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An Automated Synoptic Typing System Using Archived And Real-time NWP Model Output

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

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An Automated Synoptic Typing System Using Archived And Real-time NWP Model Output

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  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 Abstract and paper prepared for 19th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California, February, 2003. BMRC Seminar 23 October 2002

  2. Overview • Background (MENTOR, GASM) • Synoptic Classification (manual, correlation-based map-pattern and eigenvector-based classifications) • Synoptic Typer • Tools (Map Browser, IDL) • Examples (weather variables associated with synoptic types) • Future Developments • References

  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.”

  4. Background • GASM (Dahni and Stern, 1995)“The analogue technique achieved … operational status through the Australia-wide implementation of the Generalised Analogue Statistics Model … and the Forecast Guidance System component of the Australian Integrated Forecast System (Kelly and Gigliotti, 1997).”Requires major re-development:- replace analogue retrieval with synoptic classification;- associate weather variables with synoptic types; and- generate OBJECTIVE weather forecast guidance.

  5. Background Select circulation data and environmental data Compile classification first; relate to environment later Classify circulation data by environment-based criteria Classification type? Circulation- to- Environment Classification Environment- to- Circulation Classification The two fundamental approaches to synoptic classification (Yarnal, 1993)

  6. Synoptic Classification • Jasper and Stern (1983)correlation-based; seasonal; sampling; 22 years;June 1957 - May 1979; 38 synoptic types;SE Australia • Treloar and Stern (1993)manual; direction, strength and curvature of the surface flow; 1957-2002; 50 synoptic types;SE Australia • Dahni and Ebert (1998)eigenvector-based; principal components and cluster analysis; 1970-1993; first 5 principal components; 20 clusters; Melbourne

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

  8. Correlation-basedmap-pattern classification • Jasper and Stern (1983) • Updated using NCEP grids (1948-2001) • 2.5o resolution • 00UTC MSLP analyses (SE Australia) • 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 (gale) NCEP grids correlate correlation matrix derive keydays catalog synoptic types (csv) analyse synoptic types (binary) statistics

  9. Eigenvector-based classification • Dahni and Ebert (1998) – automated objective synoptic typing • Simple pattern recognition scheme with fields of MSLP as input • Principal components and cluster analysis techniques • METANAL grids • 00UTC MSLP analyses • 1.5o resolution • 1970-1993 • Specific locations (regions) around Australia

  10. Eigenvector-based classification

  11. Eigenvector-based classification

  12. Synoptic Typer • Interactive (GUI-based) mode for development • Developed on PC (Windows) using IDL 5.5 • Cross-platform (Windows, Linux, UNIX) application • Non-interactive (batch) mode for operational implementation (UNIX) Graphical User Interface

  13. Synoptic Typer • Existing C++ module used to extract NWP grids from real-time NEONS/ORACLE database • Automatic classification of real-time NWP model output (e.g. GASP, EC and LAPS) • Real-time synoptic type guidance stored in Forecast Database • Automatic synoptic type for MENTOR system

  14. Synoptic Typer 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

  15. Synoptic Typer METANAL grids (MSLP, 850 hPa temperature, 1000, 850, 700, 500, 300 and 250 hPa geopotential height, 500 hPa wind speed);00 and 12UTC analyses;1.5o resolution; 1970-1993 NCEP grids (MSLP, 850 hPa temperature, 1000 and 500 hPa geopotential height and wind, precipitable water, OLR);00, 06, 12 and 18UTC analyses; 2.5o resolution; 1948-2001

  16. Tools • Synoptic Typer • Map Browser • MapGrid • Map Annotator • Correlation-based map-pattern classification • Associating weather variables to synoptic types • IDL 5.5 • Managed desktop • UNIX server

  17. Map Browser • Interactive • METANAL grids • NCEP grids • Vector, Barb or Streamline • Derived fields • Tropical Cyclones • Synoptic Types • Mean fields • Interpolate data • Batch mode Graphical User Interface

  18. MapGrid • Interactive • McIDAS grids • NetCDF files • Sigma level • Pressure level • Plot, Contour or Fill • Vector, Barb or Streamline • Overlay fields • Difference fields • Derived fields • Batch mode Graphical User Interface

  19. Map Annotator • Meteorological Annotation Tool • Interactive • Open/Save Images • Annotate • Fronts • Troughs • Ridges • Weather Symbols • Clouds • Significant Weather • etc Graphical User Interface

  20. Example (manual classification and Launceston Airport rainfall) Treloar and Stern (1993) Synoptic Types=50 NCEP grids, Years=1948-2001 Days=19724 Rain Days > 20 mm = 280

  21. Example (correlation-based map-pattern classification and Melbourne rainfall) NCEP grids Years=1952-2001 Days=18623 Threshold=0.90 Synoptic Types=55 Rain Days > 30 mm = 115

  22. Future Developments • MOF Model Archive • LAPS grids • 0.75o resolution • 00 and 12UTC analyses and prognoses(+12, +24, +36 and +48) • July 1996-2002 • Synoptic Types: operational implementation, multiple input fields, correlate sequence of days, extension to other regions … • Associate Weather Variables with Synoptic Types: fog events, significant rainfall, forecast errors (verification) … • Replacement of GASM …

  23. References Dahni, R. R. and Ebert, E. E. 1998. Automated objective synoptic typing to characterize errors in NWP model QPFs. 12th Conference on Numerical Weather Prediction, Amer. Meteor. Soc., Phoenix, Arizona. Dahni, R. R. and Stern, H. 1995. The development of a generalised UNIX version of the Victorian Regional Office’s operational analogue statistics model. BMRC Research Report 47, Bureau of Meteorology, Melbourne, Australia. Jasper, J. D. and Stern, H. 1983. Objective classification of synoptic pressure patterns over southeast Australia. Proceedings 2nd International Meeting on Statistical Climatology, Lisboa, Portugal. Kelly, J. and Gigliotti, P. 1997. The Australian Integrated Forecast System (AIFS): Overview and current status. 13th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California. Ryan, C. J., Jha, A. and Joshi, S. 2003. MENTOR – A performance support system for forecasters. 19th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California.

  24. References Stern, H. 2003. Progress on a knowledge-based internet weather forecasting system. 19th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California. Treloar, A. B. A. and Stern, H. 1993. A climatology and synoptic classification of Victorian severe thunderstorms. 4th International Conference on Southern Hemisphere Meteorology and Oceanography, Amer. Meteor. Soc., Hobart, Australia. Yarnal, B. 1993. Synoptic Climatology in Environmental Analysis, Belhaven Press, London. Abstract and Extended Abstract (PDF) for 19th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Amer. Meteor. Soc., Long Beach, California, February, 2003. http://ams.confex.com/ams/annual2003/19IIPS/abstracts/55276.htm http://ams.confex.com/ams/pdfview.cgi?username=55276

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