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: http://www.mbari.org/bog/Projects/MOOS/methods.htm Figure on right: http://www.mbari.org/oasis/index.html

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

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 122.39W 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 1999-2008 Due to poor data quality, temperature analysis only covered data from 1994-2008 Photo: http://www.weather.nps.navy.mil/~psguest/OC3570/CDROM/imagesaug08/

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

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: 1920-1995 (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 122.25W) used for comparison purposes with MBARI buoy data LTM » mean of many observations collected over a long period of time (30yrs)2

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: 0-360E & 75.25S-89.25N2 Temporal Coverage: 1958-2004 (46 years)2 Horizontal resolution: .5 x .5 degrees2 Vertical resolution: 40 levels (5-5374 m)2 SODA January mean grid point 254,476 (36.75N 122.25W) 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

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 1994-2004 Mean Salinity data 1999-2004 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 1994-2004 SODA Period Mean Salinity data 1999-2004 GDEM JANUARY LTM DATA Depths – 0-500 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.

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.

JANUARY 1995 TEMPERATURE MEANS

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

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.

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.

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.

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.

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

JANUARY 2002 TEMPERATURE MEANS

JANUARY 2003 TEMPERATURE MEANS

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.

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 1994-2004 Green Circles = 3 Warmest JAN years Blue Square = 3 coldest JAN years Figure from: http://www.cdc.noaa.gov/cgi-bin/Timeseries/timeseries1.pl

MBARI VS. SODA & GDEM TEMPERATURE MEANS SODA cold, warm, and LT mean temps are consistent with MBARI means from the surface to approximately 50-75 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

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: http://www.cdc.noaa.gov/cgi-bin/Composites/printpage.pl

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 (1999-2002) then SODA.

JANUARY 2000 SALINITY MEANS

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

JANUARY 2002 SALINITY MEANS

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

JANUARY 2004 SALINITY MEANS

MBARI VS. SODA & GDEM SALINITY MEANS Keeping in mind the smaller set of data (1999-2004) 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

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

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

REFERENCES Carnes, Michael R., Description and Evaluation of GDEM-V 3.0, Naval Oceanographic Office (N312), April 29,2003. Murphree, T., and B. Ford, 2007. 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 1950-95. Part I: Methodology, Journal of Physical Oceanography, 2000, Vol. 30. Earth Systems Research Laboratory Website: http://www.cdc.noaa.gov/cgi-bin/Composites/printpage.pl