presented by LCDR Allon Turek, USN 14 March 2008 Comparison of Ocean Station CTD data to the GDEM and SODA Climate Databases presented by LCDR Allon Turek, USN 14 March 2008

Why is this important to the U.S. Navy? Purpose: To test the hypothesis that ocean climatology databases accurately reflect the current ocean environment Why is this important to the U.S. Navy? Nearly all tactical decision aids used for under sea warfare (USW) and Mine Warfare (MIW) rely on ocean climatology databases to provide a characterization of the environment. If these databases do not accurately represent the environment then tactical decisions can be impaired.

Method: Compare accurate and detailed temperature and salinity measurements taken from oceanographic stations to various ocean climate databases. Ocean Station Data In February 2003 data was collected from 27 ocean stations along the California coast, from Monterey Bay to the southern tip of the Baha peninsula. Of the data recorded, only temperature and salinity data will be examined in this study Temperature and salinity were recorded every 2 meters Only downward measurements were used

* 10 station pairs sharing same location OCEAN STATIONS (Feb. 2003) 27 total stations (11 shallow [200m]) (16 deep [1000m]) * 10 station pairs sharing same location * 2 stations with incomplete data Feb. long term mean climatology sample Resulting in: - 15 independent climate comparison locations

Ocean Climate Databases Ocean climate data was extracted using a MatLab GUI interface that provided both graphic and text outputs from the GDEM and SODA data sets. Station # 19 * Special thanks to Prof. Tom Murphree, NPS Dept. of Meteorology and to Bruce Ford of Clear Science Inc. for providing invaluable service in accessing and processing multiple data sets. Bruce W. Ford, Clear Science, Inc., bruce@clearscienceinc.com, fordbw@tsc-jax.navy.smil.mil, http://www.ClearScienceInc.com, Phone/Fax: 904-379-9704, 7801 Lonestar Rd. Suite #17, Jacksonville, FL  32211

Method (cont.) Ocean Climate Databases SODA (Simple Ocean Data Assimilation) Variable grid resolution approx. 0.3 Degree (depending on latitude) 20 levels Long term mean (LTM) climatology (1958-2004) GDEM (Generalized Digital Environmental Model) 0.5 Degree grid resolution 41 levels (zero level was discarded to align w/ SODA) Long term mean (LTM) climatology (70 years)

Temperature (C) at Stations Monthly Mean SST for February Temperature (C) at Stations CTD #15 = 16.3600 #16 = 16.7948 GDEM #15 = 15.4 #16 = 16.2 SODA #15 = 15.2 #16 = 16.6 CTD GDEM LTM Figure from: http://www.cdc.noaa.gov/Timeseries/

GDEM and SODA LTM climatologies are smooth and similar Station # 4 GDEM and SODA LTM climatologies are smooth and similar Observed CTD data shows sharp changes actually occurring in the environment

Station # 9 Depending on location and season GDEM and SODA climatologies can produce a fairly accurate representation of the environment

Station # 11 Strong layer

Station # 13 Weaker layer

Station # 14 Climatologies are similar yet they miss the detail evident in the CTD plot

Sharp changes in environment are smoothed out in climo Station # 15 Sharp changes in environment are smoothed out in climo

Station # 16

Station # 17

Station # 18 Climatology can pick-up on sharp features if they are persistent throughout the population

Station # 22

Station # 25

Station # 27 Sometimes the trend in salinity or temperature can be opposite that of the actual environment

Average of Maximum Deviations from CTD Measurements Across Stations Temperature (C) Salinity GDEM 1.533 0.1490 SODA 1.140 0.216

Averages of Temperature and Salinity Correlation between CTD and Climatology across Stations GDEM .9791 .9192 SODA .9734 .8866

Conclusions: Current ocean climatology databases such as GDEM and SODA provide a close approximation of the environment offering a good first estimate Anomalous environmental conditions can cause sizable deviations of T and S from the LTM, especially near the ocean surface. LTM type climatology tends to smooth T and S profiles causing features such as layers and ducts to be missed

Conclusions(cont.): Comparison of CTD data to climatology within ASPECT (USW tactical decision aid) resulted in noticeably different ranges and sound propagation paths.

Future Work: Investigate if Smart Climatology can provide data that more closely matches observed data from CTD casts. Document differences in sound propagation based on various types of climatology vs. observed data Smart Climatology: http://met.nps.edu/smart-climo/index.php