H-SAF Product Validation Report (PVR) PR-OBS-3

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Products Validation Report, 30 May 2010 - PVR-03 (Product PR-OBS-3) Page 24 3.4.3 Facilities in Hungary (OMSZ) Ground data description (instrument characteristic and map) In Hungary, about 90 automatic stations work (Fig. 16), where 10-min precipitation is measured by tipping bucket rain gauges. This data is used to correct the accumulated precipitation radar data Fig. 16 - The automatic rain gauge network in Hungary. The main data used for validation in Hungary would be the data of meteorological radars. There are three C-band dual polarized Doppler weather radars operated routinely by the OMSZ-Hungarian Meteorological Service (see Fig. 17 and Table 06). Pogányvár Napkor Budapest Fig. 17 - Location and coverage of the three meteorological Doppler radars in Hungary. Table 06 - Characteristics of the three meteorological Doppler radars in Hungary Year of installation Location Radar type Parameters measured 1999 Budapest Dual-polarimetric, Doppler radar Z, ZDR 2003 Napkor Dual-polarimetric, Doppler radar Z,ZDR,KDP,ΦDP 2004 Poganyvar Dual-polarimetric, Doppler radar Z,ZDR,KDP,ΦDP Ground data quality and accessibility Access to Hungarian radar data can be set up through contact with the responsible of the institute within the HSAF project. It will be provided for developers if required for case studies.
Products Validation Report, 30 May 2010 - PVR-03 (Product PR-OBS-3) Page 25 The quality of the radar measurements is influenced by several factors: - the accuracy of the Marshall-Palmer equation in deriving rain rates - the beam blockage which causes the lack of precipitation in areas behind mountains. The Hungarian radar data bears the consequences of both problems. The Marshall-Palmer calculations can result in a factor of multiplying or dividing by 2; whereas the beam blockage can result in serious underestimation of precipitation amounts (e.g. behind the Börzsöny mountains at the north of Budapest). Besides, the Hungarian radar data is filtered from WLAN signal, which is also a source of false signals in the radar. A filter to disregard signals below 7 dBz is also applied because in general, these data is not coming from real rain drops, but false targets. Ground data products Precipitation intensity is derived from radar reflectivity with the help of an empirical formula, the Marshall-Palmer equation. From the three radar images a composite image over the territory of Hungary is derived every 15 minutes applying the maximum method in order to make adjustments in overlapping regions. The non-corrected precipitation field can be corrected by rain gauge measurements. As recent researches have shown it is only possible to produce adequate precipitation fields by the correction of raw radar data at time scales of the order of a few hours or more, thus we do not make corrections to 15 minutes radar data. In our institute, we only use a correction for the total precipitation over a 12 hour period. For the 3h and 6h accumulated products, we use a special method as well: we interpolate the 15-minutes measurements for 1-minute grid by the help of displacement vectors also measured by the radar, and then sum up the images which we got after the interpolation. It is more precise especially when we have storm cells on the radar picture, because a storm cell moves a lot during 15 minutes and thus we do not get continuous precipitation fields when we sum up only with 15.minutes periods. This provides satisfying results. However, there is still a need for rain-gauge adjustment because there are obviously places (behind mountains) that the radar does not see. The radars are corrected with rain gauge data every 12 hours. The correction method using raingauge data for 12 hour total precipitation consists of two kinds of corrections: the spatial correction which becomes dominant in the case of precipitation extended over a large area, whereas the other factor, the distance correction factor prevails in the case of sparse precipitation. These two factors are weighted according to the actual situation. The weighting factor depends on the actual effective local station density, and also on the variance of the differences of the bias between radar and rain gauge measurements. On the whole, we can say that our correction method is efficient within a radius of 100 km from the radar. In this region, it gives a final underestimation of about 10%, while at bigger distances, the underestimation of precipitation fields slightly increases. Besides, we also produce 12 hour total composite images: first the three radar data are corrected separately, and then the composite is made from them. The compositing technique consists of weighting the intensity of each radar at a given point according to the distance of the given point from the radars. Ground data interpolation No interpolation is used for the radar data. Institute validation methodology The data used for the discrimination of case studies: OMSZ-Hungarian Meteorological Service receives operationally the MSG data and several products based on satellite data are derived and sent to the weather forecasters. The SAFNWC/MSG program package derives cloud type product and precipitation products (convective rain rate and probability of precipitation) also. MSG composite images are created operationally. For the description of
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H-SAF Product Validation Report (PVR) PR-OBS-3

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