Rain Gauge vs. Radar Measurements - Modelling an Extreme Rain Event with High Spatial Variability

2018 ◽  
pp. 413-418
Author(s):  
Tanja Vonach ◽  
Thomas Einfalt ◽  
Wolfgang Rauch ◽  
Manfred Kleidorfer
Keyword(s):  
Spatial Variability ◽  
Rain Gauge ◽  
Rain Event ◽  
Extreme Rain ◽  
Radar Measurements ◽  
High Spatial Variability

scholarly journals A Fuzzy Logic Technique for Identifying Nonprecipitating Echoes in Radar Scans

2006 ◽  
Vol 23 (9) ◽  
pp. 1157-1180 ◽  
Author(s):  
Marc Berenguer ◽  
Daniel Sempere-Torres ◽  
Carles Corral ◽  
Rafael Sánchez-Diezma
Keyword(s):  
Fuzzy Logic ◽  
Spatial Variability ◽  
Real Time ◽  
A Value ◽  
Radar Measurements ◽  
Anomalous Propagation ◽  
Radar Information ◽  
Fuzzy Logic Technique ◽  
Automatic Algorithm ◽  
High Spatial Variability

Abstract Because echoes caused by nonmeteorological targets significantly affect radar scans, contaminated bins must be identified and eliminated before precipitation can be quantitatively estimated from radar measurements. Under mean propagation conditions, clutter echoes (mainly caused by targets such as mountains or large buildings) can be found in almost fixed locations. However, in anomalous propagation conditions, new clutter echoes may appear (sometimes over the sea), and they may be difficult to distinguish from precipitation returns. Therefore, an automatic algorithm is needed to identify clutter on radar scans, especially for operational uses of radar information (such as real-time hydrology). In this study, a new algorithm is presented based on fuzzy logic, using volumetric data. It uses some statistics to highlight clutter characteristics (namely, shallow vertical extent, high spatial variability, and low radial velocities) to output a value that quantifies the possibility of each bin being affected by clutter (in order to remove those in which this factor exceeds a certain threshold). The performance of this algorithm was compared against that of simply removing mean clutter echoes. Satisfactory results were obtained from an exhaustive evaluation of this algorithm, especially in those cases in which anomalous propagation played an important role.

The Importance of Rainfall Distribution in Urban Drainage Operation

1992 ◽  
Vol 23 (2) ◽  
pp. 121-136 ◽  
Author(s):  
Fons Nelen ◽  
Annemarieke Mooijman ◽  
Per Jacobsen
Keyword(s):  
Real Time ◽  
Treatment Plant ◽  
Rain Gauge ◽  
Point Of View ◽  
Rain Event ◽  
Real Time Control ◽  
Rainfall Distribution ◽  
Statistical Point ◽  
Time Control ◽  
Spatially Distributed

A control simulation model, called LOCUS, is used to investigate the effects of spatially distributed rain and the possibilities to benefit from this phenomenon by means of real time control. The study is undertaken for a catchment in Copenhagen, where rainfall is measured with a network of 8 rain gauges. Simulation of a single rain event, which is assumed to be homogeneous, i.e. using one rain gauge for the whole catchment, leads to large over- and underestimates of the systems output variables. Therefore, when analyzing a single event the highest possible degree of rainfall information may be desired. Time-series simulations are performed for both an uncontrolled and a controlled system. It is shown that from a statistical point of view, rainfall distribution is NOT significant concerning the probability of occurrence of an overflow. The main contributing factor to the potential of real time control, concerning minimizing overflows, is to be found in the system itself, i.e. the distribution of available storage and discharge capacity. When other operational objectives are involved, e.g., to minimize peak flows to the treatment plant, rainfall distribution may be an important factor.

Simulation and analysis of the moist vortex associated with the extreme rain event of Ouagadougou in 2009

2019 ◽  
Vol 146 (726) ◽  
pp. 86-104
Author(s):  
Florent Beucher ◽  
Jean‐Philippe Lafore ◽  
Nicolas Chapelon
Keyword(s):  
Rain Event ◽  
Extreme Rain

scholarly journals Large spatial variations in the flux balance along the front of a Greenland tidewater glacier

2019 ◽  
Vol 13 (3) ◽  
pp. 911-925 ◽  
Author(s):  
Till J. W. Wagner ◽  
Fiamma Straneo ◽  
Clark G. Richards ◽  
Donald A. Slater ◽  
Laura A. Stevens ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Variability ◽  
Ocean Model ◽  
Complex Interplay ◽  
Flux Balance ◽  
Tidewater Glacier ◽  
Glacier Front ◽  
The Individual ◽  
High Spatial Variability ◽  
Frontal Ablation

Abstract. The frontal flux balance of a medium-sized tidewater glacier in western Greenland in the summer is assessed by quantifying the individual components (ice flux, retreat, calving, and submarine melting) through a combination of data and models. Ice flux and retreat are obtained from satellite data. Submarine melting is derived using a high-resolution ocean model informed by near-ice observations, and calving is estimated using a record of calving events along the ice front. All terms exhibit large spatial variability along the ∼5 km wide ice front. It is found that submarine melting accounts for much of the frontal ablation in small regions where two subglacial discharge plumes emerge at the ice front. Away from the subglacial plumes, the estimated melting accounts for a small fraction of frontal ablation. Glacier-wide, these estimates suggest that mass loss is largely controlled by calving. This result, however, is at odds with the limited presence of icebergs at this calving front – suggesting that melt rates in regions outside of the subglacial plumes may be underestimated. Finally, we argue that localized melt incisions into the glacier front can be significant drivers of calving. Our results suggest a complex interplay of melting and calving marked by high spatial variability along the glacier front.

scholarly journals A neural network model for short term river flow prediction

2006 ◽  
Vol 6 (4) ◽  
pp. 629-635 ◽  
Author(s):  
R. Teschl ◽  
W. L. Randeu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
River Flow ◽  
Radar Data ◽  
Rain Gauge ◽  
Huge Amount ◽  
Short Term ◽  
Flow Prediction ◽  
Spatial Coverage ◽  
Radar Measurements

Abstract. This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small convective shower cells, but managing such a huge amount of data is a demanding task for an artificial neural network. The method described here uses statistical analysis to reduce the amount of data and find an appropriate input vector. Based on this analysis, radar measurements (pixels) representing areas requiring approximately the same time to dewater are grouped.

scholarly journals High spatial variability of phytoplankton assessed by flow cytometry, in a dynamic productive coastal area, in spring: The eastern English Channel

2015 ◽  
Vol 154 ◽  
pp. 214-223 ◽  
Author(s):  
Simon Bonato ◽  
Urania Christaki ◽  
Alain Lefebvre ◽  
Fabrice Lizon ◽  
Melilotus Thyssen ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Spatial Variability ◽  
Coastal Area ◽  
English Channel ◽  
High Spatial Variability

scholarly journals Fecal source tracking and eDNA profiling in an urban creek following an extreme rain event

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Zachery R. Staley ◽  
Jun Dennis Chuong ◽  
Stephen J. Hill ◽  
Josey Grabuski ◽  
Shadi Shokralla ◽  
...  
Keyword(s):  
Source Tracking ◽  
Rain Event ◽  
Extreme Rain

scholarly journals Scattering Calculations for Asymmetric Raindrops during a Line Convection Event: Comparison with Radar Measurements

2018 ◽  
Vol 35 (6) ◽  
pp. 1169-1180 ◽  
Author(s):  
Sanja B. Manić ◽  
Merhala Thurai ◽  
V. N. Bringi ◽  
Branislav M. Notaroš
Keyword(s):  
Rain Event ◽  
Size Distributions ◽  
Surface Integral ◽  
Azimuthal Dependence ◽  
Industry Standard ◽  
Standard Code ◽  
Radar Measurements ◽  
Linear Depolarization Ratio ◽  
Drop Size Distributions ◽  
Differential Reflectivity

AbstractTwo-dimensional video disdrometer (2DVD) data from a line convection rain event are analyzed using the method of moments surface integral equation (MoM-SIE) via drop-by-drop polarimetric scattering calculations at C band that are compared with radar measurements. Drop geometry of asymmetric drop shapes is reconstructed from 2DVD measurements, and the MoM-SIE model is created by meshing the surface of the drop. The differential reflectivity Zdr calculations for an example asymmetric drop are validated against an industry standard code solution at C band, and the azimuthal dependence of results is documented. Using the MoM-SIE analysis on 2DVD drop-by-drop data (also referred to as simply MoM-SIE), the radar variables [Zh, Zdr, Kdp, ρhv] are computed as a function of time (with 1-min resolution) and compared to C-band radar measurements. The importance of shape variability of asymmetric drops is demonstrated by comparing with the traditional (or “bulk”) method, which uses 1-min averaged drop size distributions and equilibrium oblate shapes. This was especially pronounced for ρhv, where the MoM-SIE method showed lowered values (dip) during the passage of the line convection consistent with radar measurements, unlike the bulk method. The MoM-SIE calculations of [Zh, Zdr, Kdp] agree very well with the radar measurements, whereas linear depolarization ratio (LDR) calculations from the drop-by-drop method are found to be larger than the values from the bulk method, which is consistent with the dip in simulated and radar-measured ρhv. Our calculations show the importance of the variance of shapes resulting from asymmetric drops in the calculation of ρhv and LDR.

scholarly journals Estimating Rain Microphysical Characteristics Using S-Band Dual-Polarization Radar in South Korea

2020 ◽  
Vol 37 (6) ◽  
pp. 1067-1084 ◽  
Author(s):  
Hae-Lim Kim ◽  
Sung-Hwa Jung ◽  
Kun-Il Jang
Keyword(s):  
South Korea ◽  
Size Distribution ◽  
Empirical Relationship ◽  
Rain Gauge ◽  
Physical Parameters ◽  
Sampling Errors ◽  
Dual Polarization ◽  
Model Based ◽  
Microphysical Parameters ◽  
Radar Measurements

AbstractRaindrop size distribution (DSD) observed using a disdrometer can be represented by a constrained-gamma (C-G) DSD model based on the empirical relationship between shape (µ) and slope (Λ). The C-G DSD model can be used to retrieve DSDs and rain microphysical parameters from dual-polarization radar measurements of reflectivity (ZH) and differential reflectivity (ZDR). This study presents a new µ–Λ relationship to characterize rain microphysics in South Korea using a two-dimensional video disdrometer (2DVD) and Yong-in S-band dual-polarization radar. To minimize sampling errors from the 2DVD and radar measurements, measured size distributions are truncated by particle size and velocity-based filtering and compared with rain gauge measurement. The calibration biases of radar ZH and ZDR were calculated using the self-consistency constraint and vertical pointing measurements. The derived µ–Λ relationship was verified using the mass-weighted mean diameter (Dm) and standard deviation of the size distribution (σm), calculated from the 2DVD, for comparison with existing µ–Λ relationships for Florida and Oklahoma. The Dm–σm relationship derived from the 2DVD corresponded well with the µ–Λ relationship. The µ–Λ relationship derived for the Korean Peninsula was similar to Florida, and both generally had larger µ values than Oklahoma for the same Λ. The derived µ–Λ relationship was applied to retrieve DSD parameters from polarimetric radar data, and the retrieved DSDs and derived physical parameters were evaluated and compared with the 2DVD measurements. The polarization radar-based C-G DSD model characterized rain microphysics more accurately than the exponential DSD model. The C-G DSD model based on the newly derived µ–Λ relationship performed the best at retrieving rain microphysical parameters.

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