1. OceanSITES: NCEI is set to automatically archive and this moored buoy time series dataset with regular updates. These data will be part of all future World Ocean Database (WOD) quarterly updates. While the TAO, PIRATA, and RAMA equatorial moored buoy arrays are already part of WOD (through the Pacific Marine Environmental Lab, PMEL) other moored buoys will add valuable oceanographic profile information (Figure 1b), limited in geographic coverage, but with high time resolution. Figure from http://www.oceansites.org/images/OceanSITES_10April2015V1.png Blended fields of Sea Surface Salinity (SSS) (Xie et al., 2014) using satellite data - Aquarius, Soil Moisture and Ocean Salinity (SMOS) and one-degree gridded in situ salinity calculated as described in (2) above from the Global Temperature and Salinity Profile Programme (GTSPP). Above are slides taken directly from the May, 2015 Climate Prediction Center (CPC) Monthly Ocean Briefing. (courtesy P. Xie). The World Ocean Database (WOD) is the World's largest publicly available quality controlled uniformly formatted oceanographic profile database. It contains nearly 14 million oceanographic casts (collocated profiles of temperature, salinity, oxygen, nutrients, plankton counts, etc.) collected from 1772 to the present year, updated quarterly. An expanding suite of ocean climate time series related to ocean heat and freshwater content are updated quarterly. Efforts are ongoing to increase the sources of data available in the WOD, both from Climate Program Office projects and other domestic and international entities and to improve the quality control of the data. Efforts are also ongoing to increase the availability of WOD data to researchers, with a particular emphasis on machine-to-machine discovery and delivery. Finally, research into new uses of the data for climate research in support of newer programs such as the Aquarius sea surface salinity mission and to increase the certainty of existing climate records are being carried out using the WOD. One main purpose of quarterly updates of the World Ocean Database is to calculate quarterly (3-month) ocean climate variables. Data aggregated for the three month period (Figure 2a) are binned in one-degree geographic boxes and an anomaly calculated from a baseline climatological mean. Temperature anomalies are converted to ocean heat content and integrated over depth (Figure 2b). Integrating globally gives an estimate of quarterly ocean heat content anomaly (Figure 2c) to add to the time series which extends back to 1955. Thermosteric sea level change (Figure 2d) is also computed, as well as halosteric sea level change from salinity anomalies. This allows computation of total steric sea level change (Figure 2e). Other related climate variables, such as mean temperature and salinity anomalies over different depth intervals are calculated (Figure 2f). All data and figures are posted to http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/ during the following quarter. Enhancements to the project in the near-future include calculation of mixed-layer depth changes and heat and salt climate variables using finer depth intervals so a user can construct a time series to the ocean depth to which they are interested. World Ocean Database Activities in Support of Climate Studies Tim Boyer*, Olga Baranova, Carla Coleman, Hernan Garcia, Alexandra Grodsky, Daphne Johnson, Ricardo Locarnini, Alexey Mishonov, Rost Parsons, Christopher Paver, James Reagan, Dan Seidov, Igor Smolyar, Charles Sun, Melissa Zweng Ocean Climate Lab Team/National Centers for Environmental Information *corresponding author: tim.boyer@noaa.gov 1. New Data Sources for the World Ocean Database2. Ocean Climate Variables using the World Ocean Database 3. New Products and Research Involving the World Ocean Database: Example - Sea Surface Salinity Average monthly difference between the World Ocean Database (WOD) sea surface salinity (SSS) data and Aquarius v3.0 SSS products using Aquarius Data Processing System (ADPS) algorithm (Figure 3a) and Combined Active Passive (CAP) algorithm (Figure 3b) for the 09/2011-12/2014 time period. The CAP algorithm is shown to be in stronger agreement than ADPS based on the Aquarius and in situ SSS zonal means (Figure 3c). Updated from Reagan et al. (2014). Linear trend of SSS anomalies (10yr -1 ) (Figure 3d) calculated from baseline mean World Ocean Atlas 2009 (WOA09) using World Ocean Database (WOD) salinity data (Argo, CTD, moored buoy, glider, and bottle), closest value to the surface above 5.25 m depth. Areas of increased salinity > 0.3 are present in the subtropical North Pacific. We are investigating correlations with the Pacific Decadal Oscillation (PDO) and El Niño/Southern Oscillation (ENSO). Increased salinities > 0.75 are along the eastern United States while freshening > 0.5 is west of Australia. 3 3 3 4. Improving data delivery for the World Ocean Database References: Antonov, J. I., S. Levitus, and T. P. Boyer, 2005: Thermosteric sea level rise, 1955-2003. Geophys. Res. Lett., 32, L12602, doi:10.1029/2005GL023112. Levitus, S., J. I. Antonov, T. P. Boyer, O. K. Baranova, H. E. Garcia, R. A. Locarnini, A.V. Mishonov, J. R. Reagan, D. Seidov, E. S. Yarosh, M. M. Zweng, 2012: World Ocean heat content and thermosteric sea level change (0-2000 m) 1955-2010. Geophys. Res. Lett., 39, L10603, doi:10.1029/2012GL051106 Reagan, J., T. Boyer, J. Antonov, and M. Zweng, 2014 : Comparison analysis between Aquarius sea surface salinity and World Ocean Database in situ analyzed sea surface salinity, J. Geophys. Res. Oceans, 119, 81228140, doi:10.1002/2014JC009961 Xie, T., T. Boyer, E. Bayler, Y. Xue, D. Byrne, J. Reagan, R. Locarnini, F. Sun, R. Joyce, and A. Kumar, 2014 : An in situ - satellite blended analysis of global sea surface salinity. J. Geophy. Res. Oceans, 119, 6140 - 6160, doi: 10.1002/2014JC010046 Rolling Deck To Repository (R2R): The concerted efforts by the University-National Oceanographic Laboratory System (UNOLS) to capture and quickly disseminate oceanographic data collected from their research fleet has a parallel effort in NOAA. While the efforts are centered on navigation and meteorological data, oceanographic surface and profile data are also included. The NOAA fleet (Figure 1d) has many ships making oceanographic observations. The subsurface profile data are either already being sent or in the process of being set up to send to the NCEI and uploaded to the World Ocean Database. Data are mainly from US coastal and shelf regions, but also include substantial open ocean data. (Ship photographs from http://www.moc.noaa.gov/ ) 1d Gliders: This type of data collection is becoming steadily more widespread in the oceanographic community. There has been a concerted effort to incorporate these data into the World Ocean Database (WOD). Gliders routinely cover areas not visited by Argo floats, such as shelf regions (Figure 1c), adding valuable information in undersampled regions. WOD is incorporating data regularly from the Australian Integrated Marine Observing System (IMOS), as well as the US Integrated Ocean Observing System (IOOS) Glider Data Assembly Center (DAC), from the University of Washington Applied Physics Lab (APL) and now from Oregon State University (not shown). There is still much work to be done to aggregate these data, including acquiring data from the European Glider DAC. A time series of oceanographic profile data in the World Ocean Database (WOD) as of the end of 2014 (Figure 1a) shows the evolution of the ocean observing system. Argo is the dominant data source in the last 10 years. Glider data has been steadily increasing over the last 5 years, reaching a high in 2013 (not all 2014 data were incorporated yet). Pinniped data has been erratic, but NCEI is beginning work with an Animal Telemetry Network Data Assembly Center (ATNDAC). XBT and CTD data are steady and important data streams. 1c 1b 1a 3d 2a 2b 2c 2d 2e 2f