Effects of reflectivity gradients on rainfall estimates based on specific differential phase measurements

The rainfall estimates RDP based on the specific differential phase shift KDP are unaffected by errors in radar calibration and attenuation along the path. However, due to the signal fluctuations the estimates RDP can be very noisy at low and moderate rain rates. In order to improve the accuracy of the rainfall estimates KDP is to be estimated over a long path. In this way an error due to the reflectivity gradients, which could occur along a long path, can be introduced. In this paper we have analyzed two cases of reflectivity gradients along the path filled with rain; the first one, where the reflectivity varies linearly on dB scale that can be used to approximate regions with a steady increase or decrease of dBZ, and the other corresponding to sharp reflectivity gradient within the measurement cell, where an intense rainshaft is located adjacent in range to weak-echo regions. In both cases the error structure is discussed and the sensitivity of the normalized bias in KDP-based rainfall estimates is evaluated from a theoretical viewpoint and by simulation

Rainfall monitoring systems over an urban area: the city of Rome

In small catchments a very high space-time rainfall resolution is needed in order to obtain, with sufficient accuracy, flash flood nowcasting as well as monitoring of sewer systems. In this light, a radar meteorology campaign was conducted during the fall of 2001, over the city of Rome (Italy), using measurements collected by the polarimetric Doppler radar Polar 55C located in the south-east of the city at a distance of 15 km from the downtown and by a network consisting of 32 tipping bucket raingauges. A comparative analysis of the rainfall fields obtained using two interpolation methods (inverse-distance and kriging) with those obtained using radar rainfall measurements was performed. The overall performance of the different methods was evaluated using objective functions. Errors depending on the gauge density were weighed by changing the number of raingauges considered in the reconstructed rainfall fields. Copyright (c) 2005 John Wiley I Sons, Ltd

A technique to obtain a multiparameter radar rainfall algorithm using the probability matching procedure

The natural cumulative distributions of rainfall observed by a network of rain gauges and a multiparameter radar are matched to derive multiparameter radar algorithms for rainfall estimation. Conventional usage of multiparameter radar measurements for rainfall estimation has been associated with tracking the variability of the raindrop size distribution. The use of multiparameter radar measurements in a statistical framework to estimate rainfall is presented in this paper. The techniques developed in this paper are applied to the radar and rain gauge measurement of rainfall observed in central Florida and central Italy. Conventional pointwise estimates of rainfall are also compared. The probability matching procedure, when applied to the radar and surface measurements, shows that multiparameter radar algorithms can match the probability distribution function better than the reflectivity-based algorithms, thereby indicating the potential of multiparameter radar measurements for statistical approach to rainfall estimation. It is also shown that the multiparameter radar algorithm derived matching the cumulative distribution function of rainfall provides more accurate estimates of rainfall on the ground in comparison to any conventional reflectivity-based algorithm

Comparison of radar rainfall estimates and raingage measurements over the Central Apennines

Radar measurement of rainfall over mountainous regions is a difficult task due to the requirements of avoiding beam blockage as well as contamination by the melting layer. In this paper the raingage measurements and radar estimates of rainfall over two distinct locations in the central Apennines are compared to study the effect of beam blocking on radar measurements. A simple procedure is developed to estimate the percentage of beam blockage by the mountain ridges and, correspondingly, to correct the radar estimates of rainfall

Operational monitoring of rainfall over the Arno River basin using dual-polarized radar and rain gauges

Includes bibliographical references (page 1230).Reflectivity (ZH) and differential reflectivity (ZDR) measurements collected by Polar 55C over the Amo River basin in Italy are presented. The applicability of dual-polarization (ZDR)-based rainfall algorithms at C band in an operational setting is studied in conjunction with a network of rain gauges. Conventional pointwise comparison of radar and rain gauge estimates of rainfall, as well as statistical comparison of dual-polarization radar and rain gauge data via probability matching procedure, are presented. Error structure of reflectivity rainfall Z-R relation, as well as ZDR-based algorithms, is evaluated as a function of spatial and temporal averaging. Pointwise comparison, as well as statistical evaluation based on cumulative distribution function (CDF) matching, are used to show that in an operational environment with excessive ground-clutter contamination and attenuation problems the dual-polarization-based rainfall algorithm performs better than any arbitrary Z-R relation. In addition, it is shown that a dual-polarization (ZDR) algorithm obtained matching the CDFs performs better than the best possible Z-R relation

Rainfall stochastic modeling for runoff forecasting

Rainfall fields estimation over a catchment area is an important stage in many hydrological application. In this context weather radars have several advantages since a single site is able to obtain coverage over a vast area with very high temporal and spatial resolution and the advent of weather radar systems with dual polarization capability allowed progress on radar rainfall estimation and its hydro-meteorological applications. For these applications of radar data it was necessary to remove the ground clutter contamination with an algorithm based on the backscattering signal variance of the differential reflectivity. The calibration of the GDSTM model (Gaussian Displacements Spatial-Temporal Model), a cluster stochastic generation model in continuous space and time, is presented. In this model storms arrive in a Poisson process in time with cells occurring in each storm that cluster in space and time. The model is calibrated, using data collected by the weather radar Polar 55C located in Rome, inside a square area of 132x132 km2, with the radar at the center. The GDSTM is fitted to sequences of radar images with a time interval between the PPIs scans of 5 minutes. A generalized method of moments procedure is used for parameters estimation. For the validation of the ability of the model to reproduce the internal structure of rain event a geomorphological rainfall-runoff model based on width function (WFIUH) was calibrated using data simulated and observed data. Several rainfall fields are generated with the stochastic model and then they are used as input of the WFIUH model so that the forecasted discharges can be compared to the observed ones

Attenuation compensation technique and rainfall rate estimation using C-band dual polarization radar

The effectiveness of an attenuation correction procedure on the error structure of a C-band radar rainfall estimation is studied theoretically and by computer simulation. The iterative procedure to correct the radar observables affected by attenuation is based on the best-fit relationships between the absolute and differential reflectivity and the specific absolute and differential attenuation. This paper evaluates this attenuation correction procedure by a computer simulation to value the rainfall rate estimation errors

Multifractal analysis of radar rainfall fields over the area of Rome

A scale-invariance analysis of space and time rainfall events monitored by meteorological radar over the area of Rome (Italy) is proposed. The study of the scale-invariance properties of intense precipitation storms, particularly important in flood forecast and risk mitigation, allows to transfer rainfall information from the large scale predictive meteorological models to the small scale hydrological rainfall-runoff models. <P style=&quot;line-height: 20px;&quot;> Precipitation events are monitored using data collected by the polarimetric Doppler radar Polar 55C (ISAC-CNR), located 15 km Southeast from downtown. The meteorological radar provides the estimates of rainfall intensity over an area of about 10 000 km² at a resolution of 2&times;2 km² in space and 5 min in time. <P style=&quot;line-height: 20px;&quot;> Many precipitation events have been observed from autumn 2001 up to now. A scale-invariance analysis is performed on some of these events with the aim at exploring the multifractal properties and at understanding their dependence on the meteorological large-scale conditions

Comparison between multiparameter radar rainfall estimates and raingauge measurements during convective storms over Po valley

In this paper radar rainfall estimates obtained from C-band Doppler polarimetric weather radar GPM 500C are compared with rain gauge measurements collected by three rain gauge networks during a two months period from September 1 to October 30, 1996 when many convective thunderstorms developed over the Po valley area. In order to verify the capability and the accuracy of radar rainfall estimates two different techniques of comparison with the rain gauges have been analyzed: the first one is based on pointwise comparison of conventional and/or multiparameter radar estimates with the rain gauges measurements, the second utilizes the matching of the cumulative distribution function observed by the two sensors. The results are discussed considering two different areas, where the rain gauges are at a distance less than 40 km and at a distance ranging between 40 and 80 km, respectively

Rainfall estimation and ground clutter rejection with dual polarization weather radar

Conventional radars, used for atmospheric remote sensing, usually operate at a single polarization and frequency to estimate storm parameters such as rainfallrate and water content. Because of the high variability of the drop size distribution conventional radars do not succeed in obtaining detailed information because they just use horizontal reflectivity. The potentiality of the dual-polarized weather radar is investigated, in order to reject the ground-clutter, using differential reflectivity. In this light, a radar meteorology campaign was conducted over the city of Rome (Italy), collecting measurements by the polarimetric Doppler radar Polar 55C and by a raingauge network. The goodness of the results is tested by comparison of radar rainfall estimates with raingauges rainfall measurements