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Uncertainty of precipitation estimates in convective events by the Meteorological Service of Catalonia radar network

Identifieur interne : 003B62 ( Main/Exploration ); précédent : 003B61; suivant : 003B63

Uncertainty of precipitation estimates in convective events by the Meteorological Service of Catalonia radar network

Auteurs : Laura Trapero [Andorre, Espagne] ; Joan Bech [Espagne] ; Tomeu Rigo [Espagne] ; Nicolau Pineda [Espagne] ; David Forcadell [Espagne]

Source :

RBID : Pascal:10-0092086

Descripteurs français

English descriptors

Abstract

In order to quantify the uncertainty of the radar-derived surface point quantitative precipitation estimates (QPE) from a regional radar network, a comparison has been made with a network of rain gauges. Three C-band Doppler radars and 161 telemetered gauges have been used. Both networks cover the area of Catalonia (NE Spain). Hourly accumulations integrated in daily amounts are studied. For each radar, three different precipitation products are obtained: short range, long range, and short range corrected radar QPE. The corrected product is generated by the Hydrometeorological Integrated Forecasting Tool (EHIMI), a software package designed to correct radar observations in real time for its use in hydrometeorological applications. Among other features, EHIMI includes a topographical beam blockage correction procedure. The first part of the analysis examines the bias found in the radar. The three radars generally underestimate precipitation, an effect increased with range from the radar and beam blockage, which is examined in detail in this study. Moreover, corrected QPEs systematically improve the BIAS (2 dB) and RMSf for high blockages (50-70%). The second part of the analysis illustrates the temporal evolution of the daily mean bias. Finally, the uncertainty of each rain gauge has been compared to each rainfall radar product. Geographic distribution of daily BIAS is consistent with slight under-estimation at short range and substantial at long range, especially in the north of Catalonia, which is an area with important beam blockage (>40%). These results contribute to improve the knowledge about the spatial distribution of the QPE error benefiting a number of applications including verification of high-resolution NWP precipitation forecasts and use of advanced hydrometeorological models.


Affiliations:


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Le document en format XML

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<div type="abstract" xml:lang="en">In order to quantify the uncertainty of the radar-derived surface point quantitative precipitation estimates (QPE) from a regional radar network, a comparison has been made with a network of rain gauges. Three C-band Doppler radars and 161 telemetered gauges have been used. Both networks cover the area of Catalonia (NE Spain). Hourly accumulations integrated in daily amounts are studied. For each radar, three different precipitation products are obtained: short range, long range, and short range corrected radar QPE. The corrected product is generated by the Hydrometeorological Integrated Forecasting Tool (EHIMI), a software package designed to correct radar observations in real time for its use in hydrometeorological applications. Among other features, EHIMI includes a topographical beam blockage correction procedure. The first part of the analysis examines the bias found in the radar. The three radars generally underestimate precipitation, an effect increased with range from the radar and beam blockage, which is examined in detail in this study. Moreover, corrected QPEs systematically improve the BIAS (2 dB) and RMSf for high blockages (50-70%). The second part of the analysis illustrates the temporal evolution of the daily mean bias. Finally, the uncertainty of each rain gauge has been compared to each rainfall radar product. Geographic distribution of daily BIAS is consistent with slight under-estimation at short range and substantial at long range, especially in the north of Catalonia, which is an area with important beam blockage (>40%). These results contribute to improve the knowledge about the spatial distribution of the QPE error benefiting a number of applications including verification of high-resolution NWP precipitation forecasts and use of advanced hydrometeorological models.</div>
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