1. Effects of various SST sources on estimates of the Height of the Stratocumulus Topped Boundary Layer
LCDR Mike Cooper

2. Overview McBride’s Motivation McBride Method / NPS Model
Why do we need this capability?
McBride Method / NPS Model
The theory behind the madness
The Purpose of this Study
What am I adding to the cause?
Data Collection
The agony!
Analysis and Results
What SST source produced the best results
Conclusions and Recommendations
Do I think it really works

3. Motivation
Most areas of the world have at least a 40% chance of ducting.
The top of a stratocumulus topped boundary layer marks the axis of a duct.
Ducts have significant effects on RADAR operation, but this is a separate topic.

4. McBride/NPS Method Physically Based Method Strong Subsidence TCT
Inversion Depth
Marine Stratocumulus
LCL
Dry Adiabatic Lapse Rate TS
DT = TCT - TS
Ocean

5. McBride/NPS Method Assumptions Adiabatic Lapse Rates
Unsaturated air follows the dry adiabatic lapse rate (Γd)
Saturated air follows a case dependent pseudo or moist adiabatic lapse rate (Γm)
The Boundary layer is coupled
No inversion below top
The surface air temperature is equal to the sea surface temperature
TA=TS
May not always be true
The cloud top temperature is equal to the 11m brightness temperature
TCT=TB
May not always be true…..unless

6. McBride Method Assumptions-Cont.
The atmosphere has a negligible amount of water vapor above the layer or the water vapor content is known and corrected for
Assuming no vapor has some error
Since the structure of the STBL is unknown you must assume a certain percentage of cloud
Must Assume that the STBL is optically thick
That is no photon from below in the cloud top temp estimate.

7. Procedure of the NPS Model
Step 1: Using the measured ∆T and the dry adiabatic lapse rate, estimate the boundary layer depth with no clouds (all temperatures in °C, lapse rates in °C/m, heights in meters).
Zdry = ∆T / Γdry (3)
Step 2: Assuming a vertical cloud fraction of 1/3 (meaning 2/3 cloud-free), estimate the height of the cloud base for a 2/3 cloud-free boundary layer.
ZCloudBase = 2/3 * Zdry (4)
Step 3: Using the dry adiabatic lapse rate, Γdry, and the sea-surface temperature, TS, estimate the cloud-base temperature for a 2/3 cloud-free boundary layer.
TCloudBase = Γdry* ZCloudBase + TS (5)
Step 4: Using the measured cloud-top temperature, TCT, the estimated cloud-base temperature, TCloudBase, and the pseudo-adiabatic lapse rate, Γmoist, estimate the cloud depth (m).
CloudDepth = ( TCT - TCloudBase ) * Γmoist (6)
Step 5: Compute the cloud-top height, ZCloudTop, using the estimates of cloud-base height and cloud depth.
ZCloudTop = ZCloudBase + CloudDepth (7)
Step 6: If the cloud-top height is less than 400 meters, recompute the cloud-top height using an assumption of 2/3 vertical cloud fraction (meaning 1/3 cloud-free). Use Equation 4 with a cloudfree ratio of 1/3 vice 2/3. Using the new estimate of cloud-base height, use Equations 5-7 to generate a new, higher estimate of cloud-top height. The rationale for this step is that shallow STBLs typically have a higher vertical cloud fraction. The 400m break point was determined from observation by McBride (2000).

9. This Study? First Second
Looks at both 2 temperature fields compared to ground truth
Ground truth being the physical SST measurement on the boat
Which field is closer to ground truth?
Which would you predict to do a better job at height prediction?
Second
Looks at the STBL HT predictions from both SST fields using the cloud top temp from one souce and compares them to ground truth
Ground truth being the STBL HT as indicated in the Sonde Profile (Hght of the inversion)

10. How did I get TCT ?
GOES (Geostationary Operational Environmental Satellite)

11. A little RS theory review
L is the spectral radiance
B is the planks blackbody emittance as a function of ya know

12. GOES Data field

13. How did I get SST NCOM (NRL Coastal Ocean Model)
1/8º Resolution (~15-16km grid)
Shorter 5-7 day forecasts with a nowcast
Forced by NOGAPS
Derives mesoscale information from the 3-D MODAS T and S fields which are derived from the NRL Layered Ocean Model (NLOM) and MODAS SST analysis
Forced into a 4km grid template in Terascan so data is taken from the same central pixel as the GOES data

14. NCOM Data Field

15. How did I get SST NAVO K10 MCSST field
Multi-Channel Sea Surface Temperature field
Created from multiple AVHRR channels
Daytime
SST=1.0346T (T11-T12)
Nighttime includes T3.7 which is contaminated during the day
1/10º resolution (~11-12km)
Forced into a 4km grid template in Terascan so data is taken from the same central pixel as the GOES data

16. NCEP Data Field

17. UDAS SST Comparison
Clearly the mean would be zero, but the boom temp extremes seem to be a little more “extreme”
For the first part of this study the locker temp was used as the reference

18. K10 Leg 1
Within a degree….not bad

19. NCOM Leg 1
Within a degree..but K10 wins

20. K10 Leg 2
Still within a degree….

21. NCOM Leg 2
Out to lunch…K10 wins again

22. K10 Leg 3
Now above the one degree mark

23. NCOM Leg 3
Still out to lunch…K10 wins

24. Now lets look at the height predictions

25. 326m
302m
326m

26. 432m
431m
388m

27. 363m
321m
336m

28. 396m
577m

29. Results
Anyone want to guess which turned out better?

30. Ground Truth?????
What do you think this will look like?
What???

31. Conclusions and Recommendations
Surprisingly, yet clearly, the NCOM SST field produced better height results in this limited study
The method may need some tweaking if the K10 fields are going to continue to be the source
Recommendations
Conduct a more thorough study using NCOM data and K10 data
Conduct a more thorough study into why the field that was further from ground truth (NCOM) produced a height field closer to ground truth