational exploitation of Doppler measurements including the capability to consistently perform multiple-Doppler wind synthesis in a fully operational framework. Using real and simulated Doppler observations, the authors show that the 3D wind fields retrieved in that framework can definitely be relied upon to achieve a consistent and detailed mapping of the airflow structure in various precipitation regimes despite radar baselines averaging ∼180 km and very limited scanning strategies. This achievement could be easily transposed to other operational networks and represents a remarkable opportunity to add further value to operational Doppler velocity measurements.
Abstract
The recent deployment of an innovative triple pulse rise time (PRT) scheme within the French operational radar network allows for the simultaneous collection of reflectivity and radial velocity measurements up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of operational exploitation of Doppler measurements including the capability to consistently perform multiple-Doppler wind synthesis in a fully operational framework. Using real and simulated Doppler observations, the authors show that the 3D wind fields retrieved in that framework can definitely be relied upon to achieve a consistent and detailed mapping of the airflow structure in various precipitation regimes despite radar baselines averaging ∼180 km and very limited scanning strategies. This achievement could be easily transposed to other operational networks and represents a remarkable opportunity to add further value to operational Doppler velocity measurements.
Abstract
A method for the daily monitoring of the differential reflectivity bias for polarimetric weather radars is presented. Sun signals detected in polar volume data produced during operational scanning of the radar are used. This method is an extension of that for monitoring the weather radar antenna pointing at low elevations and the radar receiving chain using the sun. This “online” method is ideally suited for routine application in networks of operational radars.
The online sun monitoring can be used to check the agreement between horizontal and vertical polarization lobes of the radar antenna, which is a prerequisite for high-quality polarimetric measurements. By performing both online sun monitoring and rain calibration at vertical incidence, the differential receiver bias and differential transmitter bias can be disentangled. Results from the polarimetric radars in Trappes (France) and Bornholm (Denmark), demonstrating the importance of regular monitoring of the differential reflectivity bias, are discussed.
It is recommended that the online sun-monitoring method, preferably in combination with rain calibration, is routinely performed on all polarimetric weather radars because accurate calibration is a prerequisite for most polarimetric algorithms.
Abstract
A method for the daily monitoring of the differential reflectivity bias for polarimetric weather radars is presented. Sun signals detected in polar volume data produced during operational scanning of the radar are used. This method is an extension of that for monitoring the weather radar antenna pointing at low elevations and the radar receiving chain using the sun. This “online” method is ideally suited for routine application in networks of operational radars.
The online sun monitoring can be used to check the agreement between horizontal and vertical polarization lobes of the radar antenna, which is a prerequisite for high-quality polarimetric measurements. By performing both online sun monitoring and rain calibration at vertical incidence, the differential receiver bias and differential transmitter bias can be disentangled. Results from the polarimetric radars in Trappes (France) and Bornholm (Denmark), demonstrating the importance of regular monitoring of the differential reflectivity bias, are discussed.
It is recommended that the online sun-monitoring method, preferably in combination with rain calibration, is routinely performed on all polarimetric weather radars because accurate calibration is a prerequisite for most polarimetric algorithms.
Abstract
This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection.
Abstract
This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection.
Abstract
Radar reflectivity (Z h), differential reflectivity (Z dr), and specific differential phase (K dp) measured from the operational, polarimetric weather radar located in Trappes, France, were used to examine the effects of radar beam shielding on rainfall estimation. The objective of this study is to investigate the degree of immunity of K dp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered in Europe. The rain events include two cold frontal rainbands with average rainfall rates of 7 and 17 mm h−1, respectively, and two summertime convective rain events with average rainfall rates of 11 and 22 mm h−1.
The large effects of beam shielding on rainfall accumulation were observed for algorithms using Z h and Z dr with differences of up to ∼2 dB (40%) compared to a K dp-based algorithm over a power loss range of 0–8 dB. This analysis reveals that Z dr and K dp are not affected by partial beam shielding. Standard reflectivity corrections based on the degree of beam shielding would have overestimated rainfall rates by up to 1.5 dB for less than 40% beam shielding and up to 3 dB for beam shielding less than 75%. The investigation also examined the sensitivity of beam shielding effects on rainfall rate estimation to (i) axis–ratio parameterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase (ϕ dp) and estimate K dp, and (iii) event-to-event variability. Although rainfall estimates were sensitive to drop size distribution and axis–ratio parameterization, differences between Z h- and K dp-based rainfall rates increased independently from those parameters with amount of shielding. Different approaches to smoothing ϕ dp profiles and estimating K dp were examined and showed little impact on results.
Abstract
Radar reflectivity (Z h), differential reflectivity (Z dr), and specific differential phase (K dp) measured from the operational, polarimetric weather radar located in Trappes, France, were used to examine the effects of radar beam shielding on rainfall estimation. The objective of this study is to investigate the degree of immunity of K dp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered in Europe. The rain events include two cold frontal rainbands with average rainfall rates of 7 and 17 mm h−1, respectively, and two summertime convective rain events with average rainfall rates of 11 and 22 mm h−1.
The large effects of beam shielding on rainfall accumulation were observed for algorithms using Z h and Z dr with differences of up to ∼2 dB (40%) compared to a K dp-based algorithm over a power loss range of 0–8 dB. This analysis reveals that Z dr and K dp are not affected by partial beam shielding. Standard reflectivity corrections based on the degree of beam shielding would have overestimated rainfall rates by up to 1.5 dB for less than 40% beam shielding and up to 3 dB for beam shielding less than 75%. The investigation also examined the sensitivity of beam shielding effects on rainfall rate estimation to (i) axis–ratio parameterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase (ϕ dp) and estimate K dp, and (iii) event-to-event variability. Although rainfall estimates were sensitive to drop size distribution and axis–ratio parameterization, differences between Z h- and K dp-based rainfall rates increased independently from those parameters with amount of shielding. Different approaches to smoothing ϕ dp profiles and estimating K dp were examined and showed little impact on results.
Abstract
A fuzzy logic algorithm has been developed for the purpose of segregating precipitating from nonprecipitating echoes using polarimetric radar observations at C band. Adequate polarimetric descriptions for each type of scatterer are required for the algorithm to be effective. An observations-based approach is presented in this study to derive membership functions and objectively weight them so that they apply directly to conditions experienced at the radar site and to the radar wavelength. Three case studies are examined and show that the algorithm successfully removes nonprecipitating echoes from rainfall accumulation maps.
Abstract
A fuzzy logic algorithm has been developed for the purpose of segregating precipitating from nonprecipitating echoes using polarimetric radar observations at C band. Adequate polarimetric descriptions for each type of scatterer are required for the algorithm to be effective. An observations-based approach is presented in this study to derive membership functions and objectively weight them so that they apply directly to conditions experienced at the radar site and to the radar wavelength. Three case studies are examined and show that the algorithm successfully removes nonprecipitating echoes from rainfall accumulation maps.
Abstract
Rain path attenuation correction is a challenging task for quantitative use of weather radar measurements at frequencies higher than S band. The proportionality relationship between specific attenuation αhh (specific differential attenuation α dp) and specific differential phase K dp is the basis for simple path-integrated attenuation correction using differential phase Φdp. However, the coefficients of proportionality are known to be dependent upon temperature, on the one hand, and shape and raindrop size distribution, on the other hand. To solve this problem, a Bayesian classification scheme is proposed to empirically find the prevailing rain regime and adapt the Φdp-based method. The proposed approach herein is compared with other polarimetric techniques currently available in the literature. Several episodes observed in the Paris, France, area by the C-band dual-polarized weather radar operating in Trappes (France) are analyzed and results are discussed.
Abstract
Rain path attenuation correction is a challenging task for quantitative use of weather radar measurements at frequencies higher than S band. The proportionality relationship between specific attenuation αhh (specific differential attenuation α dp) and specific differential phase K dp is the basis for simple path-integrated attenuation correction using differential phase Φdp. However, the coefficients of proportionality are known to be dependent upon temperature, on the one hand, and shape and raindrop size distribution, on the other hand. To solve this problem, a Bayesian classification scheme is proposed to empirically find the prevailing rain regime and adapt the Φdp-based method. The proposed approach herein is compared with other polarimetric techniques currently available in the literature. Several episodes observed in the Paris, France, area by the C-band dual-polarized weather radar operating in Trappes (France) are analyzed and results are discussed.
