Combining weather radar and raingauge data for hydrologic applications

Author(s):  
Cinzia Mazzetti ◽  
Ezio Todini
Keyword(s):  
2008 ◽  
Vol 18 (2) ◽  
pp. 11-17
Author(s):  
Gustavo Cerda Villafaña ◽  
Sergio Ledesma ◽  
Dawei Han

The application of ANNs (Artifi cial Neural Networks) has been studied by many researchers in modelling rainfall runoff processes. However, the work so far has been focused on the rainfall data from traditional raingauges. Weather radar is a modern technology which could provide high resolution rainfall in time and space. In this study, a comparison in rainfall runoff modelling between the raingauge and weather radar has been carried out. The data were collected from Brue catchment in Southwest of England, with 49 raingauges covering 136 km2 and two C-band weather radars. This raingauge network is extremely dense (for research purposes) and does not represent the usual raingauge density in operational flood forecasting systems. The ANN models were set up with both lumped and spatial rainfall input. The results showed that raingauge data outperformed radar data in all the events tested, regardless of the lumped and spatial input.


2014 ◽  
Vol 134 (4) ◽  
pp. 204-210 ◽  
Author(s):  
Yuki Hirano ◽  
Kouichi Maruo ◽  
Shigeharu Shimamura ◽  
Satoru Yoshida ◽  
Tomoo Ushio ◽  
...  
Keyword(s):  

2007 ◽  
Vol 66 (8) ◽  
pp. 715-727 ◽  
Author(s):  
F. J. Yanovsky ◽  
C. M. H. Unal ◽  
H. W. J. Russchenberg ◽  
L. P. Ligthart

2016 ◽  
Vol 75 (5) ◽  
pp. 463-475
Author(s):  
V. V. Naumenko ◽  
A. V. Totsky ◽  
G. I. Khlopov ◽  
O. A. Voitovych ◽  
J. T. Astola

Author(s):  
VN Nikitina ◽  
GG Lyashko ◽  
NI Kalinina ◽  
EN Dubrovskaya ◽  
VP Plekhanov

Summary. Introduction: Location of weather surveillance radars near settlements, in residential areas and on airport premises makes it important to ensure safe levels of electromagnetic fields (EMF) when operating these radio transmitters. EMF maximum permissible levels for weather radars developed in the 1980s are outdated. Our objective was to analyze modern weather surveillance radars to develop proposals for improvement of radar-generated radiofrequency field monitoring. Materials and methods: We studied trends in meteorological radiolocation and technical characteristics of modern weather radars for atmospheric sensing and weather alerts, analyzed regulations for EMF measurements and hygienic assessment, and measured radiofrequency fields produced by weather radar antennas in open areas and at workplaces of operators. Results: We established that modern types of weather radars used in upper-air sensing systems and storm warning networks differ significantly in terms of technical characteristics and operating modes from previous generations. Developed in the 1980s, current hygienic standards for human exposures to radiofrequency fields from weather radar antennas are obsolete. Conclusions: It is essential to develop an up-to-date regulatory and method document specifying estimation and instrumental monitoring of EMF levels generated by weather radars and measuring instruments for monitoring of pulse-modulated electromagnetic radiation.


1998 ◽  
Vol 37 (11) ◽  
pp. 155-162 ◽  
Author(s):  
B. Maul-Kötter ◽  
Th. Einfalt

Continuous raingauge measurements are an important input variable for detailed rainfall-runoff simulation. In North Rhine-Westphalia, more than 150 continuous raingauges are used for local hydrological design through the use of site specific rainfall runoff models. Requiring gap-free data, the State Environmental Agency developed methods to use a combination of daily measurements and neighbouring continuous measurements for filling periods of lacking data in a given raindata series. The objective of such a method is to obtain plausible data for water balance simulations. For more than 3500 station years the described methodology has been applied.


2021 ◽  
Vol 13 (9) ◽  
pp. 1779
Author(s):  
Xiaoyan Yin ◽  
Zhiqun Hu ◽  
Jiafeng Zheng ◽  
Boyong Li ◽  
Yuanyuan Zuo

Radar beam blockage is an important error source that affects the quality of weather radar data. An echo-filling network (EFnet) is proposed based on a deep learning algorithm to correct the echo intensity under the occlusion area in the Nanjing S-band new-generation weather radar (CINRAD/SA). The training dataset is constructed by the labels, which are the echo intensity at the 0.5° elevation in the unblocked area, and by the input features, which are the intensity in the cube including multiple elevations and gates corresponding to the location of bottom labels. Two loss functions are applied to compile the network: one is the common mean square error (MSE), and the other is a self-defined loss function that increases the weight of strong echoes. Considering that the radar beam broadens with distance and height, the 0.5° elevation scan is divided into six range bands every 25 km to train different models. The models are evaluated by three indicators: explained variance (EVar), mean absolute error (MAE), and correlation coefficient (CC). Two cases are demonstrated to compare the effect of the echo-filling model by different loss functions. The results suggest that EFnet can effectively correct the echo reflectivity and improve the data quality in the occlusion area, and there are better results for strong echoes when the self-defined loss function is used.


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