1. MOS What does acronym stand for ?
MODEL OUTPUT STATISTICS
What is the difference between the GFS and GFS MOS ?

2. GFS MOS KUNV GFS MOS GUIDANCE 2/26/2008 1200 UTC
DT /FEB 26/FEB /FEB /FEB 29 HR
N/X
TMP
DPT
CLD OV OV OV OV OV OV OV OV OV OV OV OV OV SC BK BK BK SC CL SC OV
WDR
WSP P P Q Q
T / 0 2/ 1 0/ 1 0/ 0 0/ 0 0/ 0 0/ 0 0/ 0 0/ 3 0/ 0
T / / / / / 3
POZ
POS
TYP S R S S S S S S S S S S S S S S S S S S S
SNW
CIG
VIS
OBV BR BR BR BR N N N N N N N N N N N N N N N N N

3. GFS MODEL
Station: UNV Lat: Lon: Elev: 378 Closest grid pt: 29.6 km.
Initialization Time: UTC
HOUR VALID PMSL THCK 6HRPCN 2m_TMP 850TMP 850REL 700REL 10m_WD 850WND
/ /003 20/026
/ /005 20/037
/ /005 26/018
/ /014 34/028
/ /014 33/034
/ /014 31/027
/ /013 31/032
/ /011 31/031
/ /010 30/032
/ /013 30/025
/ /008 30/027
/ /003 28/019
/ /007 24/023

4. MOS AVN = Dynamical Model Seven fundamental equations !
AVN MOS = Statistical Model
No seven fundamental equations !
Equations are statistical, not dynamical !

5. MOS Why even have MOS ? Predicts unique parameters
Visibility
Cloud ceilings
Predicts better than dynamic models (averaged over all cases)
Surface weather-> temp., dew pt., winds

6. MOS How does MOS make its predictions? Uses technique of association
Objectively relates (associates) model output to observed weather using statistical technique of linear regression

7. MOS
Two steps to MOS ……….
Equation Development
Equation Application

8. MOS Equation Development ->> Linear Regression PREDICTOR
Variable that is doing the PREDICTING
PREDICTAND
Variable that is getting PREDICTED
Linear Regression
Relates PREDICTOR to PREDICTAND

9. MOS: Equation Development
Y1 = mx1 + b1

10. MOS: Temperature Predictors Single site development
Model low level temps (i.e. 850mb/2m)
Model relative humidity
Accounts for clouds
Model wind direction /speed
Climatology
Previous days min (max)
Single site development

11. MOS: Precipitation Predictors Regional development
Model mean relative humidity (i.e mb layer average)
Precipitation output of model
Model vertical velocity (i.e. 700, 500, 850mb)
Model low level wind direction (i.e. 10m)
Regional development

12. MOS: Wind Predictors Single site development
Low-level wind direction/speed output of model (i.e. 10m, 850mb wind)
Single site development

13. MOS Characteristics Requires large sample size
Several years of model output
Increases statistical significance

14. MOS Partially removes systematic model errors (i.e. biases)
If model has a cool bias at 850mb, MOS will account for/remove model bias
Works best when models are not tweaked (i.e. no change to physics)

15. MOS: Equation Application

16. GFS MOS KUNV GFS MOS GUIDANCE 2/26/2008 1200 UTC
DT /FEB 26/FEB /FEB /FEB 29 HR
N/X
TMP
DPT
CLD OV OV OV OV OV OV OV OV OV OV OV OV OV SC BK BK BK SC CL SC OV
WDR
WSP P P Q Q
T / 0 2/ 1 0/ 1 0/ 0 0/ 0 0/ 0 0/ 0 0/ 0 0/ 3 0/ 0
T / / / / / 3
POZ
POS
TYP S R S S S S S S S S S S S S S S S S S S S
SNW
CIG
VIS
OBV BR BR BR BR N N N N N N N N N N N N N N N N N

17. GFS MODEL
Station: UNV Lat: Lon: Elev: 378 Closest grid pt: 29.6 km.
Initialization Time: UTC
HOUR VALID PMSL THCK 6HRPCN 2m_TMP 850TMP 850REL 700REL 10m_WD 850WND
/ /003 20/026
/ /005 20/037
/ /005 26/018
/ /014 34/028
/ /014 33/034
/ /014 31/027
/ /013 31/032
/ /011 31/031
/ /010 30/032
/ /013 30/025
/ /008 30/027
/ /003 28/019
/ /007 24/023

18. MOS ERRORS: Who’s at fault?
Dynamic model (gfs model)
Garbage In = Garbage Out
Statistical model (gfs mos)
Imperfect statistical relationships
(i.e. lines of best fit are not line of prefect fit!)
Forecasting MOS error
(utilizing association method)