1. Evaluation of a Statistical Refractivity Model using Observations from R/V PT SUR
OC3570
LCDR Henry A. Miller
18 September 2001

2. Overview Background Overview of the Model Evaluation Method
Accuracy Determining Duct Occurrence
Accuracy Determining Duct Height
Correlation with Duct Thickness
Correlation with Duct Strength
Recommended Model Changes
Conclusions

3. Background Decreased budget means rawinsondes frequently unavailable.
METOC personnel still required to provide RF propagation support.
Need low-cost method of determining refractive conditions.
Helvey and Rosenthal developed model for inferring from synoptic parameters.
I wrote FORTRAN program to incorporate their model.
Accessable via web.

4. Overview of the Model
Refractive conditions depend on temp and humidity.
Specifically inversion.
Identified relationships between observable parameters and ducting.
Assigns point values for each value.
Sum the points.
Divide by weighting factors.
Resulting number equates to probability of ducting.

5. Evaluation Method Model run using observations:
Ship observations
ETA model analyses.
GOES-10 satellite imagery
700mb temp from sounding.
Observed ducts determined from soundings (M profile).

6. Evaluation Method M units
Ducting is determined by gradient of refractivity N.
Ducting occurs when grad(N)≤ m-1 so we define modified refractivity M
Ducting occurs when M is vertical or has negative gradient.

7. Evaluation Method “Unlikely” and “possible” – negative.
“Probable” and “very likely” – positive. 1
Duct assessed
Duct observed 2
No duct observed 3
No duct assessed 4
Heights compared directly.
Within 15% considered correct.

8. Evaluation Limitations
Only 13 observations.
All cases in same quadrant of high.
Duct occurred in all cases.
All cases in Pacific.

9. Accuracy Determining Duct Occurrence
Model assessed duct in all cases.
“Probable” 5 times.
“Very likely” 8 times.
Duct observed in all cases.
Model appears to be very accurate in determining duct occurrence in these conditions.

10. Accuracy Determining Duct Height
NO SKILL at estimating duct height.
Only correct 1 of 13 cases.
Estimates duct too low 76.9% of time (10 of 13).
Average model 478m.
Average observed 786m.
Possible reasons for error:
Wind mixing.
Point SST observations.

11. Correlation with Duct Thickness
Considered possible correlations between duct occurrence probability and duct thickness or strength.
“Probable” – m, ave 266.2m
“Very likely” – m, ave 190.9m
Conclusion: No correlation.

12. Correlation with Duct Strength
Strength of a duct is determined by the difference in min and max modified refractivity in the duct.
“Probable” – 8-34, ave 17.0
“Very likely” – 3-26, ave 11.4
Conclusion: no correlation.

13. Recommend Model Changes
The height estimation algorithm probably needs a lot of work.
Use air/sea temp as stability vice sfc/700mb temp.
Shallow inversion may be missed.
700mb temp may introduce model error.
Use regional ave SST instead of point observation.
Incorporate wind speed into height estimate.

14. Conclusions Definitive accuracy cannot be established.
Model appears to be very accurate at determining duct occurrence.
No skill at estimating duct height.
No correlation with duct thickness or strength.