An%20Automated%20Synoptic%20Typing%20System%20Using%20Archived%20And%20Real-time%20NWP%20Model%20Output

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
• 19th 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 MENTOR
• Synoptic Classification manual correlation-based
  map-pattern eigenvector-based
• Tools Synoptic Typer Map Browser
• Examples weather variables associated with
  synoptic types
• Future 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.

4
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)

5
Correlation-basedmap-pattern classification

• Jasper and Stern (1983) seasonal sampling 22
  years38 synoptic types
• Updated using NCEP grids (1948-2001)
• 2.5o resolution (SE Australia)
• 00UTC MSLP analyses
• Correlation thresholds(0.7, 0.75, 0.8, 0.85,
  0.9, 0.95)
• Number of keydays (lt100)
• Number of synoptic types(10, 15, 20, , 90, 95)
• Minimum group size (1)
• Resources IDL 5.5 and UNIX server

NCEP grids
correlate
correlation matrix
derive
keydays
catalog
synoptic types (csv)
analyse
Daily data (years) Disk or RAM (Mb) CPU (hours)
54 780 15
synoptic types (binary)
statistics
6
Eigenvector-based classification

• Dahni and Ebert (1998) automated objective
  synoptic typing
• Simple pattern recognition scheme with fields of
  MSLP as input
• METANAL 00UTC MSLP analyses 1.5o resolution
  1970-1993
• Principal components and cluster analysis
  techniques
• First 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 2.5o resolution 1948-2001
8
Synoptic Typer
Graphical User Interface

• Interactive (GUI-based) mode for development
• Developed on PC (Windows) using IDL 5.5
• Cross-platform (Windows, Linux, UNIX) application

9
Synoptic Typer

• Non-interactive (batch) mode for operational
  implementation (UNIX)
• Existing 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)
• Real-time synoptic type guidance stored in the
  Forecast Database
• Automatic 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

• Interactive
• NCEP grids
• Vector, Barb or Streamline
• Derived fields
• Tropical Cyclones
• Synoptic Types
• Mean fields
• Interpolate data
• Weather variables
• Batch mode

11
Example (manual classification and Melbourne
rainfall)
Treloar and Stern (1993) Synoptic Types50 NCEP
grids, Years1948-2001 Days19724 Rain Days gt 30
mm 127
Synoptic Type Freq () Rain Daysgt 30 mm ()
41 4.0 18.1
43 1.5 17.3
27 3.4 15.0
12
Example (correlation-based map-pattern
classification and Melbourne rainfall)
NCEP grids Years1948-2001 Days19724 Threshold0.
90 Synoptic Types50 Rain Days gt 30 mm 127
Synoptic Type Freq() Rain Daysgt 30 mm ()
49 1.1 18.1
21 2.1 11.8
28 1.5 8.7
9 2.0 7.9
46 1.3 7.9
13
Example (correlation-based map-pattern
classification and Melbourne heat waves)
NCEP grids Years1948-2001 Days19724 Threshold0.
90 Synoptic Types50 Heat Wave Days 136
Synoptic Type Freq() Heat Wave Days ()
17 2.1 22.8
34 1.6 12.5
8 2.0 10.3
4 3.4 9.6
14
Future Developments

• 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)
• For further information go to the following web
  site
• http//www.bom.gov.au/inside/cosb/mss/projects/syn
  optictyper/