scholarly journals Small-Scale Rainfall Variability Impacts Analyzed by Fully-Distributed Model Using C-Band and X-Band Radar Data

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1273 ◽  
Author(s):  
Igor Paz ◽  
Bernard Willinger ◽  
Auguste Gires ◽  
Bianca Alves de Souza ◽  
Laurent Monier ◽  
...  
Keyword(s):  
Data Quality ◽  
Rainfall Variability ◽  
Drainage System ◽  
Radar Data ◽  
Rainfall Data ◽  
Distributed Model ◽  
Small Scale ◽  
Distributed Models ◽  
X Band ◽  
Spatio Temporal

Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called “Multi-Hydro” to study small-scale rainfall variability and its hydrological impacts. The catchment modelled is a semi-urban area located in the southwest region of Paris, an area that has been previously partially validated. At this time, we make some changes to the model, henceforth using its drainage system globally, and we investigate the influence of small-scale rainfall variability by modelling three rainfall events with two different rainfall data inputs: the C-band radar data provided by Météo-France at a 1 km × 1 km × 5 min resolution, and the new X-band radar (recently installed at Ecole des Ponts, France) data at a resolution of 250 m × 250 m × 3.41 min, thereby presenting the gains of better resolution (with the help of Universal Multifractals). Finally, we compare the Multi-Hydro hydrological results with those obtained using an operational semi-distributed model called “Optim Sim” over the same area to revalidate Multi-Hydro modelling, and discuss the model’s limitations and the impacts of data quality and resolution, observing the difficulties associated with semi-distributed models when accounting the spatial variability of weather radar data. This work concludes that it may be useful in future to improve rainfall data acquisition, aiming for better spatio-temporal resolution (now achieved by the weather dual-polarized X-band radars) and data quality when considering small-scale rainfall variability, and to merge deterministic, fully-distributed and stochastic models into a hybrid model which would be capable of taking this small-scale rainfall variability into account.

scholarly journals Automated convective and stratiform precipitation estimation in a small mountainous catchment using X-band radar data in Central Spain

2016 ◽  
Vol 19 (2) ◽  
pp. 315-330 ◽  
Author(s):  
Carolina Guardiola-Albert ◽  
Carlos Rivero-Honegger ◽  
Robert Monjo ◽  
Andrés Díez-Herrero ◽  
Carlos Yagüe ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Radar Data ◽  
Rain Gauge ◽  
Spatial And Temporal Variability ◽  
Central Spain ◽  
Small Catchment ◽  
Mountainous Catchment ◽  
X Band ◽  
Precipitation Estimation ◽  
Spatio Temporal

For the purposes of weather nowcasting, flood risk monitoring and water resources assessment, it is often difficult to achieve a reliable spatio-temporal representation of rainfall due to a low rain gauge network density. However, quantitative precipitation estimation (QPE) has acquired new prospects with the introduction of weather radars, thanks to their higher spatio-temporal resolution. Although a wide number of QPE algorithms are available for using C-band radar data, only a few studies have employed X-band radar. In this study the microscale rainfall variability in a small catchment is automatically measured using short-range X-band radar variograms and classifying precipitation into convective and stratiform types with a recently published index. The aim is to apply a straightforward geostatistical algorithm, named ordinary kriging of radar errors (OKRE), to integrate X-band radar and rain gauge measurements in a mountainous catchment (15 km2) in central Spain. As expected, convective events presented higher estimation errors due to their complex spatial and temporal variability. Despite this fact, errors are sufficiently small and results are reliable rainfall estimations. The two main contributions of this work are the adaptation of the OKRE method to small spatial scales and its application automatically differentiating between convective and stratiform events.

A dense network of rain gauges within an urban area: Rainfall uncertainty and variability

2021 ◽  
Author(s):  
Luc Neppel ◽  
Pierre Marchand ◽  
Pascal Finaud-Guyot ◽  
Vincent Guinot ◽  
Christian Salles
Keyword(s):  
Spatial Variability ◽  
Urban Area ◽  
Urban Areas ◽  
Rainfall Variability ◽  
Temporal Structure ◽  
Drainage System ◽  
Spatiotemporal Variability ◽  
Small Scale ◽  
Rain Gauges ◽  
Rain Gauges Network

<p>This study presents a new high density rain gauges network installed in urban area to study spatio-temporal structure and variability of precipitation at small scales. The preliminary results concerning gauges calibration and characterization of the rainfall spatial variability at fine scale are discussed.</p><p>In urban areas, the impervious surfaces connected to the drainage system leads to highly dynamic flows. The flood and runoff risk characterization requires  fine spatiotemporal scale to describe hydrological model input data :rainfall within spatial scale of less than 1km and temporal scale close to 1minis necessary for urban hydrological applications and risk assessment. In order to characterize small-scale rainfall spatiotemporal variability, a dense rain gauges network is deployed at Montpellier (France) with inter-gauges distances from 100m to 1km. Currently, 9 tipping bucket rain gauges  associated with 9 anemometers are acquiring rainfall and wind norm intensity every minutes. The network density and extension will be increased soon.</p><p>The first year measurements highlight a spatial variability of the 1-minute rainfall at the subkilometer scale. This observed variability is analyzed in view of the measurement uncertainty (gauge calibration, gauge error, bias due to the gauge location) to identify the natural rainfall variability.</p><p>This contribution presents the new densely extensive rainfall  network measurement, the typing bucket raingauge calibration and highlights that the observed 1-minute rainfall intensity variability  is significant and cannot be only explained by the measurement uncertainties.</p>

scholarly journals Characterization of dynamic evolution of the spatio-temporal variation of rain-field in Hong Kong

2015 ◽  
Vol 47 (2) ◽  
pp. 468-482 ◽  
Author(s):  
Peng Liu ◽  
Yeou-Koung Tung
Keyword(s):  
Hong Kong ◽  
Spatial Structure ◽  
Temporal Structure ◽  
Radar Data ◽  
Small Scale ◽  
Large Set ◽  
Time Space ◽  
Main Challenge ◽  
Geostatistical Approach ◽  
Spatio Temporal

A significant part of Hong Kong has hilly terrain with relatively short flow concentration time and, hence, is susceptible to the threat of flash floods and landslides during intense convective thunderstorms and tropical cyclones. For places like Hong Kong, a rainfall model that could adequately capture small-scale temporal and spatial variations would be highly desirable. The main challenge in rain-field modeling is to capture and describe the dynamic time-space evolution of the rainfall during rainstorm events. In this study, radar data with a high spatial (1 km2) and temporal (6 min) resolution of four rainstorm events in Hong Kong are analyzed. A geostatistical approach based on indicator variograms of rain-fields is used. The spatial structure of a rain-field is found to be highly anisotropic and should be adequately considered in the model. Variability of the spatial structure of a rain-field was described well by the main features of the variograms. Moreover, it is possible to identify whether multiple rainstorm centers exist by comparing the mean length and range. In order to establish reliable statistics on the spatial and temporal structure of rain-fields in Hong Kong, this approach could be applied to a large set of rainstorm events in this same region in the future.

scholarly journals Point-Based Rainfall Intensity Information System in Mt. Merapi Area by X-Band Radar

2019 ◽  
Vol 14 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Santosa Sandy Putra ◽  
Banata Wachid Ridwan ◽  
Kazuki Yamanoi ◽  
Makoto Shimomura ◽  
Sulistiyani ◽  
...  
Keyword(s):  
Satellite Data ◽  
Early Warning Systems ◽  
Radar Data ◽  
Rain Gauge ◽  
Data Grid ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Rain Gauge Data ◽  
X Band ◽  
Gauge Data

An X-band radar was installed in 2014 at Merapi Museum, Yogyakarta, Indonesia, to monitor pyroclastic and rainfall events around Mt. Merapi. This research aims to perform a reliability analysis of the point extracted rainfall data from the aforementioned newly installed radar to improve the performance of the warning system in the future. The radar data was compared with the monitored rain gauge data from Balai Sabo and the IMERG satellite data from NASA and JAXA (The Integrated Multi-satellitE Retrievals for GPM), which had not been done before. All of the rainfall data was compared on an hourly interval. The comparisons were conducted based on 11 locations that correspond to the ground rainfall measurement stations. The locations of the rain gauges are spread around Mt. Merapi area. The point rainfall information was extracted from the radar data grid and the satellite data grid, which were compared with the rain gauge data. The data were then calibrated and adjusted up to the optimum state. Based on January 2017–March 2018 data, it was obtained that the optimum state has a NSF value of 0.41 and R2value of 0.56. As a result, it was determined that the radar can capture around 79% of the hourly rainfall occurrence around Mt. Merapi area during the chosen calibration period, in comparison with the rain gauge data. The radar was also able to capture nearby 40–50% of the heavy rainfall events that pose risks of lahar. In contrast, the radar data performance in detecting drizzling and light rain types were quite precise (55% of cases), although the satellite data could detect slightly better (60% of cases). These results indicate that the radar sensitivity in detecting the extreme rainfall events must receive higher priority in future developments, especially for applications to the existing Mt. Merapi lahar early warning systems.

scholarly journals An approach to combine radar and gauge based rainfall data under consideration of their qualities in low mountain ranges of Saxony

2010 ◽  
Vol 10 (3) ◽  
pp. 429-446 ◽  
Author(s):  
N. Jatho ◽  
T. Pluntke ◽  
C. Kurbjuhn ◽  
C. Bernhofer
Keyword(s):  
Data Quality ◽  
Cost Function ◽  
Input Data ◽  
Radar Data ◽  
Combination Method ◽  
Small Scale ◽  
Quality Information ◽  
Target Area ◽  
Sampling Point ◽  
System Quality

Abstract. An approach to combine gauge and radar data and additional quality information is presented. The development was focused on the improvement of the diagnostic for temporal (one hour) and spatial (1×1 km2) highly resolved precipitation data. The method is embedded in an online tool and was applied to the target area Saxony, Germany. The aim of the tool is to provide accurate spatial rainfall estimates. The results can be used for rainfall run-off modelling, e.g. in a flood management system. Quality information allows a better assessment of the input data and the resulting precipitation field. They are stored in corresponding fields and represent the static and dynamic uncertainties of radar and gauge data. Objective combination of various precipitation and quality fields is realised using a cost function. The findings of cross validation reveal that the proposed combination method merged the benefits and disadvantages of interpolated gauge and radar data and leads to mean estimates. The sampling point validation implies that the presented method slightly overestimated the areal rain as well as the high rain intensities in case of convective and advective events, while the results of pure interpolation method performed better. In general, the use of presented cost function avoids false rainfall amount in areas of low input data quality and improves the reliability in areas of high data quality. It is obvious that the combined product includes the small-scale variability of radar, which is seen as the important benefit of the presented combination approach. Local improvements of the final rain field are possible due to consideration of gauges that were not used for radar calibration, e.g. in topographic distinct regions.

scholarly journals Snake Line Performance Applying Single Pixel X-Band MP Radar Data (Case of Mt. Merapi Area, Indonesia)

2019 ◽  
Vol 5 (3) ◽  
pp. 201 ◽  
Author(s):  
Ani Hairani ◽  
Adam Pamudji Rahardjo ◽  
Djoko Legono ◽  
Istiarto Istiarto
Keyword(s):  
Short Duration ◽  
Time Use ◽  
Heavy Rainfall ◽  
Rainfall Intensity ◽  
Radar Data ◽  
Disaster Risk ◽  
Rainfall Data ◽  
High Demand ◽  
X Band ◽  
Single Pixel

The short-duration-rainfall monitoring techniques have become important recently due to the high demand for disaster risk miti­gation. Such techniques produce important information on the rainfall intensity during heavy rainfall in the form of snake line. At the same time, use of X-Band Multi-Parameter Radar (XMP Radar) in rainfall monitoring has increased significantly be­cause of its capacity to cover wide area. An assessment on the snake line performance that was developed based on XMP Radar and ground rainfall monitoring instrument (i.e. Automatic Rainfall Recorder or ARR) has been applied to Mt. Merapi area, Java, Indonesia. Selected rainfall data of November-December 2018 were examined. The assessment used a single pixel of radar data at the location of the ARR. The result shows that rainfall data obtained from XMP Radar are lower than those from ARR. The computed snake line obtained from XMP Radar differs from that from ARR data. The XMP Radar underestimates the warning level by about two level out of four.

Comparison of radar and raingauge measurements during heavy rainfall

2005 ◽  
Vol 51 (2) ◽  
pp. 195-201 ◽  
Author(s):  
T. Einfalt ◽  
M. Jessen ◽  
B. Mehlig
Keyword(s):  
Time Series ◽  
Heavy Rainfall ◽  
Radar Data ◽  
Spatial Extent ◽  
Small Scale ◽  
Rainfall Events ◽  
Radar Images ◽  
X Band ◽  
Raingauge Data ◽  
Quality Check

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.

scholarly journals Integration between X-Band Radar and Buoy Sea State Monitoring

2016 ◽  
Author(s):  
Giovanni Ludeno ◽  
Ferdinando Reale ◽  
Francesco Raffa ◽  
Fabio Dentale ◽  
Francesco Soldovieri ◽  
...  
Keyword(s):  
Radar Data ◽  
Small Scale ◽  
State Monitoring ◽  
Sea State ◽  
Simultaneous Acquisition ◽  
X Band ◽  
Definite Improvement ◽  
Good Consistency ◽  
Monitoring Activity ◽  
Important Progress

Abstract. The paper presents the results of an integrated buoy and X-Band radar sea state monitoring activity carried out on the southern coast of Sicily. The work involved the integration of buoy and radar data, as well as the simultaneous acquisition of Significant Wave Height (SWH) values from two similar radar sets located at a slight distance from each other – a rare and fortunate circumstance which took place during two storms in the winter 2014–2015. Good consistency and repeatability was reached between the two radars and the reliability of X-Band radar as a wave monitoring system was confirmed by the comparison with the buoy wave meter. A further and important result of the work is the knowledge gained on the short spatial and temporal fluctuations of the sea state: while such Small Scale Storm Variations (SSSV) cannot be easily discriminated from electromagnetic effects and from algorithm artefacts, some important progress has been done towards the identification of this phenomenon. Integration of different sensors is the key to a definite improvement of sea state monitoring for most coastal applications.

Experimental and numerical studies of small-scale rainfall measurements and variability

1998 ◽  
Vol 37 (11) ◽  
pp. 131-138 ◽  
Author(s):  
W. F. Krajewski ◽  
A. Kruger ◽  
V. Nespor
Keyword(s):  
High Resolution ◽  
Wind Velocity ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Data Logger ◽  
Radar Rainfall ◽  
Numerical Studies ◽  
X Band

A high-resolution rainfall observatory was established at the Iowa Institute of Hydraulic Research to support studies of small scale rainfall variability. It includes a vertically pointing X-band radar, a two-dimensional video disdrometer, an optical rain gauge, a standard tipping bucket raingauge, and high temporal resolution sensors for measurements of wind velocity and direction, temperature, humidity, and pressure. All the instruments are collocated. The observatory is being upgraded to include a Doppler processor for the radar, a mobile platform to enable participation in community-organized hydrometeorological experiments, and a network of about 15 high-resolution raingauges to be installed at a nearby airport. The airport network design includes innovative concepts of dual sensors constituting a single observational point, connected to the same data logger. The observational points are separated with distances ranging from 10-1000 metres. We present comparisons of data collected by the various sensors and discuss implications for radar-rainfall estimation. The capabilities of the experimental setup at IIHR will facilitate numerical studies of rainfall measurements. In particular, we present results of computational fluid dynamics calculations of the measurement error of the video disdrometer based on the high resolution observations of drop size distribution and wind velocity.

Distributed Modeling Of Building Systems Through Cyber-Physical Integration

2019 ◽  
pp. 12-17
Keyword(s):  
Data Structure ◽  
Operating Conditions ◽  
Physical Models ◽  
Distributed Model ◽  
Physical Processes ◽  
Distributed Modeling ◽  
Distributed Models ◽  
Operating Modes ◽  
Building Systems ◽  
Important Practical Application

This article describes the proposed approaches to creating distributed models that can, with given accuracy under given restrictions, replace classical physical models for construction objects. The ability to implement the proposed approaches is a consequence of the cyber-physical integration of building systems. The principles of forming the data structure of designed objects and distributed models, which make it possible to uniquely identify the elements and increase the level of detail of such a model, are presented. The data structure diagram of distributed modeling includes, among other things, the level of formation and transmission of signals about physical processes inside cyber-physical building systems. An enlarged algorithm for creating the structure of the distributed model which describes the process of developing a data structure, formalizing requirements for the parameters of a design object and its operating modes (including normal operating conditions and extreme conditions, including natural disasters) and selecting objects for a complete group that provides distributed modeling is presented. The article formulates the main approaches to the implementation of an important practical application of the cyber-physical integration of building systems - the possibility of forming distributed physical models of designed construction objects and the directions of further research are outlined.

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