Journal ArticleDOI
Correcting of real-time radar rainfall bias using a Kalman filtering approach
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TLDR
In this paper, a method to adjust the mean field bias of radar rainfall estimates in real-time is presented, where Kalman filtering techniques are used as the basis for correcting the mean filed bias in real time.About:
This article is published in Journal of Hydrology.The article was published on 2006-02-05. It has received 106 citations till now. The article focuses on the topics: Radar & Rain gauge.read more
Citations
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Journal ArticleDOI
A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data
TL;DR: Results seem to indicate that the methodology of kriging with external drift [KED], in combination with the technique of automatically computing 2-D spatial correlograms, provides merged rainfall fields with good agreement with rain gauges and with the most accurate approach to the spatial tendencies observed in the radar rainfall fields, when compared with other alternatives analyzed.
Journal ArticleDOI
Weather radar rainfall data in urban hydrology
Søren Liedtke Thorndahl,Thomas Einfalt,Patrick Willems,Jesper Ellerbæk Nielsen,Marie-Claire ten Veldhuis,Karsten Arnbjerg-Nielsen,Michael R. Rasmussen,Peter Molnar +7 more
TL;DR: In this paper, a review of the state of the art in radar rainfall data and applications is presented, focusing on three key areas with significant advances over the past decade: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications.
Journal ArticleDOI
Bias adjustment and advection interpolation of long-term high resolution radar rainfall series
TL;DR: In this article, different bias adjustment techniques are investigated, developing a complete 10-year dataset (2002-2012) of high spatio-temporal resolution radar rainfall based on a radar observations from a single C-band radar from Denmark.
Journal ArticleDOI
Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework
M. M. Hasan,Ashish Sharma,Gregoire Mariethoz,Gregoire Mariethoz,Fiona Johnson,Alan Seed,Alan Seed +6 more
TL;DR: In this paper, a nonparametric radar rainfall estimation method was proposed to address known limitations in radar rainfall products by using a relatively long history of radar reflectivity and ground rainfall observations.
Journal ArticleDOI
Characteristics of 2-D convective structures in Catalonia (NE Spain): an analysis using radar data and GIS
TL;DR: In this paper, statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain) have been provided by means of weather radar, and applying 2D radar algorithms a distinction between convective and stratiform precipitation is made.
References
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Book ChapterDOI
A New Approach to Linear Filtering and Prediction Problems
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
Journal ArticleDOI
Climatological Characterization of Three-Dimensional Storm Structure from Operational Radar and Rain Gauge Data
TL;DR: In this article, three algorithms extract information on precipitation type, structure, and amount from operational radar and rain gauge data, and statistically summarize the vertical structure of the radar echoes, and determine precipitation rates and amounts on high spatial resolution.