use of c-band radars in nowcast applications at the german ... · later, a train ran off the rails...

ERAD 2012 - THE SEVENTH EUROPEAN CONFERENCE ON RADAR IN METEOROLOGY AND HYDROLOGY

Use of C-band radars in nowcast applications at the German Weather Service (DWD)

Tim Böhme Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany,

[email protected]

(Date: 31 May 2012)

Tim BÖHME

1. Introduction

The German National Weather Service (DWD) is currently replacing all C-band radars by new polarimetric radars. This poster presents the new radar network configuration. In addition to satellite and lightning data, radar data is the most important source of information for DWD nowcast products. These products are the main basis for the triggering of warnings. DWD is merging the individual radar and nowcasting products in the visualisation system NinJo, which is the main information platform for DWD forecasters.

2. Radar network

Until 2015 the radar network configuration will be optimised. This is carried out in the project RadSys-E. New sites are selected outside large cities, e. g. in Boostedt for Hamburg, Offenthal for Frankfurt, Prötzel for Berlin and Schnaupping for Munic. In addition, a new radar is installed in Memmingen in order to improve the detection of heavy precipitation in the Central Northern Alp region. The radar network (see figure 1) is covering more than 99% of Germany and is contributing significantly to the European radar network (e.g., OPERA).

Fig 1: Network of 17 operational C-band radars in Germany (after replacement). The red circles represent a radius of 150 km around each individual radar.


3. Visualisation of radar and nowcast data in NinJo

For the visualisation, DWD is using the system NinJo (see figure 2). The radar products are grouped into three different classes: Reflectivity products (product name):

� Local products of each radar site (PX, PL), � Composite products (PC, RX, EuRadCom), � Horizontal and vertical cross-section composite products (PZ),

Precipitation products (product name):

� Local products (PH, PY), � Composite products (RADOLAN): unfiltered (RZ), filtered (RY, RH), adjusted (RW),

Wind products:

� Local CAPPI products (PU, PR). There are two different scan modes: the volume scan mode with a scan period of currently 15 minutes (to be updated to 5 minutes in a later stage) and the precipitation scan mode with a period of 5 minutes. After the completed replacement of all radar systems, due in 2015, improved radar data and additional information, e.g. about the precipitation phase, will be available. Radar data give a significant contribution to nowcast products, which are used intensively in the convective season. At DWD nowcast products are calculated for up to 120 minutes, in 5 minutes interval. Together with satellite and lightning information several products are operationally used in NinJo: Identification and tracking of objects:

� KONRAD (convective cells), see also Lang (2001), � CellMOS (convective cells), see also Hoffmann (2008), � Meso-cyclones (rotation signal), see also Hengstebeck et al. (2011),

Identification of hazard zones:

� NowcastMIX (combination of several warning parameters), see also James et al. (2011). Whilst the preceding products are already in operational use, others are in development or at an evaluation stage: Nowcasting of precipitation areas:

� RADVOR-OP (precipitation amount and phases), see also Winterrath et al. (2011).

New products: � Rad-TRAM (for cell identification and tracking), see also Kober and Tafferner (2009).

Further nowcast products, not based on radar but on satellite data, are also in an evaluation process:

� RDT (for cell identification and tracking), see also SAFNWC/MSG (2012) � CI (for the identification of cell initiation), see also Mecikalski and Bedka (2006) � Cb-TRAM (for cell identification and tracking), see also Zinner (2008).

The aim of the nowcast product range is to combine individual nowcast products of different remote sensing data with different lead times and spatial resolution. While radar data can provide data of high temporal and spatial resolution – especially in the future with the polarimetric data –, satellite data can cover a wider area. Another advantage of satellite data is e. g. the identification of convective potential much earlier than a radar.


Fig 2: NinJo visualisation of combined radar, lightning and nowcast products over Germany (23 May 2012, 15.00 UTC): In the addition the radar EuRadCom product, the lightning activity (crosses), the nowcast products KONRAD (circles) and CellMOS (rectangles) are presented. The colours represent the individual object intensity, from low (green) via medium (yellow) to high intensity (red and purple). On top of it, additional layers can be added (e.g. satellite, observations from weather stations etc.). The time line is set at the bottom of the screen. Beside individual images, animations can be produced. In addition, the illustration can be controlled via the buttons on the left side.

4. Case study of 11 September 2011

A case study with clear signals in the radar and nowcast products is shown in Figs. 3 to 8. As an illustrative case, the 11 September 2011 is presented. On this day, a cold front with a preceding convergence line crossed Germany from West to East and caused heavy gusts, even tornadoes, and heavy precipitation including hail.

Fig.3: Analysis of fronts & surface pressure from 11.09.2011, 00 UTC.


Fig.4: Radar precipitation scan data 250m resolution and HRV satellite data of Germany from 11.09.2011, 12.30 UTC (left) and 16.30 UTC (right). The radar values represent the maximum reflectivity in the lowest elevation (mostly 0,8°) which is terrain following. The stron gest echoes are indicated in white and represent individual storm cells in the convergence line which is preceding the cold front. The main convective activity is located over Western Germany (regions of Rheinland-Pfalz and Hessen) at 12.30 UTC and over Eastern Germany (near the river Elbe) at 16.30 UTC. Figure 3 shows the synoptic situation: On 11 September 2011, a warm and humid air stayed over Germany. During the late morning a cold front with a preceding convergence line crossed first Western and then later Eastern and Southern Germany. Figure 4 shows the radar and satellite images at 12.30 UTC and 16.30 UTC. The situation at 12.30 UTC over Western Germany is presented in detail in Figs. 5 and 6. At the rear, the cold front is clearly marked with a line without radar signals from Luxemburg towards the Rhine-Ruhr area. In addition, the Figure 6 shows also clear meso-cyclones especially in the southern part of the convergence line. Some of them caused heavy damage. Later in the afternoon, the systems reached Eastern Germany (see situation at 16.30 UTC in Figs. 6 and 7) with hail, gusts and even several tornadoes. Figure 5 shows the linked precipitation (filtered signals using an improved Z-R relation). In addition, the KONRAD cell identification and tracking product is presented. It shows up to 5 strong convective cells, two of them of highest intensity (purple circles) moving towards the Rhine valley and the Northern Hessen region. Some minutes later, a train ran off the rails in the Rhine valley near Mainz after a landslide. The site is matching with the forecasted path of the identified purple KONRAD cell.

Fig.5: Filtered precipitation data (RH, 1 km resolution) over Western Germany from 11.09.2011, 12.30 UTC, using an improved Z-R relation (coloured iso-surfaces). In addition, KONRAD cells are presented (coloured circles). The small rectangles represent previous cell positions, the white lines the calculated tracking path.


Fig 6: Top: Radar precipitation scan data (RX, 1 km resolution) of Western Germany from 11.09.2011, 12.30 UTC. In addition meso-cyclones (coloured triangles) and the nowcast cell identification and tracking product CellMOS (coloured rectangles) are presented. Bottom: The forecasted tracking path of the CellMOS product is presented.

Fig 7: Filtered precipitation data (RH) of Eastern Germany from 11.09.2011, 16.30 UTC, using the improved Z-R relation. In addition KONRAD cells are presented.


Fig 8: Left: Radar precipitation scan data 250m, meso-cyclones and identified / forecasted CellMOS cells at 16.30 UTC. Right: The probability of ≥ 10 mm precipitation between 16.30 and 17.30 UTC predicted by CellMOS. Figure 6 shows on the top the convective cells using the CellMOS product (rectangles) together with the RX reflectivity product on the top (1 km horizontal resolution). In addition, meso-cyclones with strong wind-shear values are indicated (triangles). On the bottom, Figure 6 shows the calculated tracking path of the CellMOS cells. Figure 7 shows the position of the convergence line at 16.30 UTC, when strong convective cells reached Eastern Germany (south-west of Berlin). Around 16.30 UTC tornadoes were observed in the region of Dessau near the river Elbe, approximately 120 km south-west of Berlin. This area is marked by a strong KONRAD cell (number 431) and in Figure 8 by a strong CellMOS cells, high reflectivity values above 59 dBZ and strong meso-cyclone signals (wind shear). The systems continued to propagate towards north-east. The CellMOS probability marks the areas where more 10 mm precipitation is going to occur with the indicated probability. Altogether, the cell localisation is quite similar with CellMOS and KONRAD. While the calculated propagation agrees at 12.30 UTC, there is a small difference in the calculated propagation direction at 16.30 UTC.

5. Summary

The currently used radar and nowcast products for operational forecasts at DWD are shown. The case study demonstrates how valuable already existing products are for the triggering of warnings. In the future, the new radars could provide even more information based on area-wide polarimetric data. The quality of precipitation quantities forecasts will then be improved and phase information added which are valuable both in summer (hail) and winter (snow, sleet).

References Hengstebeck, T., D. Heizenreder, P. Joe and P. Lang, 2011: The mesocyclone detection algorithms of DWD, 6th European Conference on Severe Storms (ECSS), Palma de Mallorca (Spain), 3-7 October 2011. Hoffmann, J. M., 2008: Entwicklung und Anwendung von statistischen Vorhersage-Interpretationsverfahren für Gewitternowcasting und Unwetterwarnungen unter Einbeziehung von Fernerkundungsdaten. Dissertation, Freie Universität Berlin (Germany). James, P., S. Trepte, D. Heizenreder and B. K. Reichert, 2011: A fuzzy logic based tool for providing automatic integrated short-term warnings from continuously monitored nowcasting systems, European Conference on Applications of Meteorology, Berlin (Germany), 12-16 September 2011. Kober, K. and A. Tafferner, 2009: Tracking and nowcasting of convective cells using remote sensing data from radar and satellite. Meteorologische Zeitschrift, 18(1), 075-084. Lang, P., 2011: Cell tracking and warning indicators derived from operational radar products. 30th International Conference on Radar Meteorology, Munic (Germany), 245-247. Mecikalski, J. M. and K. M. Bedka, 2006: Forecasting convective initiation by monitoring the evolution of moving cumulus in daytime GOES imagery, Monthly Weather Review, 134, 49-78. SAFNWC/MSG, 2012: Algorithm theoretical basis document for “Rapid Development Thunderstorm” (RDT-PGE11 v2.3). SAF/NWC/CDOP/MFT/SCI/ATBD/11, Issue 2, Rev. 3, 15 February 2012, Météo France. Winterrath, T., W. Rosenow and E. Weigl, 2011: On the DWD quantitative precipitation analysis and nowcasting system for real-time application in German flood risk management. Weather review and Hydrology, in press. Zinner, T., H. Mannstein, A. Tafferner, Cb-TRAM, 2008: Tracking and monitoring severe convection from onset over rapid development to mature phase using multi-channel Meteosat-8 SEVIRI data, Meteorol. Atmos. Phys.., 101, 191-210.

use of c-band radars in nowcast applications at the german ... · later, a train ran off the rails...

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