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Bertrand Vignal and Witold F. Krajewski

Abstract

The vertical variability of reflectivity is an important source of error that affects estimations of rainfall quantity by radar. This error can be reduced if the vertical profile of reflectivity (VPR) is known. Different methods are available to determine VPR based on volume-scan radar data. Two such methods were tested. The first, used in the Swiss Meteorological Service, estimates a mean VPR directly from volumetric radar data collected close to the radar. The second method takes into account the spatial variability of reflectivity and relies on solving an inverse problem in determination of the local profile. To test these methods, two years of archived level-II radar data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Tulsa, Oklahoma, and the corresponding rain gauge observations from the Oklahoma Mesonet were used. The results, obtained by comparing rain estimates from radar data corrected for the VPR influence with rain gauge observations, show the benefits of the methods—and also their limitations. The performance of the two methods is similar, but the inverse method consistently provides better results. However, for use in operational environments, it would require substantially more computational resources than the first method.

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Witold F. Krajewski and Bertrand Vignal

Abstract

A method of detecting anomalous propagation echo in volume scan radar reflectivity data is evaluated. The method is based on a neural network approach and is suitable for operational implementation. It performs a classification of the base scan data on a pixel-by-pixel basis into two classes: rain and no rain. The results of applying the method to a large sample of Weather Surveillance Radar-1988 Doppler (WSR-88D) level II archive data are described. The data consist of over 10 000 volume scans collected in 1994 and 1995 by the Tulsa, Oklahoma, WSR-88D. The evaluation includes analyses based on radar data only and on various comparisons of radar and rain gauge data. The rain gauge data are from the Oklahoma Mesonet. The results clearly show the effectiveness of the procedure as indicated by reduced bias in rainfall accumulation and improved behavior in other statistics.

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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.

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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.

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Bertrand Vignal, Gianmario Galli, Jürg Joss, and Urs Germann

Abstract

The vertical variability of radar reflectivity reduces the reliability of precipitation estimation by radar, especially in complex orography. This important source of error can, at least partially, be corrected for, if the vertical profile of radar reflectivity (VPR) is known. This work addresses three ways to determine VPR from volumetric radar data for correcting precipitation estimates. The first way uses a climatological profile. The second method, operational in Switzerland, takes the actual weather conditions into account: a mean profile is estimated directly from volumetric radar data collected close to the radar. The third way determines the identified profile, taking the variability of the VPRs in space into account. This approach yields local estimates of the profile (on areas of about 20 km × 20 km) based on an inverse method. Two cases, a convective event and a stratiform event, are used to illustrate the three ways for determining the VPR, and the resulting improvement, verified with rain gauges. An enlarged dataset of nine cases shows that a correction based on a climatological profile already improves the accuracy of rain estimates by radar significantly: the fractional standard error (FSE) is reduced from the noncorrected 44% to 31%. By correcting with a single, mean profile (averaged over 1 h using real-time data), the FSE is further reduced from 31% to 25%. Last, the use of 70 locally identified profiles leads to best results (FSE = 23%). A higher improvement (lower FSE) is obtained for the stratiform rain event than for the convective case.

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Thierry Pellarin, Guy Delrieu, Georges-Marie Saulnier, Hervé Andrieu, Bertrand Vignal, and Jean-Dominique Creutin

Abstract

A simulation procedure has been developed for use in predetermining the expected quality of rain-rate estimates that a given weather radar system operating in a mountainous region may obtain over a given hydrologic catchment. This first application of what is referred to as the “hydrologic visibility” concept focuses on the quantification of the rain-rate error resulting from the effects of ground clutter, beam blockage, and the vertical profile of reflectivity (VPR). The assessment of the impact of the space–time structure of the radar error in terms of discharge at the catchment outlet is also investigated using a distributed hydrologic model. A case study is presented for the Ardèche catchment in France using the parameters of two S-band weather radars operated by Météo-France at Nîmes and Bollène. Radar rain-rate error generation and rainfall–runoff simulations are performed using VPR and areal rainfall time series representative of the Cévennes rain climatology. The major impact of ground clutter on both rainfall and runoff estimates is confirmed. The “hydrologic compositing procedure,” based on the selection of the elevation angle minimizing the rain-rate error at a given point, is shown to be preferable to the “pseudo-CAPPI” procedure based on radar-range considerations only. An almost perfect ground-clutter reduction (GCR) technique is simulated in order to assess the effects of beam blockage and VPR alone. These error sources lead to severe and slight rain underestimations for the Nîmes and Bollène radars, respectively, over the Ardèche catchment. The results, indicating an amplification of the errors on the discharge parameters (peak discharge, runoff volume) compared to the areal rainfall error, are of particular interest. They emphasize the need for refined corrections for ground clutter, beam blockage, and VPR effects, in addition to the optimization of the radar location and scanning strategy, if hydrologic applications are foreseen.

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