1. LT Sarah Heidt 9 September 2008
A Comparison of MBARI II Buoy Temperature and Salinity Measurements to SODA and GDEM Climatology
LT Sarah Heidt
9 September 2008
Figure on left:
Figure on right:

2. MBARI II Buoy Data Overview Data Quality Control
GDEM Database Overview
SODA Database Overview
Buoy vs. GDEM & SODA Temperature Comparison
Buoy vs. GDEM and SODA Salinity Comparison
Future Work & Conclusions

3. MBARI II BUOY DATA COLLECTION
The joys of data collection…
Although the MBARI data was not collected as part of the cruise, the buoy is often recovered/redeployed by the Point Sur…
MBARI II Buoy Position:
36.70N W
The OASIS project began in 1992
Temperature & Salinity are collected and recorded every 10 minutes
Due to fouling and poor data quality, salinity data was only available and analyzed from
Due to poor data quality, temperature analysis only covered data from
Photo:

4. MBARI II BUOY DATA QUALITY CONTROL
Data Quality Control for MBARII II begins with Fred Bahr…
Run an automated QC check for gross outliers
Review data depth by depth… variable by variable… flagging data that may potentially be “bad”
Salinity data spikes seem to be more apparent then temperature spikes and are likely due to instrument fouling
Temperature spikes are harder to discern… a perceived “bad” data point/s could be due to an internal wave

5. GENERALIZED DIGITAL ENVIRONMENTAL MODEL (GDEM) OVERVIEW
WHAT IS GDEM???
A global ocean climatology data base of temperature and salinity
Developed by the Naval Oceanographic Office in 1975 and first released to the Navy in 19841
Most current release used by the Navy is GDEM3 (1995)
Computed from in-situ temperature and salinity profiles extracted from the Master Oceanographic Observational Data Set (MOODS)1
GDEM3
3D monthly grids of temperature, salinity, temp sd, and salinity sd
Spatial coverage: 0°-360°E & 60°S-90°N1
Temporal Coverage: (75 years)1
Horizontal grid resolution: .25° x .25°1
Vertical grid: 78 depths from surface to 6600m1
GDEM January LTM grid point 477,952 (36.75N W) used for comparison purposes with MBARI buoy data
LTM » mean of many observations collected over a long period of time (30yrs)2

6. SIMPLE OCEAN DATA ASSIMILATION (SODA) OVERVIEW
WHAT IS SODA?
A global reanalysis database of upper ocean temperature, salinity, and currents using OI data assimilation3
A reanalysis uses modern analysis processes to analyze past and present states of the climate system by applying a consistent set of analysis procedures to all times in the reanalysis period yielding gridded data sets that are temporally and spatially continuos2
SODA 1.4.3
Assimilated data includes: temperature & salinity profiles from the World Ocean Atlas-94 (MBT (prior to mid-1980’s), XBT, CTD, & station data) as well as hydrography, SST, and altimetry data (post 1986)3
Spatial Coverage: E & 75.25S-89.25N2
Temporal Coverage: (46 years)2
Horizontal resolution: .5 x .5 degrees2
Vertical resolution: 40 levels ( m)2
SODA January mean grid point 254,476 (36.75N W) used for comparison purposes with MBARI buoy data
Reanalysis ->
Same as atmospheric or oceanic analysis, except not done in real time
Major source of climate data since they fill in many of the spatial and temporal gaps in observations of the climate system
Typically done for multi-year or multi-decadal periods

7. WHAT IS BEING COMPARED? MBARI II JANUARY BUOY DATA
Depths – 0, 10, 20, 40, 60, 80, 100, 150, 200, 300, 500 meters
Mean Temperature data
Mean Salinity data
SODA JANUARY REANALYSIS DATA
Depths – 5, 15, 25, 35, 46, 57, 70, 82, 96, 112, 129, 148, 171, 197, 229, 268, 317, 381, 465, 579 meters
SODA Period Mean Temperature data
SODA Period Mean Salinity data
GDEM JANUARY LTM DATA
Depths – meters (42 levels)
GDEM LTM Temperature
GDEM LTM Salinity
BUOY -> take the mean of all the measured data in January at that point
SODA ->takes all collected data and uses a set of algorithms, assimilation schemes, and model to generate reanalysis fields (mean temperature) of a gridded area of .25 X .25
GDEM -> takes all collected data and determines the LTM over a number of years for a .5 X .5 gridded area.

8. JANUARY 1994 TEMPERATURE MEANS
Of note:
Obviously these do not exactly line up, nor should we expect the three data sets to show the exact same results since they are representing different (however similar things).
However… analysis such as this can help us determine the consistency/verification of climatology with actual weather.

9. JANUARY 1995 TEMPERATURE MEANS

10. JANUARY 1996 TEMPERATURE MEANS
SODA tends to capture the general temp vs. depth pattern especially the surface variability.
In this one case SODA captured the temperature inversion near the surface

11. JANUARY 1997 TEMPERATURE MEANS
SODA is again consistent with the general temp. vs. depth pattern at the surface.
Here the GDEM LTM is consistent with the mean of the measured buoy data.

12. JANUARY 1998 TEMPERATURE MEANS
GDEM shows relative inconsistency with SODA and the buoy.
JAN98 happens to be a strong El Nino year with warmer then normal water in the EastPac.
SODA is more consistent then GDEM in capturing the warmer then normal variability due to the JAN98 El Nino.

13. JANUARY 1999 TEMPERATURE MEANS
Here we see consistency with GDEM and the buoy below 100m and again reasonable consistency with SODA capturing the general surface variability pattern in the upper 100m.

14. JANUARY 2000 TEMPERATURE MEANS
Below 150 meters in many of these figures SODA is fairly inconsistent with the buoy.
Possible Reasons:
Poor representation of deep currents
Not enough data below 150 meters
MBARI buoy location may not be representative of the grid area that SODA is representing.

15. JANUARY 2001 TEMPERATURE MEANS
SODA is again consistent with the general pattern of the buoy temp vs. depth.
GDEM not consistent at the surface.

16. JANUARY 2002 TEMPERATURE MEANS

17. JANUARY 2003 TEMPERATURE MEANS

18. JANUARY 2004 TEMPERATURE MEANS
SODA again consistently cooler at deeper depths but capturing the general surface variability pattern.
GDEM also capturing the general pattern of the buoy except near the surface.

19. JANUARY SEA SURFACE TEMP TIME SERIES
For further comparison...apply conditional climatology
Warmest JAN years via Time Series -> 1994,1996,1998,2003
Coldest JAN years via Time Series -> 1999, 2000, 2002
Green Circles = 3 Warmest JAN years Blue Square = 3 coldest JAN years
Figure from:

20. MBARI VS. SODA & GDEM TEMPERATURE MEANS
SODA cold, warm, and LT mean temps are consistent with MBARI means from the surface to approximately m
SODA is far less consistent and generally cooler then MBARI below 100 m suggesting inaccuracies in interpreting the deeper ocean or the lack of data in the deep ocean
GDEM LTM is inconsistent with MBARI and SODA warm/cold/LT means at the surface and is generally cooler then MBARI below 100 meters

21. TAKING THIS ONE STEP FURTHER
Using conditional climatology by selecting the 3 coldest and 3 warmest years from the 10 year data set we can infer a La Nina pattern in the EastPac during the 3 coldest years and an El Nino pattern in the EastPac during the 3 warmest years.
SST – Coldest Years
SST – Warmest Years
Figures created at:

22. JANUARY 1999 SALINITY MEANS
Following this relatively short salinity data set of 6 years it seems that GDEM is more consistent with MBARI buoy data for higher salinity years ( ) then SODA.

23. JANUARY 2000 SALINITY MEANS

24. JANUARY 2001 SALINITY MEANS
GDEM is very consistent with MBARI in highest salinity years in 2001 & 2002.

25. JANUARY 2002 SALINITY MEANS

26. JANUARY 2003 SALINITY MEANS
SODA is more consistent with MBARI buoy data in years of decreased salinity (2003 & 2004).

27. JANUARY 2004 SALINITY MEANS

28. MBARI VS. SODA & GDEM SALINITY MEANS
Keeping in mind the smaller set of data ( ) we can see here that :
GDEM captures the general pattern of the MBARI high salinity years more so then any SODA LTM/high/low salinity years
SODA low salinity years capture the general pattern of the MBARI low salinity years and SODA in general captures the MBARI low salinity years

29. CONCLUSIONS
Both SODA and GDEM are fairly good at capturing the general characteristics of the temperature & salinity profiles for MBARI II
Temperature Profiles
SODA consistently captured the surface variability that GDEM did not… this may be due to a great number of measurements at the surface going into the SODA database
SODA and GDEM were consistently cooler then MBARI below 100m
The buoy collects data for one specific point, whereas SODA and GDEM represent a gridded area that in a coastal location such as MBARI could make a large impact on data consistency
Salinity Profiles
SODA was more consistent with MBARI data years of decreased salinity
GDEM was more consistent with MBARI data years of increased salinity
Only 6 years could be compared… this is not substantial
Limited years of MBARI buoy data make it difficult to make substantial comparison conclusions
It would be hard to conclude that SODA is ‘more accurate’ than GDEM or vice versa… SODA has a large advantage over GDEM in that it has much higher temporal resolution allowing for more complete analysis and increased potential for climate scale forecasting – so why doesn’t the Navy use it?
There is more work to be done in making SODA and GDEM more easily accessible and manageable for operation and research applications.
FUTURE WORK: Do similar research with longer data sets and more buoys

30. MY THANK YOU SLIDE SPECIAL THANKS TO:
LCDR Allon Turek for his assistance with obtaining data from and understanding the GDEM and SODA database
Mike Cook for his patience and assistance with MATLAB coding
Dr. Tom Murphree for his guidance on how to best interpret/understand the collected data
Fred Bahr & Prof. Curt Collins for their time and help with obtaining the MBARI II buoy data

31. REFERENCES
Carnes, Michael R., Description and Evaluation of GDEM-V 3.0, Naval Oceanographic Office (N312), April 29,2003.
Murphree, T., and B. Ford, Smart Climatology for Antisubmarine Warfare: Initial Assessments and Recommendations. Brief to CAPT Jim Berdeguez, CNMOC, Stennis Space Center, MS, 14 August 2007, slide 16.
Carton, James A., Chepurin G., & Cao X. A Simple Ocean Data Assimilation Analysis of Global Upper Ocean Part I: Methodology, Journal of Physical Oceanography, 2000, Vol. 30.
Earth Systems Research Laboratory Website: