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

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 prospect...

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Bibliographic Details
Published in:Journal of hydroinformatics 2017-03, Vol.19 (2), p.315-330
Main Authors: Guardiola-Albert, Carolina, Rivero-Honegger, Carlos, Monjo, Robert, Díez-Herrero, Andrés, Yagüe, Carlos, Bodoque, Jose María, Tapiador, Francisco J.
Format: Article
Language:English
Subjects:
Adaptation
Algorithms
Atmospheric precipitations
C band
Catchment area
Catchments
Climatology
Data processing
Design of experiments
Environmental risk
Errors
Estimates
Floods
Gauges
Geostatistics
Hydrology
Kriging interpolation
Mathematical models
Methods
Mountains
Nowcasting
Precipitation
Radar
Radar data
Rain
Rain gauges
Rainfall
Rainfall measurement
Runoff
Simulation
Statistical methods
Stream flow
Superhigh frequencies
Temporal resolution
Temporal variations
Water resources
Weather
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Summary: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.
ISSN:1464-7141
1465-1734
DOI:10.2166/hydro.2016.225