Search Results

You are looking at 1 - 10 of 17 items for

  • Author or Editor: Hervé Andrieu x
  • Refine by Access: Content accessible to me x
Clear All Modify Search
Brice Boudevillain and Hervé Andrieu

Abstract

Vertically integrated liquid (VIL) water content is a parameter obtained from a radar performing voluminal scanning. This parameter has proven useful in the detection of severe storms and may be a worthwhile indicator for very short-term rainfall forecasting methods. Unfortunately, no information is available on the accuracy of VIL radar measurements. The present paper addresses this issue by means of simulation. Reference VILs are defined from vertical profiles of drop size distributions (DSD). These profiles make it possible to simulate the corresponding vertical profiles of reflectivity as well as the radar measurements used to deduce the VIL, as estimated classically (i.e., application of a classical relationship between equivalent radar reflectivity factor Z e and liquid water content M adapted to raindrops). A comparison of the reference VIL to the corresponding estimate then allows estimating radar measurement error. The VIL measurement error is first studied from two hypothetical, yet realistic, vertical profiles of DSD: one typical of stratiform rain and the other typical of a convective situation. A sensitivity analysis with respect to both meteorological conditions and radar operating conditions is also performed on these two profiles. For the convective case, use of a classical Z eM relationship adapted to liquid water results in a significant underestimation of the reference VIL value. The same effect applies to the stratiform profile, even though brightband phenomena can compensate for this underestimation and lend the impression of smaller measurement error. A simple alternative method is proposed in order to reduce measurement errors. Both conventional and alternative VIL measurement methods are tested on the two theoretical profiles as well as on a series of actual vertical profiles of reflectivity. Better measurements are obtained with the alternative method, provided the altitude of the 0°C isotherm and the density of ice particles can be determined with reasonable precision. This alternative method for estimating VIL from radar data could serve to improve VIL measurement accuracy and would be worth applying to a longer series of observed data.

Full access
Hervé Andrieu and Jean Dominique Creutin

Abstract

A method of identification of the vertical profile of reflectivity, formulated by the authors in an accompanying paper, is tested through a sensitivity analysis. Two simulated but realistic profiles (with and without brightband effects) are used. The radar features and the statistical parameters involved in this method are allowed to varyaround standard values in order to understand their influence on the results. The main conclusion is that, for a given radar configuration, results of acceptable quality can be obtained with a single adjustment ofthe method for the two types of profiles, which suggests the approach is operationally applicable. To complement this theoretical analysis, actual profiles of reflectivities are studied for two rainfall eventsobserved in the Cevennes region of France. The efficiency of the proposed method is appreciated from a hydrological point of view. A comparison is performed at the basin scale between hourly rainfall intensities, measured with a dense network of rain gauges and radar data. The analysis shows that the introduction of the identification and the correction of the influence of vertical profiles of reflectivity improve the accuracy of rainfall estimates from radar data.

Full access
Hervé Andrieu and Jean Dominique Creutin

Abstract

The vertical variability of reflectivity in the radar beam is one of the main sources of error in estimating rainfall intensity. This vertical variability, which has several origins, is characterized globally by a function called "vertical profile of reflectivity." The impact of this vertical profile of reflectivity on the radar measurement is quantified by incorporating this function in the radar equation. It is then possible to specify the influence of the characteristics of the radar, the distance, and the vertical profile on errors in estimating rain rates at the ground level. A method for determining the vertical profile of reflectivity is then described. This procedure requires the use of radar images from at least two different elevation angles. It is based on the evolution of theratio of reflectivities (reflectivity at high elevation divided by reflectivity at a lower elevation angle) versus distance. The ratio evolution is closely related to the vertical profile of reflectivity and to the conditions of radar operation. An inverse solution method is used to identify the vertical profile of reflectivity corresponding to the observed ratio of reflectivities. The advantages and limitations of the proposed method are discussed.

Full access
Guy Delrieu, Jean Dominique Creutin, and Hervé Andrieu

Abstract

The aim of the present study is to characterize mountain returns measured with a ground-based weather radar operating in a mountainous region. A computation code based on the use of a digitized terrain model is developed for calculating the areas illuminated by the radar beam. Partial and total screening effects am accounted for in the calculation. The angular and range weighting functions of the radar measurement am modeled using Gaussian approximations to give the so-called weighted illuminated areas for various sizes of the radar resolution volume. Radar measurements are compared to the computed illuminated areas in order to determine the average backscattering coefficient of partly grass-covered, partly forested mountains: 87% of the measured time-averaged mountain return variance is explained by the computed values when the 15-dB resolution volume is considered. Additional geometrical information, provided by the calculated angles of incidence, is accounted for to yield a linear σ(dB) 0(α) model relevant for the so-called near-grazing region since most of the angles of incidence are in the 70°–900° range. Here 92% of the measurement variance is explained when the σ(dB) 0(α) model is used.

Full access
Brice Boudevillain, Hervé Andrieu, and Nadine Chaumerliac

Abstract

A very short-term rainfall forecast model is tested on actual radar data. This model, called RadVil, takes advantages of voluminal radar data through vertically integrated liquid (VIL) water content measurements. The model is tested on a dataset collected during the intensive observation period of the Mesoscale Alpine Program (MAP). Five rain events have been studied during this experiment. The results confirm the interest of VIL for quantitative precipitation forecasting at very short lead time. The evaluation is carried out in qualitative and quantitative ways according to Nash and correlation criteria on forecasting times ranging from 10 to 90 min and spatial scales from 4 to 169 km2. It attempts to be consistent with the hydrological requirements concerning the rainfall forecasting, for instance, by taking account of the relation between the catchments' size, their response time, and the required forecasting time. Several versions of RadVil corresponding to several VIL measurement strategies have been tested. Improvements offered by RadVil depend on meteorological situations. They are related to the spatial and temporal evolution of the VIL field structure and the validity of the models assumptions. Finally, a relationship between the temporal structure of VIL fields and forecast quality is established.

Full access
Bertrand Vignal, Hervé Andrieu, and J. Dominique Creutin

Abstract

The vertical variability of reflectivity in the radar beam is an important source of error that interferes with a reliable estimation of the rainfall rate by radar. This source of error can be corrected if the vertical profile of reflectivity (VPR) has been previously determined. This paper presents a method for determining local VPRs from volume scan radar data, that is, from radar data recorded at multiple elevation angles. It is shown that the VPR directly provided by volume scan radar data differs from the true one, which can make it inappropriate to the correction of radar data for the VPR influence. The VPR identification method, based on the analysis of ratios of radar measurements at multiple elevations angles, is then described. The application conditions of the method are defined through sensitivity tests applied to a synthetic case. A “real world” case study allows performing a first evaluation of the proposed method. This analysis demonstrates that the identification of local VPRs and the correction for their influence at a scale of about 100 km2 contributes to improving the reliability of rainfall measurement by radar. Moreover, it is shown that a correction of radar data based on identified VPRs performs better than a correction based on the VPRs directly deduced from volume scan radar data. This last point confirms the importance of the VPR identification stage in the correction of radar data for this source of error.

Full access
Guy Delrieu, Hervé Andrieu, and Jean Dominique Creutin

Abstract

The aim of the current study is to quantify attenuation effects that X- and C-band weather radar systems may experience in heavy rainfall. Part of this information can be obtained from power-law relationships between the attenuation coefficient k (dB km−1) and the rain rate R (mm h−1). These relations exhibit a strong dependence on the wavelength used and a significant influence of the raindrop size and temperature distributions. Here the purpose is to go one step further by providing estimates of the path-integrated attenuations (PIAs) that could be observed as a function of range for a given wavelength. Obviously, these values depend on the space and time structure of rainfall and, therefore, refer to a given climatological context. The methodology used consists of using k–R relations to downgrade carefully processed S-band radar data to the corresponding X- and C-band signals. The data were collected in the Cévennes region, a Mediterranean region in France subject to intense and long-lasting rain events during the autumn season. A refined data processing procedure was applied to the available reflectivity measurements, including ground-clutter removal and correction for the effects of the vertical profile of reflectivity as well as a final bias adjustment using rain gauge data. For three rain events, 75 h of instantaneous rain-rate fields thus were available with total rain amounts that exceeded 300 mm over most of the area of interest. Examples of attenuated profiles are presented, and PIA-range-frequency curves are established for the two wavelengths considered under various hypotheses that concern the raindrop size distribution. One of the results is that, at C band, a PIA of 3 dB is exceeded for 5% of the rain-rate profiles at a range of 50 km. Another finding is that a multiplicative factor of about 6 exists between C- and X-band attenuation effects. Implications for rain-rate estimation at X- and C band are discussed.

Full access
Bertrand Vignal, Hervé Andrieu, G. Delrieu, and J. Dominique Creutin

Abstract

Attenuation in rainfall is recognized as one of the most significant limitations in rain-rate estimation from weather radar returns at X- or C-band wavelengths. This paper introduces a radar measurement correction as an inverse problem that accounts for attenuation effects in rainfall. First, a direct theoretical model, relating radar returns at attenuating wavelengths to the rainfall rates between the radar and the point of measurement, is presented. Second, the inverse algorithm used to identify rain-rate estimates from radar returns is described and its application to the attenuation correction is discussed, with the well-known characteristics of the attenuation model (i.e., instability, underdetermination, and nonlinearity) receiving particular attention. Third, a sensitivity analysis is then performed to test the influence of the raindrop size distribution, radar measurement features, and statistical parameters involved in the inverse method. The sensitivity analysis allows for establishing the application conditions of the method. Last, a preliminary evaluation of the method is provided, through simulated radar rainfall measurements and through a limited case study. Various attenuation correction methods are compared with the inverse algorithm. These methods include the standard radar reflectivity–rainfall rate algorithm and two versions of the Hitschfeld–Bordan algorithm. In the simulation exercise, various examples of rainfall field, with different characteristics, are tested. The case study confirms the utility of the proposed method and its ability to provide a robust and stable solution. The method consistently provides better results than the well-known Hitschfeld–Bordan algorithm.

Full access
Mark N. French, Hervé Andrieu, and Witold F. Krajewski

Abstract

Radar reflectivity is used to estimate meteorological quantities such as rainfall rate, liquid water content, and the related quantity, vertically integrated liquid (VIL) water content. The estimation of any of these quantities depends on several assumptions related to the characteristics of the physical processes controlling the occurrence and character of water in the atmosphere. Additionally, there are many sources of error associated with radar observations, such as those due to brightband, hail, and drop size distribution approximations. This work addresses one error of interest, the radar reflectivity observation error; other error sources are assumed to be corrected or negligible. The result is a relationship between the uncertainty in VIL water content and radar reflectivity measurement error. An example application illustrates the estimation of VIL uncertainty from typical radar reflectivity observations and indicates that the coefficient of variation in VIL is much larger than the coefficient of variation in radar reflectivity.

Full access
Alexis Berne, Guy Delrieu, Herve Andrieu, and Jean-Dominique Creutin

Abstract

The present study aims to demonstrate the major influence of the vertical heterogeneity of rainfall on radar–rain gauge assessment. For this purpose, an experimental setup was deployed during the HYDROMET Integrated Radar Experiment (HIRE-98) based on a conventional S-band weather radar operating at long range (90 km), an X-band vertically pointing radar, and a network of 25 tipping-bucket rain gauges. After calibration and attenuation corrections, the X-band radar data enables the estimation of the vertical profile of reflectivity (VPR) time series. Screening and VPR correction factors are derived for the distant S-band radar measurements. The raw and corrected S-band radar estimates are compared to rain gauge measurements for various integration time steps (6–30 min). Considering about 12 h of intense Mediterranean precipitation, the VPR influence at the X-band radar site is clear for all the time steps considered. For instance, a continuous increase in the Nash efficiency for the corrected radar data compared to the rain gauge data (0.85 for the 6-min time step, up to 0.93 for the 30-min time step) is observed while this criterion remains less than 0.15 for the raw radar data, regardless of the time step. The effect of the low-level reflectivity enhancement on the radar–rain gauge assessment was also found to be very important in the considered configuration. The establishment of reliable VPR climatologies is therefore a challenge in order to better account for such effects that are not observable at long range from the radars. The spatial validity of the VPR correction derived from a point sensor like the vertically pointing radar is also investigated. As a result of the high space–time variability of rainfall, such a punctual VPR correction has an efficiency limited to areas of about 20 km2 (200 km2) for the 6-min (30 min) integration time step.

Full access