The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform

R J Moore - One of the best experts on this subject based on the ideXlab platform.

  • hydrological assessment of radar Raingauge merging techniques using the grid to grid model
    EGUGA, 2015
    Co-Authors: Paul S Mattingley, R J Moore, Steven J Cole, Steven C Wells, Kevin B Black
    Abstract:

    The relative performance of merging methods is commonly assessed at radar pixels coincident with Raingauge locations employing evaluation statistics such as the cross-validated Root Mean Square Error (RMSE). Such assessments indicate the extent to which the merged rainfall estimate can reproduce the Raingauge value omitted at each cross-validation step and given time but not whether this leads to improved hydrological model performance.

  • Raingauge quality control algorithms and the potential benefits for radar based hydrological modelling
    2012
    Co-Authors: Phil J Howard, Steve Cole, A Robson, R J Moore
    Abstract:

    Raingauges and weather radar are essential sources of rainfall information for hydrological modelling and forecasting. However, significant errors in Raingauge time-series can drastically affect Raingauge-only and combined radar-Raingauge rainfall estimates. In turn, these errors can have a negative impact on hydrological model calibration, performance and failure diagnosis. This study considers the automated quality-control of 15 minute rainfall totals obtained from 981 tipping-bucket Raingauges across England & Wales. The Grid-to-Grid distributed hydrological model, now operated by the Flood Forecasting Centre in support of national flood warning, is used with gridded rainfall estimates to assess the utility of the Raingauge quality-control procedures. Although a historical dataset is used here for demonstration and assessment purposes, the automated algorithms have been designed for implementation in real-time.

  • hydrological modelling using Raingauge and radar based estimators of areal rainfall
    Journal of Hydrology, 2008
    Co-Authors: Steven J Cole, R J Moore
    Abstract:

    Summary Three types of gridded rainfall estimator, based on Raingauge and/or radar observations, are considered and their merits for hydrological modelling explored. Gridded multiquadric surface fitting techniques are developed to form Raingauge-only and ‘Raingauge-adjusted radar’ rainfall estimators. A third estimator is provided by the unadjusted radar data which comes in raw or Nimrod form. The latter is a post-processed radar product that aims to apply physically based corrections. These estimators are assessed first from a rainfall perspective, and then from a hydrological perspective by using them to provide rainfall inputs to hydrological models and comparing their simulated flows to observations. The PDM, a lumped conceptual rainfall-runoff model, and the Grid-to-Grid Model, a distributed grid-based runoff and routing model, are used for the hydrological assessment over two upland catchments in northwest England. Important insights are gained into the performance of the different rainfall estimators in assessing rainfall over space and their use in lumped and distributed hydrological models. The need for frequent and spatially varying gauge-adjustment of radar is identified as crucial for the weather radar products assessed.

  • design of the hyrex Raingauge network
    Hydrology and Earth System Sciences, 2000
    Co-Authors: R J Moore, D. A. Jones, Valerie Isham
    Abstract:

    Abstract. Dense Raingauge experiments in the past have experienced difficulties in the automated recording of rainfall amount and timing which with the benefit of modern instrument technology are now less problematic. The HYdrological Radar EXperiment, HYREX, provided a timely opportunity to design and implement a dense Raingauge network in support of rainfall measurement and modelling research studies concerned with the use of weather radar in hydrology. The principles and random function theory underlying the design of this Raingauge network over the Brue catchment in south-west England are detailed in this paper. Keywords: Raingauge, design, network, rainfall, flood, spatial correlation

  • Static and dynamic calibration of radar data for hydrological use
    Hydrology and Earth System Sciences Discussions, 2000
    Co-Authors: S. J. Wood, D. A. Jones, R J Moore
    Abstract:

    The HYREX dense Raingauge network over the Brue catchment in Somerset, England is used to explore the accuracy of calibrated (Raingauge-adjusted) weather radar data. Calibration is restricted to the use of any single gauge within the catchment so as to simulate the conditions in a typical rainfall monitoring network. Combination of a single gauge and a radar estimate is used to obtain calibrated radar estimates, with the "calibration factor" varying dynamically from one time-frame to the next. Comparing this dynamic calibration with a static (long-term) calibration factor indicates the distance from a gauge over which the dynamic calibration is useful. A tapered calibration factor is implemented which behaves in the same way as the raw dynamic calibration at short distances, tending towards the static calibration factor at larger distances. This hybrid approach outperforms Raingauge, uncalibrated radar, and statically-calibrated radar estimates of rainfall for the majority of Raingauges in the catchment. The results provide valuable guidance on the density of Raingauge network to employ in combination with a weather radar for flood estimation and forecasting. Keywords: radar, Raingauge, calibration, rainfall, accuracy

F Russo - One of the best experts on this subject based on the ideXlab platform.

  • on the use of radar reflectivity for estimation of the areal reduction factor
    Natural Hazards and Earth System Sciences, 2006
    Co-Authors: Federico Lombardo, F Napolitano, F Russo
    Abstract:

    Abstract. In order to estimate the rainfall fields over an entire basin Raingauge, pointwise measurements need to be interpolated and the small-scale variability of rainfall fields can lead to biases in the rain rate estimation over an entire basin, above all for small or medium size mountainous and urban catchments. For these reasons, several Raingauges should be installed in different places in order to determine the spatial rainfall distribution during the evolution of the natural phenomena over the selected area. In technical applications, many empirical relations are used in order to deduce heavy areal rainfall, when just one Raingauge is available. In this work, we studied the areal reduction factor (ARF) using radar reflectivity maps collected with the Polar 55C, a C-band Doppler dual polarized coherent weather radar with polarization agility and with a 0.9° beamwidth. The radar rainfall estimates, for an area of 1 km2, were integrated for heavy rainfall with an upscaling process, until we had rainfall estimate for an area of 900 km2. The results obtained for a significant amount of data by using this technique are compared with the most important relations of the areal reduction factor reported in the literature.

  • Rainfall estimation and ground clutter rejection with dual polarization weather radar
    Advances in Geosciences, 2006
    Co-Authors: F. Lombardo, F Napolitano, F Russo, G. Scialanga, Luca Baldini, E. Gorgucci
    Abstract:

    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.

  • calibration of a rainfall runoff model using radar and Raingauge data
    Advances in Geosciences, 2005
    Co-Authors: V Lopez, F Napolitano, F Russo
    Abstract:

    Abstract. Since Raingauges give pointwise measurements the small scale variability of rainfall fields leads to biases on the estimation for the rainfall over the whole basin. In this context meteorological radars have several advantages since a single site is able to obtain coverage over a wide area with high temporal and spatial resolution. The purpose of this study is to compare the capability of the two different measurement systems in order to give correct input to drive rainfall-runoff models. Therefore a geomorphological model was calibrated, using firstly Raingauge data and secondly radar rainfall estimates, for the Treja river basin. In this way it is possible to determine different sets of parameters and the influence of measurement system in hydrological modelling. The results shown that radar rainfall data is able to improve significantly hydrographs reconstructions.

Yeoukoung Tung - One of the best experts on this subject based on the ideXlab platform.

  • establishing rainfall depth duration frequency relationships at daily Raingauge stations in hong kong
    Journal of Hydrology, 2013
    Co-Authors: Peishi Jiang, Yeoukoung Tung
    Abstract:

    Summary Rainfall intensity (depth)–duration–frequency (IDF/DDF) relationships provide information essential for urban stormwater drainage system design and other hydrosystem infrastructures. For catchments where drainage areas are small, rainfall DDF relationships with short duration can be established based on rainfall records from automatic Raingauges. Due to the progression of technology development, wide spread installation of automatic Raingauges does not happen until 2–3 decades ago. Therefore, record lengths at majority of automatic Raingauges are relatively short and the derived rainfall DDF relationships on the basis of at-site frequency analysis are potentially subject to significant sampling error. On the other hand, many conventional Raingauges exist long before automatic Raingauges were deployed. However, daily rainfall data with long records at conventional Raingauges are of limited use to establish rainfall DDF relationships in areas with small catchment size like Hong Kong where design storm duration significantly shorter than 24-h are needed. This study presents a practical methodological framework to derive rainfall DDF relationships with short duration at conventional Raingauge locations. The core components of the framework include the scaling model of rainfalls of different durations, the establishment of relationship between annual maximum daily rainfall and rolling-time 1440 min rainfall, the quantification of statistical features of estimated annual maximum 1440 min rainfalls, and the assessment of uncertainty of derived rainfall DDF relationships at conventional Raingauges.

  • Establishing rainfall depth–duration–frequency relationships at daily Raingauge stations in Hong Kong
    Journal of Hydrology, 2013
    Co-Authors: Peishi Jiang, Yeoukoung Tung
    Abstract:

    Summary Rainfall intensity (depth)–duration–frequency (IDF/DDF) relationships provide information essential for urban stormwater drainage system design and other hydrosystem infrastructures. For catchments where drainage areas are small, rainfall DDF relationships with short duration can be established based on rainfall records from automatic Raingauges. Due to the progression of technology development, wide spread installation of automatic Raingauges does not happen until 2–3 decades ago. Therefore, record lengths at majority of automatic Raingauges are relatively short and the derived rainfall DDF relationships on the basis of at-site frequency analysis are potentially subject to significant sampling error. On the other hand, many conventional Raingauges exist long before automatic Raingauges were deployed. However, daily rainfall data with long records at conventional Raingauges are of limited use to establish rainfall DDF relationships in areas with small catchment size like Hong Kong where design storm duration significantly shorter than 24-h are needed. This study presents a practical methodological framework to derive rainfall DDF relationships with short duration at conventional Raingauge locations. The core components of the framework include the scaling model of rainfalls of different durations, the establishment of relationship between annual maximum daily rainfall and rolling-time 1440 min rainfall, the quantification of statistical features of estimated annual maximum 1440 min rainfalls, and the assessment of uncertainty of derived rainfall DDF relationships at conventional Raingauges.

B Mehlig - One of the best experts on this subject based on the ideXlab platform.

  • Analysis of heavy rainfall events in North Rhine–Westphalia with radar and Raingauge data
    Atmospheric Research, 2005
    Co-Authors: Markus Jessen, Thomas Einfalt, Andre Stoffer, B Mehlig
    Abstract:

    Abstract Five heavy rainfall events were investigated with radar and Raingauge data. Special attention was paid to quality check and adjustment of radar data. Attenuation effects could be observed on both, C-Band and on X-Band radar. Adjustment of radar data to Raingauge values turned out to be difficult in the vicinity of heavy local rain cells. Four adjustment methods were analysed and radar data from different radar stations were compared. As a further result of this project, the spatial extent of the precipitation fields was identified by adjusted radar data and compared to Raingauge data. For each rainfall event, radar derived accumulated rainfall images and catchment time series were produced.

  • analysis of heavy rainfall events in north rhine westphalia with radar and Raingauge data
    Atmospheric Research, 2005
    Co-Authors: Markus Jessen, Thomas Einfalt, Andre Stoffer, B Mehlig
    Abstract:

    Abstract Five heavy rainfall events were investigated with radar and Raingauge data. Special attention was paid to quality check and adjustment of radar data. Attenuation effects could be observed on both, C-Band and on X-Band radar. Adjustment of radar data to Raingauge values turned out to be difficult in the vicinity of heavy local rain cells. Four adjustment methods were analysed and radar data from different radar stations were compared. As a further result of this project, the spatial extent of the precipitation fields was identified by adjusted radar data and compared to Raingauge data. For each rainfall event, radar derived accumulated rainfall images and catchment time series were produced.

  • comparison of radar and Raingauge measurements during heavy rainfall
    Water Science and Technology, 2005
    Co-Authors: Thomas Einfalt, Markus Jessen, B Mehlig
    Abstract:

    Five heavy small-scale rainfall events in North Rhine-Westphalia (Germany) were investigated with radar and Raingauge data. Special attention was paid to quality check and adjustment of radar data. Attenuation effects could be observed on both, C-Band and on X-Band radar. Adjustment of radar data to Raingauge values turned out to be very difficult in the vicinity of heavy local rain cells. For the five affected regions the precipitation was quantified in the form of areal time series and cumulated radar images. As further result of this project, the spatial extent of the precipitation fields was identified and compared with radar and Raingauge data.

J F Elliott - One of the best experts on this subject based on the ideXlab platform.

  • flood estimation using radar and Raingauge data
    Journal of Hydrology, 2000
    Co-Authors: Russell G Mein, T D Keenan, J F Elliott
    Abstract:

    Flood hydrographs for the Finniss River catchment in Darwin, Australia, were calculated using different approaches to estimate the input rainfalls from the available radar and Raingauge data. The rainfall estimation methods were: (1) using Raingauge data alone; (2) using kriging of the Raingauge data; (3) using radar data alone and (4) using cokriging of both radar and Raingauge data. Both probability matching and power law methods were used to estimate rainfall from measured radar reflectivities. The results showed that rainfall estimated by cokriging considerably improved flood estimates, because it optimally combines both the Raingauge and radar data to improve the estimate of subcatchment rainfall.