1. FORECAST MODELS: DYNAMIC(PHYSICAL) VS. STATISTICAL
DYNAMICAL MODEL
STATISTICAL MODEL
Physical equations!
- 7 fund. + few more
Statistical equations!
- Pure mathematical

2. Statistical models … examples

3. STATISTICAL MODELS … examples
MOS
“Model Output Statistics”
How are MOS equations made ?
Relate dynamical model output to observations of past weather

4. MOS
Partially Removes Model Biases!

5. STATISTICAL MODELS (MOS)
Why have MOS ?
Partially removes biases!
Predicts parameters that dynamical models don’t
Visibility, Cloud ceilings …..
Predicts some parameters better than dynamical models (averaged over all cases)
Surface temperature, Td, wind

6. AVN MOS BUF EC AVN MOS GUIDANCE 9/26/01 1200 UTC
DAY /SEPT 26 /SEPT /SEPT /
HOUR
MN/MX
TEMP
DEWPT
CLDS OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV BK SC
WDIR
WSPD
POP
POP
QPF / 1/ 1/1 2/ 1/2 1/ 1/1 0/ 0/0
TSV / 0 7/ 0 9/ 0 3/ 1 26/ 0 21/ 0 10/ 0 10/ 0 9/ 0
TSV / / / / 0
PTYPE R R R R R R R R R R R R R R R
POZP
POSN
SNOW / 0/ 0/0 0/ 0/0 0/ 0/0 0/ 0/0
CIG
VIS
OBVIS N N N N N F F N N N F N N

7. AVN MODEL
Station: BUF Lat: Lon: Elev: 217 Closest grid pt: 13.5 km.
Initialization Time: UTC
PARAMETER/TIME
DAY / HOUR /12 26/18 27/00 27/06 27/12 27/18 28/00 28/06 28/12
TEMPS
1000 MB (C)
950 MB (C)
900 MB (C)
850 MB (C)
800 MB (C)
THCK
MOISTURE
1000 MB DP(C)/RH 6/93 4/5 5/57 6/75 9/95 7/73 7/63 7/60 8/68
850 MB DP(C)/RH -3/92 -1/91 0/91 0/97 -1/97 0/97 1/93 1/89 2/91
700 MB DP(C)/RH-10/93 -10/98 -10/97 -11/95 -12/90 -12/97 -11/94 -10/82 -9/78
500 MB DP(C)/RH-22/76 -25/64 -28/60 -24/77 -24/92 -24/99 -25/94 -24/86 -26/61
PRCPABLE WTR (I
CONV PRECIP (IN
TOTAL PRECIP (I
WIND DD/FFF (Kts)
1000 MB /014 21/009 26/011 30/009 30/009 28/007 30/008 36/011 01/016
850 MB /025 23/021 25/017 28/011 30/011 31/013 32/011 36/014 01/017
700 MB /036 24/029 25/028 26/022 29/013 34/017 35/020 01/024 02/026
500 MB /049 23/045 25/039 25/034 27/021 33/016 00/027 02/038 03/044
250 MB /050 23/054 23/048 24/044 25/027 29/011 00/026 02/039 03/050

8. FORECAST MODELS: DYNAMIC(PHYSICAL) VS. STATISTICAL
dynamic models
statistical models- MOS

9. CONCEPTUAL MODELS
Dynamic Ascent: Shortwaves
Aloft: 500mb

10. What is a conceptual model?
a mental model of how things in our surrounding environment work
based on information received through scientific data and observations
important diagnostic tool, widely used in meteorology

11. CONCEPTUAL MODELS: The Norwegian cyclone model

12. Forecasting Technique: Pattern Recognition
Associating a “weather pattern” to a “weather event”
Significant weather events have patterns
surface features
upper level features
4-panel maps useful

13. Pattern Recognition: Severe Weather
Dynamics (winds)
Shortwaves/vortmax
“JET STREAM DISTURBANCE”
Thermodynamics (stability)
High theta-e air!
WARM, HUMID AIR
“MATCH”
“FUEL”