scholarly journals Improved radar rainfall estimation at ground level

2006 ◽  
Vol 6 (3) ◽  
pp. 323-342 ◽  
Author(s):  
S. M. Wesson ◽  
G. G. S. Pegram
Keyword(s):  
Effective Means ◽  
Ground Level ◽  
Radar Data ◽  
Rank Reduction ◽  
Radar Rainfall ◽  
Rainfall Events ◽  
Nearest Neighbours ◽  
Rainfall Type ◽  
Value Decomposition

Abstract. A technique has been developed to provide an estimate of the rainfall reaching the earth's surface by extrapolating radar data contained aloft to ground level, simultaneously estimating unknown data in the radar volume scan. The technique has been developed so as to be computationally fast, to work in real time and comprises the following steps. A rainfall classification algorithm is applied to separate the rainfall into two separate types: convective and stratiform rainfall. Climatological semivariograms based on the rainfall type are then defined and justified by testing, which result in a fast and effective means of determining the semivariogram parameters anywhere in the radar volume scan. Then, extrapolations to ground level are computed by utilising 3-D Universal and Ordinary Cascade Kriging; computational efficiency and stability in Kriging are ensured by using a nearest neighbours approach and a Singular Value Decomposition (SVD) matrix rank reduction technique. To validate the proposed technique, a statistical comparison between the temporally accumulated radar estimates and the Block Kriged raingauge estimates is carried out over matching areas, for selected rainfall events, to determine the quality of the rainfall estimates at ground level.

scholarly journals Radar rainfall estimates in an alpine environment using inverse hydrological modelling

2006 ◽  
Vol 9 ◽  
pp. 25-29 ◽  
Author(s):  
A. Marx ◽  
H. Kunstmann ◽  
A. Bárdossy ◽  
J. Seltmann
Keyword(s):  
Spatial Information ◽  
Global Radiation ◽  
Reaction Times ◽  
Radar Data ◽  
Hydrological Modelling ◽  
Radar Rainfall ◽  
Alpine Environment ◽  
Rainfall Events ◽  
Areal Precipitation

Abstract. The quality of hydrological modelling is limited due to the restricted availability of high resolution temporal and spatial input data such as temperature, global radiation, and precipitation. Radar-based rain measurements provide good spatial information. On the other hand, using radar data is accompanied by basic difficulties such as clutter, shielding, variations of Z/R-relationships, beam-resolution and attenuation. Instead of accounting for all errors involved separately, a robust Z/R-relationship is estimated in this study for the short range (up to 40 km distance) using inverse hydrological modelling for a continuous period of three months in summer 2001. River gauge measurements from catchment sizes around 100 km2 are used to estimate areal precipitation and finally Z/R-relationships using a calibrated hydrological model. The study is performed in the alpine Ammer catchment with very short reaction times of the river gauges to rainfall events.

scholarly journals Impact of the Altitudinal Gradients of Precipitation on the Radar QPE Bias in the French Alps

Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 306 ◽  
Author(s):  
Dominique Faure ◽  
Guy Delrieu ◽  
Nicolas Gaussiat
Keyword(s):  
Ground Level ◽  
Radar Data ◽  
Rain Gauge ◽  
Altitudinal Gradients ◽  
French Alps ◽  
Rain Gauges ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Radar Data Processing

In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until −40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation.

scholarly journals Radar rainfall image repair techniques

2004 ◽  
Vol 8 (2) ◽  
pp. 220-234 ◽  
Author(s):  
Stephen M. Wesson ◽  
Geoffrey G. S. Pegram
Keyword(s):  
Singular Value Decomposition ◽  
Ordinary Kriging ◽  
Singular Systems ◽  
Ground Level ◽  
Singular Value ◽  
Rainfall Data ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Ground Clutter ◽  
Value Decomposition

Abstract. There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality) on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the "screening effect" that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD) are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

scholarly journals Bollène-2002 Experiment: Radar Quantitative Precipitation Estimation in the Cévennes–Vivarais Region, France

2009 ◽  
Vol 48 (7) ◽  
pp. 1422-1447 ◽  
Author(s):  
Guy Delrieu ◽  
Brice Boudevillain ◽  
John Nicol ◽  
Benoît Chapon ◽  
Pierre-Emmanuel Kirstetter ◽  
...  
Keyword(s):  
Data Processing ◽  
Processing System ◽  
Ground Level ◽  
Radar Data ◽  
Rain Gauge ◽  
Space Time ◽  
Time Step ◽  
Radar Rainfall ◽  
Mountainous Regions ◽  
Study Results

Abstract The Bollène-2002 Experiment was aimed at developing the use of a radar volume-scanning strategy for conducting radar rainfall estimations in the mountainous regions of France. A developmental radar processing system, called Traitements Régionalisés et Adaptatifs de Données Radar pour l’Hydrologie (Regionalized and Adaptive Radar Data Processing for Hydrological Applications), has been built and several algorithms were specifically produced as part of this project. These algorithms include 1) a clutter identification technique based on the pulse-to-pulse variability of reflectivity Z for noncoherent radar, 2) a coupled procedure for determining a rain partition between convective and widespread rainfall R and the associated normalized vertical profiles of reflectivity, and 3) a method for calculating reflectivity at ground level from reflectivities measured aloft. Several radar processing strategies, including nonadaptive, time-adaptive, and space–time-adaptive variants, have been implemented to assess the performance of these new algorithms. Reference rainfall data were derived from a careful analysis of rain gauge datasets furnished by the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory. The assessment criteria for five intense and long-lasting Mediterranean rain events have proven that good quantitative precipitation estimates can be obtained from radar data alone within 100-km range by using well-sited, well-maintained radar systems and sophisticated, physically based data-processing systems. The basic requirements entail performing accurate electronic calibration and stability verification, determining the radar detection domain, achieving efficient clutter elimination, and capturing the vertical structure(s) of reflectivity for the target event. Radar performance was shown to depend on type of rainfall, with better results obtained with deep convective rain systems (Nash coefficients of roughly 0.90 for point radar–rain gauge comparisons at the event time step), as opposed to shallow convective and frontal rain systems (Nash coefficients in the 0.6–0.8 range). In comparison with time-adaptive strategies, the space–time-adaptive strategy yields a very significant reduction in the radar–rain gauge bias while the level of scatter remains basically unchanged. Because the Z–R relationships have not been optimized in this study, results are attributed to an improved processing of spatial variations in the vertical profile of reflectivity. The two main recommendations for future work consist of adapting the rain separation method for radar network operations and documenting Z–R relationships conditional on rainfall type.

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

2005 ◽  
Vol 5 (2) ◽  
pp. 267-274 ◽  
Author(s):  
A. Berne ◽  
M. ten Heggeler ◽  
R. Uijlenhoet ◽  
L. Delobbe ◽  
Ph. Dierickx ◽  
...  
Keyword(s):  
Preliminary Investigation ◽  
Weather Radar ◽  
Radar Data ◽  
Convective Precipitation ◽  
Initial State ◽  
Radar Rainfall ◽  
Bootstrap Analysis ◽  
Rainfall Events ◽  
The Mean ◽  
Areal Rainfall

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 gauge-calibrated (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 ~1600km2} 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.

scholarly journals Rainfall Estimates with Respect to Rainfall Types Using S-Band Polarimetric Radar in Korea

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 773
Author(s):  
Cheolhwan You ◽  
Miyoung Kang ◽  
Dong-In Lee
Keyword(s):  
Polarimetric Radar ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Rainfall Events ◽  
Stratiform Rain ◽  
Rainfall Variation ◽  
Precipitation Type ◽  
Rainfall Type ◽  
The Impact

To investigate the impact of rainfall type on rainfall estimation using polarimetric variables, rainfall relations such as those between rain rate (R) and specific differential phase (KDP), between R and KDP/differential reflectivity (ZDR), and between R and reflectivity (Z)/ZDR, were examined with respect to the precipitation type classified using drop size distributions (DSDs) measured by a disdrometer. The classification of rainfall type was assessed using four different methods: temporal rainfall variation; and the relations between intercept parameter (N0) and R; normalized intercept parameter (Nw) and median diameter (D0); and slope parameter (Λ) and R. The logN0–R relation discriminated between convective and stratiform rain with less standard deviation than the other methods as shown by the Z–ZDR scatter with respect to the rainfall types. The transition type from convective to stratiform and vice versa occurred in the stratiform rain region for all methods. To apply the classified rainfall relations to radar rainfall estimation, logNw and D0 were retrieved from polarimetric variables to discriminate the rainfall types in the radar domain. The DSD classification was verified with the vertical profile of reflectivity extracted at two positions corresponding to gage sites. Statistical analysis of four different rainfall events showed that rainfall estimation using the relations with precipitation type were better than those obtained without classification. The R(KDP,ZDR) relation with classification performed best on rainfall estimation for all rainfall events. The greatest improvement in rainfall estimation was obtained from R(Z,ZDR) with classification. We conclude that the classification of rainfall type leads to more accurate rainfall estimation. The different relations R(KDP), R(KDP,ZDR), and R(Z,ZDR) with respect to the rain types using polarimetric radar show improvement compared to estimation without consideration of rainfall type, in Korea.

Robust damped rank-reduction method for simultaneous denoising and reconstruction of 5-D seismic data

Geophysics ◽  
2020 ◽  
pp. 1-143
Author(s):  
Yapo Abolé Serge Innocent Oboué ◽  
Wei Chen ◽  
Hang Wang ◽  
Yangkang Chen
Keyword(s):  
Singular Value Decomposition ◽  
Seismic Data ◽  
Moving Average ◽  
Random Noise ◽  
Singular Value ◽  
Truncated Singular Value Decomposition ◽  
Rank Reduction ◽  
Residual Noise ◽  
Value Decomposition

We have developed a new method for simultaneous denoising and reconstruction of 5-D seismic data corrupted by random noise and missing traces. Several algorithms have been proposed for seismic data restoration based on rank-reduction methods. More recently, a damping operator has been introduced into the conventional truncated singular value decomposition (TSVD) formula to further remove residual noise, the presence of which disturbs the quality of the seismic results. Despite the success of the damped rank-reduction (DRR) method when the observed data have an extremely low signal-to-noise ratio (SNR), random noise is still a limiting factor for obtaining perfect quality of the result. Therefore, how to accurately solve the simultaneous denoising and reconstruction problem with high fidelity is still challenging. We assume that introducing only the damping operator into the TSVD formula is not enough to remove the random noise and restore the useful signal well. Here, by combining the soft thresholding operator and the moving-average filter, we first develop a new operator, which we call soft thresholding moving-average (STMA) operator. Then, by introducing the STMA operator into the DRR framework, we develop a new algorithm known as the robust damped rank-reduction (RDRR) method, which aims at mixing the advantages of the STMA operator and the damping operator. The STMA operator is applied to the Hankel matrix after damped truncated singular value decomposition (DTSVD) to better remove the residual noise. Examples of the proposed approach on synthetic and field 5-D seismic data demonstrate the better performance in terms of the visual examination and numerical test compared with the DRR approach. The proposed method aims at producing an effective low-rank filter and, thus, can perfectly enhance the SNR of the simultaneously denoised and reconstructed results with higher accuracy.

Rainfall Events as Paths of a Stochastic Process: Problems of Design Storm Analysis

1984 ◽  
Vol 16 (8-9) ◽  
pp. 131-138 ◽  
Author(s):  
Johannes Brummer
Keyword(s):  
Stochastic Process ◽  
Peak Flow ◽  
Rainfall Events ◽  
Peak Flows ◽  
Design Storm ◽  
Adequate Evaluation ◽  
Rainfall Patterns

Problems in the construction of design storms are expressed in mathematical terms. Introduced here is a concept for approximating natural peak flow values by means of the distribution of typical rainfall patterns. A comparison demonstrates the quality of this concept and the competency of some well-known design storms for the adequate evaluation of peak flows.

scholarly journals Multi-Task Optimization and Multi-Task Evolutionary Computation in the Past Five Years: A Brief Review

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 864
Author(s):  
Qingzheng Xu ◽  
Na Wang ◽  
Lei Wang ◽  
Wei Li ◽  
Qian Sun
Keyword(s):  
Evolutionary Computation ◽  
Explicit Knowledge ◽  
Optimization Problems ◽  
Effective Means ◽  
Typical Application ◽  
The Past ◽  
Current State ◽  
Evolution Algorithms ◽  
Application Fields

Traditional evolution algorithms tend to start the search from scratch. However, real-world problems seldom exist in isolation and humans effectively manage and execute multiple tasks at the same time. Inspired by this concept, the paradigm of multi-task evolutionary computation (MTEC) has recently emerged as an effective means of facilitating implicit or explicit knowledge transfer across optimization tasks, thereby potentially accelerating convergence and improving the quality of solutions for multi-task optimization problems. An increasing number of works have thus been proposed since 2016. The authors collect the abundant specialized literature related to this novel optimization paradigm that was published in the past five years. The quantity of papers, the nationality of authors, and the important professional publications are analyzed by a statistical method. As a survey on state-of-the-art of research on this topic, this review article covers basic concepts, theoretical foundation, basic implementation approaches of MTEC, related extension issues of MTEC, and typical application fields in science and engineering. In particular, several approaches of chromosome encoding and decoding, intro-population reproduction, inter-population reproduction, and evaluation and selection are reviewed when developing an effective MTEC algorithm. A number of open challenges to date, along with promising directions that can be undertaken to help move it forward in the future, are also discussed according to the current state. The principal purpose is to provide a comprehensive review and examination of MTEC for researchers in this community, as well as promote more practitioners working in the related fields to be involved in this fascinating territory.

Neurotechnology as a factor of the educational process transformation

2021 ◽  
pp. 98-13
Author(s):  
Л.Д. Александрова ◽  
Р.А. Богачева ◽  
Т.А. Чекалина ◽  
М.В. Максимова ◽  
В.И. Тимонина
Keyword(s):  
Effective Means ◽  
Individual Characteristics ◽  
Educational Process ◽  
Special Equipment ◽  
Research Areas ◽  
Long Time ◽  
Mental Abilities ◽  
The Individual ◽  
And Control

Изучение возможностей мозга для повышения качества обучения находится в центре внимания педагогической науки уже много лет. Развитие цифровизации позволило использовать в исследованиях специальное оборудование, с помощью которого можно оценивать и контролировать работу мозга, развивать умственные способности, познавательные функции и т. п. Нейротехнологии стали эффективным средством, позволяющим трансформировать образовательный процесс за счет подбора специального учебного контента с учетом индивидуальных особенностей обучающихся. Вместе с тем возникает необходимость в конкретизации терминологии и определении актуальных направлений исследований в данной области. For a long time, the study of the brain capabilities for the improvement of the quality of education has been an urgent direction in pedagogical science. Due to the development of digitalization, new areas of research have emerged related to the use of special equipment that makes it possible to assess and control brainwork, develop mental abilities, cognitive functions, etc. One of them is neurotechnology, which is an effective means of transforming the educational process: it offers educational content based on the individual characteristics of students. Thus, a need to concretize the terminology and determine the current research areas arises. The article aims to attempt to fill this gap with the help of a representative analysis of publications on neurotechnologies, as well as the essence of neuroeducation.

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