1 The role of ECMWF products in the optimisation of operational processes at KNMI Janneke Ottens Head Forecasting Division Thanks to: Robert Mureau, Kees Lemcke, Marcel Molendijk, Nico Maat, Ben Wichers-Schreur, Albert Jacobs, and Hans Roozekrans ECMWF user meeting, June 2006

2 Content Part I ECMWF /EPS derived products linked to optimisation –Severe weather –Water management board risk profiles –Water level management/wind surge Part II Restructuring of operational processes –The 5 Points Program

3 ECMWF /EPS derived products linked to optimisation Severe weather: Criteria linked to warnings: –Weather alarms (general public) –Warnings for special groups (maritime, aviation, ……. ) –Special warnings/advice for (other) ministries Critria linked to fcst period –Warning (12-24 hrs) –Weather alarm (0-12 hrs) First guess table: First guess medium range forecast ( including error margins )

4 ECMWF /EPS derived products linked to optimisation Severe weather: Now new weather alarms Yes or no, not good enough for all warning types Early Warnings ( hrs) : probabilities Warnings (12-24 hrs) : subjective probabilities Weather alarm (0-12 hrs) : yes or no

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6 ECMWF /EPS derived products linked to optimisation Water management board risk profiles: Alert System input Precipitation History based on radar images Short Range: Hirlam 22 km model Beyond +36 h: EPS

7 ECMWF /EPS derived products linked to optimisation Water management board risk profiles: 37 Water Boards in the Netherlands 5 participated in pilot project Water Boards are responsible for: –flood control, –water quantity, –water quality –treatment of urban wastewater

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9 ECMWF /EPS derived products linked to optimisation Input from waterboards Risk Profiles = set of thresholds Example: 50 mm within 72 hours – probability 33% Several ranges possible The specified ranges can include history Alert System If forecast or history+forecast exceeds threshold: Automatic to the involved Water Board(s) Water Board gets access to our Extranet Forecasters informed and on standby

10 Example history - short range

11 Example EPS

12 ECMWF /EPS derived products linked to optimisation Water level management/Wind surge:

13 ECMWF /EPS derived products linked to optimisation Water level management/Wind surge: Shifts are added at the storm surge centre, when critical levels are exeeded More frequent updates of fcsts More frequent contact between fcst office and storm surge centre

14 ECMWF /EPS derived products linked to optimisation External use All these products lead to introduction of probabilities in forecast products for users Internal use Also for the KNMI organisation: –Enabling more automated production of fcsts/ scenario- fcsts –Enabling more efficient shift-management in the fcst office – so called:weather dependent upscaling in relation to user requirements

15 Further use of EPS Experiment with prob early warnings on (protected) web site Link up to EMMA Target specific groups with specific risk profiles (each group with its own threshold: e.g. Water Boards, Red Cross, Windsurge) Development of heat wave warnings Monitor, verify and calibrate

16 Part II Restructuring of operational processes The 5 Points Program Replacement Meteorological Workstation (MWS) Automated Product generation forecast office Monitoring & Alerting tools Nowcasting / Severe weather Post-processing/editing models or choose a specific model: Switchfc

17 Replacement MWS –P1 Current situation: –MWS of 3SI (Spatial Software Solutions Inc, USA) –Started with Metlab Classic in 1992, operational in 1995 –Migration to Smartwindows (KNMI version Metlab2) ( )

18 Replacement MWS – P1 –Evaluation of NinJo Version 1.1 with live data soon (Obs, Satellite, Radar and Models) –Evaluation of DIANA Available for download since May 31th

19 Replacement MWS – P1 –Specifications new MWS To be used for evaluation NinJo and DIANA or ITT –Internal WEB solutions (additional to MWS) Redesign of current distributed server solution : 13 non-operational scientific webservers…. Now: Mainly maps & animations Future: Google Earth/Maps solutions ??

20 Product generation Starting points: –Better use of existing NWP-model products and predictability products –Largely automated production weather dependent automatic distribution of products Criteria/ranges based on model output and agreed upon with users –Better use of forecasters less routine production more advisory function weather dependent deployment (EPS for internal shift management)

21 Product generation Projects: –Quick Wins: small adaptions existing tools (2005) –New tools to improve automatic product generation –New working methods adapted to new production tools

22 Product generation/alerting Some requirements: –Pre-defined alert levels for raw data –Pre-defined alert levels for products –Alerts in XML –Filtering of alerts –Visualisation of alerts (dash board) –Link to raw data or products –Possibility for manual interactive editing of products

23 data customers Forecaster: 1. Check automatic Monitoring 2. Check and edit automated product generation 3. Manual production 4. Manual monitoring objective post- processing automated product generation automatic monitoring Yellow data flow not monitored by forecaster Pilot study Meteorological Production Process (MPP)

24 Trigger Database Dashboard Forecaster Information about What? When? Where? Why? Functionality (a.o.): a)Presentation triggers (filtering) based on: Trigger system Trigger issue time Trigger kind Forecasters Area of interest b)(Connected with) production tools and detailed information (URLs) System X generates triggers: Alerts observations, …, … System Z generates triggers: Alerts Automatic Production, …, … automatic distribution Manual production/adaption distribution System Y generates triggers: Alerts NWM-models, …, … XML DASHBOARD FORECASTER Dashboard Forecaster Information about What? When? Where? Why? Functionality (a.o.): a)Presentation triggers (filtering) based on: Trigger system Trigger issue time Trigger kind Forecasters Area of interest b)(Connected with) production tools and detailed information (URLs)

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27 Monitoring & Alerting tools Meteorological alerts Timely production Timely distribution Verification of models and issued forecasts

28 Nowcasting / Severe weather Projects Satrep & Eumetrain Downscaling Implementation MSG and Cinesat Innovation radar display

29 Nowcasting / Severe weather Eumetrain: –international project as follow-up Satrep ( ZAMG,FMI,UKMO,DWD,KNMI,DMHZ,Eumetsat) –Development training modules (e-learning) –Update description conceptual models –KNMI will focus on severe weather

30 Nowcasting / Severe weather Downscaling: A method for the computation of the local wind flow on scales as small as 500 m to 1 km. –A very simple two-layer physical model of the Planetary Boundary Layer –High-resolution topographical information of the surface roughness derived from Geographical Information System (GIS) datasets.

31 HIRLAM resolution 22 kmDownscaling resolution 1 km

32 Polderbaan (18R-36L) Zwanenburgbaan (18C-36C) Buitenveldertbaan (09-27) Kaagbaan (06-24) Aalsmeerbaan (18L-36R) Can be used for: windforecasts at touchdown positions (cross- and tailwind) wind gusts

33 Nowcasting / Severe weather Implementation MSG and Cinesat: MSG requires other/more tools to benifit of new data Current MWS does not have decicated tools for MSG (TM Gepard,Vienna) offers a large range of analysing tools and postprocessing tools.

34 Atmospheric motion fields Nowcasted (predicted) images Cloud contour prediction Predicted trajectories Cloud development maps Convective cells and their predicted trajectories Upper tropospheric humidity image Image movies

35 Nowcasting / Severe weather Innovation radar display: A few years ago KNMI developed a SVG-display

36 What happens, why need for new display? More information required: –More GIS info while zooming –Adding road temperature, more lightning facilities, precipitation type, cumulative precip, higher resolution images etc. SVG is not hot anymore, not much progress in viewers (e.g. Adobe SVG-viewer) Adding more info to existing application too complex and unstable

37 How to use/choose models: Switch fc Original plan: Model Switch Model A Model B Model.. Model Z post processing productsproducts

38 How to use/choose models: Switch fc New plan: Switch fc Statistical Weighting of Information Targeted at Combining High-resolution forecasts A system to combine available deterministic forecasts in an optimal way using the Bayesian Model Averaging (BMA) technique

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40 Role of ECMWF products in optimisation of operational processes The 5 Points Program should ultimately lead to: More efficient production Better quality products Easier implementation innovation More flexibility The same approach as with EPS for medium range, now also for short range using HIRLAM Thank you for your attention!