Identification of the bright band through the analysis of volumetric radar data

Sánchez-Diezma, Rafael; Zawadzki, Isztar; Sempere‐Torres, Daniel

doi:10.1029/1999jd900310

Cited by 74 publications

(50 citation statements)

References 17 publications

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“…(iii) The presented methodology assumes that the height of the brightband peak is known, and this is not always the case within the framework of radar data assimilation. Here, we propose using the information of the 0°C isotherm provided by the background term and/or the information about the brightband peaks identified by an algorithm such as the one proposed by Sanchez-Diezma et al (2000). (iv) The fact that the study has been carried out using long-term observations means that the resulting error covariance matrix is representative of the mean stratiform conditions and it may be not fully appropriate for each individual situation.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

A Study of the Error Covariance Matrix of Radar Rainfall Estimates in Stratiform Rain

Berenguer

Zawadzki

2008

Weather and Forecasting

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The contribution of various physical sources of uncertainty affecting radar rainfall estimates at the ground is quantified toward deriving and understanding the error covariance matrix of these estimates. The focus here is on stratiform precipitation at a resolution of 15 km, which is most relevant for data assimilation onto mesoscale numerical models. In the characterization of the error structure, the following contributions are considered: (i) the individual effect of the range-dependent error (associated with beam broadening and increasing height of radar measurements with range), (ii) the error associated with the transformation from reflectivity to rain rate due to the variability of drop size distributions, and (iii) the interaction of the first two, that is, the term resulting from the cross correlation between the effects of the range-dependent error and the uncertainty related to the variability of drop size distributions (DSDs).For this purpose a large database of S-band radar observations at short range (where reflectivity near the ground is measured and the beam is narrow) is used to characterize the range-dependent error within a simulation framework, and disdrometric measurements collocated with the radar data are used to assess the impact of the variability of DSDs. It is noted that these two sources of error are well correlated in the vicinity of the melting layer as result of the physical processes that determine the density of snow (e.g., riming), which affect both the DSD variability and the vertical profile of reflectivity.

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Section: Conclusion and Discussionmentioning

confidence: 99%

A Study of the Error Covariance Matrix of Radar Rainfall Estimates in Stratiform Rain

Berenguer

Zawadzki

2008

Weather and Forecasting

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“…These properties also form the basis of stratiformconvective separation techniques that have been proposed in the literature (e.g. Steiner et al, 1995;Sanchez-Diezma et al, 2000). Further research on this topic will ultimately contribute to the development of an operational VPR identification and correction algorithm, which has a high priority for the RMI.…”

Section: Analysis Of the Vertical Structure Of Precipitationmentioning

confidence: 99%

A preliminary investigation of radar rainfall estimation in the Ardennes region and a first hydrological application for the Ourthe catchment

Berne

Heggeler

Uijlenhoet

et al. 2005

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper presents a first assessment of the hydrometeorological potential of a C-band doppler weather radar recently installed by the Royal Meteorological Institute of Belgium near the village of Wideumont in the southern Ardennes region. An analysis of the vertical profile of reflectivity for two contrasting rainfall events confirms the expected differences between stratiform and convective precipitation. The mean areal rainfall over the Ourthe catchment upstream of Tabreux estimated from the Wideumont weather radar using the standard Marshall-Palmer reflectivity-rain rate relation shows biases between +128% and −42% for six selected precipitation events. For two rainfall events the radar-estimated mean areal rainfall is applied to the gaugecalibrated (lumped) HBV-model for the Ourthe upstream of Tabreux, resulting in a significant underestimation with respect to the observed discharge for one event and a closer match for another. A bootstrap analysis using the radar data reveals that the uncertainty in the hourly discharge from the ∼1600 km 2 catchment associated with the sampling uncertainty of the mean areal rainfall estimated from 10 rain gauges evenly spread over the catchment amounts to ±25% for the two events analyzed. This uncertainty is shown to be of the same order of magnitude as that associated with the model variables describing the initial state of the model.

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“…Stratification of the data based on the height of the 0 • -isotherm could represent a possible way of capturing the different rainfall regimes (e.g. Sánchez-Diezma et al, 2000;Mittermaier and Illingworth, 2003;Berenguer and Zawadzki, 2008).…”

Section: Conditional and Unconditional Biasesmentioning

confidence: 99%

Empirically based modelling of radar‐rainfall uncertainties for a C‐band radar at different time‐scales

Villarini

Krajewski

2009

Quart J Royal Meteoro Soc

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Radar-based estimates of rainfall are affected by several sources of systematic and random errors. The propagation of these uncertainties is required for improving the understanding and interpretation of the results obtained when radar-rainfall estimates are used as input or initial conditions. Despite the relevance of the problem, modelling of radar-rainfall uncertainties is still at an early stage. The authors apply an empirically based model in which the relation between true rainfall and radar-rainfall can be described as the product of a systematic distortion function (accounting for systematic biases) and random component (describing the remaining random errors). The proposed results are based on a large sample (more than six years) of data from a C-band radar (Wardon Hill) located in southwest England. The true ground rainfall is approximated by rain gauge measurements from a highly dense network deployed in the Brue catchment, located about 40 km from the radar site.The authors present results from their modelling of the radar-rainfall errors at four time-scales of hydrologic interest (5-and 15-minute, hourly and three-hourly) and 2 km spatial resolution, discussing the impact of spatial sampling errors on the proposed results.

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Identification of the bright band through the analysis of volumetric radar data

Cited by 74 publications

References 17 publications

A Study of the Error Covariance Matrix of Radar Rainfall Estimates in Stratiform Rain

A Study of the Error Covariance Matrix of Radar Rainfall Estimates in Stratiform Rain

A preliminary investigation of radar rainfall estimation in the Ardennes region and a first hydrological application for the Ourthe catchment

Empirically based modelling of radar‐rainfall uncertainties for a C‐band radar at different time‐scales

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