1. Severe Weather Forecasting Tools in the Ninjo Workstation Paul Joe 1, Hans-Joachim Koppert 2, Dirk Heizenreder 2 Bernd Erbshaeusser 2, Wolfgang. Raatz 2, Bernhard Reichert 2 and Michael Rohn 2 1 Meteorological Service of Canada 2 Deutscher Wetterdienst

2. Outline Brief NinJo overview Various Tools Specfic to Weather Warnings Radar – Doppler, 3D Algorithms (Konrad, CARDS) Storm Classification Identification and Tracking Interactive Cross-sections Interactive Cell Views Automon EPM – Editing, Production, Monitoring of Warnings OOG – Objectively Optimized Guidance MMO – Modified Model Output Current status

3. What is NinJo? Consortium of five partners Data Visualization Workstation 1.0 release date 27.03.2005 1.0 deployed by DWD, DMI, MCH, BGS MSC responsible for radar, lightning DWD responsible for SCIT

4. Why NinJo? “stuck” in adding more forecast applications Need common interfaces (data and human) Legacy software, stovepiped one system=one application, expensive to support Modern, Architecture

5. NinJo Layers = Client Interface to Server Applications

6. Severe Weather Warnings for DWD DWD announced that it will to take the responsibility to provide a severe thunderstorm/tornado warning service!

7. Radar in NinJo Initially based on the Canadian radar system in Canada due to requirements for severe weather. Integrates data/products DWD legacy systems [KONRAD Hohenpeissenberg / RDT Offenbach AP2003 group], from MCH (TRT)

8. Some Philosophy Assume expert severe wx user Must maintain situational awareness Work from composite and drill down to details Support Analysis/Mental Models Detail view match “text book” material Create Leverage Points/not answers Use algorithms as guidance and not to promote dumbness Do not rely on algorithms, use them wisely

9. Implementation – SCIT and Cells Composite radar; Imagery hidden Cell detections shown Storm Classification Identification and Tracking - “ranked storms”

10. Cell View

11. Radar Data/Products and NinJo Can manipulate, view, interact with radar in the same way as any other data – separation by usage rather than by sensor Radar/data functionality separated VAD = aerological data Cell Objects = point data Radar Fields = 2D or 3D data Cross-section capability = path layer

12. NinJo and Radar Composites on the fly or pre-computed, Data viewer A NinJo View: Transparent radar and satellite overaid on surface data

13. Interactive “Cell” Views (first prototype step) User sets the area for viewing. Not necessarily based on algorithm detection of thunderstorms (and their problems)! Any data type can be included in the cell view window. eg boundary identification, fog monitoring

14. Assessing Models with Data Watch / Assessment Phase of the Severe weather forecast process

15. Cross-sections

16. MxRadar XSection

17. AutoMon (Automatic Monitoring) (i) point threshold for alerting, (ii) model vs data, (iii) forecast vs data Objects: Will handle objects generated by lightning cluster algorithms, satellite, manually using the same

18. Assessing Models Watch Phase Real vs Synthetic (NWP)

19. Assessing Models by Comparing with Data

21. Editting, Production and Monitoring (Warning Layer)

22. Objectively Optimized Guidance (Blending)

23. Summary Very brief description of the NinJo and the Severe Weather package Several tools to support the forecaster to make better decisions Radar, algorithms, ranking, cell views, cross-sections, Automon, MMO (EPM (warning production), lightning, swath products System in development, v1 released, v1.2 March 2006 Need to spend time on training to develop expertise Science, technology, usage Practice/Simulation needed to optimize use

24. Lightning / Lightning Cluster Analysis

25. Modified Model Output (Point and Area editting)