1. An Automated Synoptic Typing System Using Archived And Real-time NWP Model Output Robert Dahni Meteorological Systems Central Operations and Systems Branch Bureau of Meteorology 19 th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California, February, 2003. 11 February 2003

2. Overview Background MENTORBackground MENTOR Synoptic Classification manual correlation-based map-pattern eigenvector-basedSynoptic Classification manual correlation-based map-pattern eigenvector-based Tools Synoptic Typer Map BrowserTools Synoptic Typer Map Browser Examples weather variables associated with synoptic typesExamples weather variables associated with synoptic types Future DevelopmentsFuture Developments

3. Background MENTOR (Ryan et al, 2003) “Mentor is a web-based system which allows forecasters to record in real-time their assessments of likely meteorological “problems of the day”, forecast difficulty and their estimates of the value of objective guidance … entries accumulate in the Mentor database, and can be quickly analysed and searched by forecasters to assist in subsequent forecasting decisions. Automatic synoptic type classification is an important element of the system.”MENTOR (Ryan et al, 2003) “Mentor is a web-based system which allows forecasters to record in real-time their assessments of likely meteorological “problems of the day”, forecast difficulty and their estimates of the value of objective guidance … entries accumulate in the Mentor database, and can be quickly analysed and searched by forecasters to assist in subsequent forecasting decisions. Automatic synoptic type classification is an important element of the system.”

4. Manual classification Treloar and Stern (1993)Treloar and Stern (1993) Direction, strength and curvature of the surface flowDirection, strength and curvature of the surface flow 50 synoptic types50 synoptic types 0900 hours EST MSLP station data (1957-2002)0900 hours EST MSLP station data (1957-2002) SE AustraliaSE Australia Spreadsheet (Excel) computationSpreadsheet (Excel) computation Updated using NCEP grids (1948-2001)Updated using NCEP grids (1948-2001) Interpolated to station locationsInterpolated to station locations Updated synoptic types (Stern, 2003)Updated synoptic types (Stern, 2003)

5. Correlation-based map-pattern classification Jasper and Stern (1983); seasonal; sampling; 22 years;38 synoptic types Updated using NCEP grids (1948-2001) 2.5 o resolution (SE Australia) 00UTC MSLP analyses Correlation thresholds (0.7, 0.75, 0.8, 0.85, 0.9, 0.95) Number of keydays (<100) Number of synoptic types (10, 15, 20, …, 90, 95) Minimum group size (1%) Resources IDL 5.5 and UNIX server NCEPgrids correlate statistics correlationmatrix keydays synoptic types (csv) synoptictypes(binary) catalog derive analyse Daily data (years) Disk or RAM (Mb) CPU (hours) 5478015

6. Eigenvector-based classification Dahni and Ebert (1998) – automated objective synoptic typingDahni and Ebert (1998) – automated objective synoptic typing Simple pattern recognition scheme with fields of MSLP as inputSimple pattern recognition scheme with fields of MSLP as input METANAL; 00UTC MSLP analyses; 1.5 o resolution; 1970-1993METANAL; 00UTC MSLP analyses; 1.5 o resolution; 1970-1993 Principal components and cluster analysis techniquesPrincipal components and cluster analysis techniques First 5 principal components; 20 clusters; MelbourneFirst 5 principal components; 20 clusters; Melbourne

7. Eigenvector-based classification NCEP grids (MSLP, 850 hPa temperature, 1000 and 500 hPa geopotential height and wind, precipitable water, OLR); 00, 06, 12 and 18UTC analyses; 2.5 o resolution; 1948-2001

8. Synoptic Typer Interactive (GUI-based) mode for development Developed on PC (Windows) using IDL 5.5 Cross- platform (Windows, Linux, UNIX) application Graphical User Interface

9. Synoptic Typer Non-interactive (batch) mode for operational implementation (UNIX)Non-interactive (batch) mode for operational implementation (UNIX) Existing C ++ module used to extract NWP grids from real-time the NEONS/ORACLE databaseExisting C ++ module used to extract NWP grids from real-time the NEONS/ORACLE database Automatic synoptic classification of real-time NWP model output (e.g. GASP, EC and LAPS)Automatic synoptic classification of real-time NWP model output (e.g. GASP, EC and LAPS) Real-time synoptic type guidance stored in the Forecast DatabaseReal-time synoptic type guidance stored in the Forecast Database Automatic synoptic type for the MENTOR systemAutomatic synoptic type for the MENTOR system STNNUM, FCST_TIME, SYNT 086071, 2002092600, 7 086071, 2002092700, 7 086071, 2002092800, 18 066062, 2002092600, 2 066062, 2002092700, 13 066062, 2002092800, 12 040842, 2002092600, 1 040842, 2002092700, 3 040842, 2002092800, 13 014015, 2002092600, 3 014015, 2002092700, 11 014015, 2002092800, 14 009225, 2002092600, 8 009225, 2002092700, 8 009225, 2002092800, 12 023090, 2002092600, 7 023090, 2002092700, 7 023090, 2002092800, 5 094010, 2002092600, 11 094010, 2002092700, 5 094010, 2002092800, 16

10. Map Browser Graphical User Interface InteractiveInteractive NCEP gridsNCEP grids Vector, Barb or StreamlineVector, Barb or Streamline Derived fieldsDerived fields Tropical CyclonesTropical Cyclones Synoptic TypesSynoptic Types Mean fieldsMean fields Interpolate dataInterpolate data Weather variablesWeather variables Batch modeBatch mode

11. Example (manual classification and Melbourne rainfall) Treloar and Stern (1993) Synoptic Types=50 NCEP grids, Years=1948-2001 Days=19724 Rain Days > 30 mm = 127 Synoptic Type Freq(%) Rain Days > 30 mm (%) 414.018.1 431.517.3 273.415.0

12. Example (correlation-based map-pattern classification and Melbourne rainfall) Synoptic Type Freq (%) Rain Days > 30 mm (%) 491.118.1 212.111.8 281.58.7 92.07.9 461.37.9 NCEP grids Years=1948-2001Days=19724Threshold=0.90 Synoptic Types=50 Rain Days > 30 mm = 127

13. Example (correlation-based map-pattern classification and Melbourne heat waves) Synoptic Type Freq (%) Heat Wave Days (%) 172.122.8 341.612.5 82.010.3 43.49.6 NCEP grids Years=1948-2001Days=19724Threshold=0.90 Synoptic Types=50 Heat Wave Days = 136

14. Future Developments Synoptic Types: operational implementation, multiple input fields, correlate sequence of days, extension to other regions …Synoptic Types: operational implementation, multiple input fields, correlate sequence of days, extension to other regions … Associate Weather Variables with Synoptic Types: significant rainfall, heat waves, fog events, forecast errors (verification) …Associate Weather Variables with Synoptic Types: significant rainfall, heat waves, fog events, forecast errors (verification) … For further information go to the following web site: http://www.bom.gov.au/inside/cosb/mss/projects/synoptictyper/