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Journal ArticleDOI

Review of the Different Sources of Uncertainty in Single Polarization Radar-Based Estimates of Rainfall

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TLDR
In this paper, the authors provide an extensive literature review of the principal sources of error affecting single polarization radar-based rainfall estimates, including radar miscalibration, attenuation, ground clutter and anomalous propagation, beam blockage, variability of the Z-R relation, range degradation, vertical variability of precipitation system, vertical air motion and precipitation drift.
Abstract
It is well acknowledged that there are large uncertainties associated with radar-based estimates of rainfall. Numerous sources of these errors are due to parameter estimation, the observational system and measurement principles, and not fully understood physical processes. Propagation of these uncertainties through all models for which radar-rainfall are used as input (e.g., hydrologic models) or as initial conditions (e.g., weather forecasting models) is necessary to enhance the understanding and interpretation of the obtained results. The aim of this paper is to provide an extensive literature review of the principal sources of error affecting single polarization radar-based rainfall estimates. These include radar miscalibration, attenuation, ground clutter and anomalous propagation, beam blockage, variability of the Z–R relation, range degradation, vertical variability of the precipitation system, vertical air motion and precipitation drift, and temporal sampling errors. Finally, the authors report some recent results from empirically-based modeling of the total radar-rainfall uncertainties. The bibliography comprises over 200 peer reviewed journal articles.

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Journal ArticleDOI

A decade of Predictions in Ungauged Basins (PUB)—a review

TL;DR: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS) launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power as discussed by the authors.
Journal ArticleDOI

Using the Climate Forecast System Reanalysis as weather input data for watershed models

TL;DR: In this paper, a method for using the Climate Forecast System Reanalysis (CFSR) global meteorological dataset to obtain historical weather data and demonstrates the application to modelling five watersheds representing different hydroclimate regimes.
Journal ArticleDOI

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

Abstract: This review and commentary sets out the need for authoritative and concise information on the expected error distributions and magnitudes in observational data We discuss the necessary components of a benchmark of dominant data uncertainties and the recent developments in hydrology which increase the need for such guidance We initiate the creation of a catalogue of accessible information on characteristics of data uncertainty for the key hydrological variables of rainfall, river discharge and water quality (suspended solids, phosphorus and nitrogen) This includes demonstration of how uncertainties can be quantified, summarizing current knowledge and the standard quantitative results available In particular, synthesis of results from multiple studies allows conclusions to be drawn on factors which control the magnitude of data uncertainty and hence improves provision of prior guidance on those uncertainties Rainfall uncertainties were found to be driven by spatial scale, whereas river discharge uncertainty was dominated by flow condition and gauging method Water quality variables presented a more complex picture with many component errors For all variables, it was easy to find examples where relative error magnitudes exceeded 40% We consider how data uncertainties impact on the interpretation of catchment dynamics, model regionalization and model evaluation In closing the review, we make recommendations for future research priorities in quantifying data uncertainty and highlight the need for an improved ‘culture of engagement’ with observational uncertainties Copyright © 2012 John Wiley & Sons, Ltd
Journal ArticleDOI

Rainfall uncertainty in hydrological modelling: An evaluation of multiplicative error models

TL;DR: In this article, the authors used data from a dense gauge/radar network in the Mahurangi catchment (New Zealand) to directly evaluate the form of basic statistical rainfall error models.
References
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Book

Characterization of ceramics

TL;DR: This article reviewed the principles of Doppler radar and emphasized the quantitative measurement of meteorological parameters, and illustrated the relation of radar data and images to atmospheric phenomena such as tornadoes, microbursts, waves, turbulence, density currents, hurricanes, and lightning.
Book

Polarimetric Doppler Weather Radar: Principles and Applications

TL;DR: A detailed introduction to the principles of Doppler and polarimetric radar, focusing in particular on their use in the analysis of weather systems, is provided in this article, where the authors discuss background topics such as electromagnetic scattering, polarization, and wave propagation.
Journal ArticleDOI

The WSR-88D Rainfall Algorithm

TL;DR: In this paper, a detailed description of the operational WSR-88D rainfall estimation algorithm is presented, and the processing steps to quality control and compute the rainfall estimates are described, and current deficiencies and future plans for improvement are discussed.
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