Since 1982, the Levitus Climatological Atlas of the World’s Ocean and each succeeding World Ocean Atlas have been used to provide initial and boundary conditions for modeling studies, as well as baselines for climate studies. However, there has been a broadening demand for ocean modeling on spatial scales finer than 1-degree resolution [e.g., Penduff et al., 2010]. Likewise, vertical resolution for isobaric coordinate models is important for realistic representation of ocean processes [Wang et al., 2008].

As models increase their horizontal and vertical resolution, long-term in situ climatological averages on a 1-degree grid may not be sufficient initial and boundary conditions [e.g., Wakelin et al., 2009]. Further, as studies of climate change focus on regional (in addition to global) cause and effect, long-term, ­higher-resolution mean fields of oceanographic variables are needed to better resolve ­near-coastal areas, processes, and features [Kim et al., 2007]. The World Ocean Atlas 2013 (WOA13) seeks to address these needs.

Higher-Resolution In Situ Climatological Mean Fields

Greater awareness of the oceans’ role in global climate change has led to improved acquisition, dissemination, and quality control of oceanographic data through international observational projects such as Argo and Climate and Ocean: Variability Predictability and Change (­CLIVAR), and data aggregation projects such as Global Oceanographic Data Archaeology and Rescue (­GODAR).

The more abundant data of higher quality and resolution have allowed for WOA13 global climatological mean fields at finer horizontal resolution than previous versions, increasing to .25 degree for temperature and salinity. Vertical resolution also has markedly improved: Instead of calculating means of temperature, salinity, and nutrient concentrations (for oxygen, phosphate, nitrate, and silicate) on 33 standard depth levels, the current atlas expands to 102 standard depth levels.

More Realistic Oceanographic Features With Higher Resolution

­Higher-​­resolution climatological means are critical for discerning oceanic features that are of great importance not just to climate systems but also to nutrient cycling and biological habitat.

For example, the Gulf Stream is a major large-scale feature of the North Atlantic Ocean, yet it is not well resolved horizontally (Figure 1a) in the ­1-degree WOA13 annual mean temperature maps, which show the warm Gulf Stream waters extending all the way to the coast.

Fig. 1. Gridded mean annual temperature ( °C) off the southeast coast of the United States. (a) 1-degree horizontal resolution at 10 meters depth and (b) ­.25-degree horizontal resolution at 10 meters depth. Black line represents 31.5ºN, the latitude of profiles in Figures 1c, 1d, and 1e. (c) Low vertical resolution profile from 0 to 200 meters in depth along 31.5°N, ­1-degree horizontal resolution (from the World Ocean Atlas 2009; see; (d) high vertical resolution profile from 0 to 200 meters in depth along 31.5ºN, ­1-degree horizontal resolution; and (e) high vertical resolution profile from 0 to 200 meters in depth along 31.5°N, ­.25-degree horizontal resolution. Note how the increase in the number of standard depth levels from 2009 to 2013 improves vertical resolution, and how ­.25-degree horizontal resolution mean fields also make features more distinguishable.

By contrast, the WOA13 ­.25-degree field (Figure 1b) reveals cooler shelf waters. Figures 1c, 1d, and 1e demonstrate the improvement at higher vertical resolutions on zonal cross sections of the western North Atlantic along 31.5°N.

It should be noted that WOA13 on isobaric standard depth levels may represent oceanographic features differently than isopycnal analyses (isopycnal analyses are better equipped to highlight coherent water masses), especially in ­high-gradient areas such as the Gulf Stream [see Lozier et al., 1994]. WOA13 temperature and salinity climatological mean fields have been stabilized with respect to density to preserve consistency between these fields despite separate objective analyses.

Decadal Climatologies, Including Decadal Average Climatology

In historically undersampled areas such as the Southern Ocean, the data distribution is biased toward the Argo period for temperature and salinity. In the Northern Hemisphere, observations are spread more consistently over time. Due to this imbalance, if each observation was given equal weight, the climatological mean fields in each hemisphere would represent a different time frame [Wijffels et al., 2008; Figure S1a], a condition exacerbated with increasing depth [Wijffels et al.; 2008, Figure S1b]. To address these biases, WOA13 temperature and salinity climatological means are averages of six decadal climatologies calculated for the periods 1955–1964, 1965–1974, 1975–1984, 1985–1994, 1995–2004, and 2005–2012. The final climatological mean fields then encompass the 1955–2012 period with equal contribution from each of the six decades.

Other works use only Argo data from its ­near-global coverage period (2004 to the present) to calculate climatological means, [e.g., Roemmich and Gilson, 2009]. The balanced hemispheric coverage by Argo in this era eliminates any time biases between hemispheres. However, there are areas, such as continental shelves, that are not well represented by Argo, and the Argo ­full-coverage era is relatively short compared to scales of decadal variability. Using available historical data back to 1955 ensures representation from ocean conditions that were not present during the Argo period, such as strong El Niño events, allowing WOA13 to generate more robust estimates of long-term means and standard deviations.

In addition to the main ­6-decade-averaged WOA13 product, each decadal set of temperature and salinity fields is available to facilitate studies of climate change with a baseline mean most appropriate for a given study. Nutrient and oxygen climatologies use all available ­quality-controlled data regardless of year.

Accessing WOA13 Data

Atlases with descriptions of techniques and resultant fields for the different oceanographic variables, data, and documentation are available on the National Oceanographic Data Center (NODC) website (­1r32dEz) and through the WOA13 Digital Object Identifier (DOI;


This work was partially supported by the U.S. National Oceanic and Atmospheric Administration’s Climate Program Office. We acknowledge Sydney Levitus for his pioneering work in ocean climatology. We especially acknowledge all the projects that funded data acquisition; the researchers who measured, calibrated, and quality controlled ocean profile data; and the providers who made the data available to the NODC archive.We thank Melanie Hamilton for her contribution to the World Ocean Atlas.


Kim, H.-S., A. Gangopadhyay, L. K. Rosenfeld, and F. L. Bub (2007), Developing a high-resolution climatology for the Central California coastal region, Cont. Shelf Res., 27, 2135–2161.

Lozier, M. S., M. S. McCartney, and W. B. Owens (1994), Anomalous anomalies in averaged hydrographic data, J. Phys. Oceanogr., 24, 2624–2638.

Penduff, T., M. Juza, L. Brodeau, G. C. Smith, B. Barnier, J. Molines, and G. Madec (2010), Impact of global ocean model resolution on ­sea-​­level variability with emphasis on interannual time scales, Ocean Sci., 6, 269–284.

Roemmich, D., and J. Gilson (2009), The 2004-2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo Program, Prog. Oceanogr., 82, 81–100.

Wakelin, S. L., J. T. Holt, and R. Proctor (2009), The influence of initial conditions and open boundary conditions on shelf circulation in a 3D ocean-shelf model of the North East Atlantic, Ocean Dyn., 59, 67–81.

Wang, Q., S. Danilov, and J. Schröter (2008), Comparison of overflow simulations on different vertical grids using the Finite Element Ocean Circulation Model, Ocean Modell., 20, 313–335.

Wijffels, S. E., J. Willis, C. M. Domingues, P. Barker, N. J. White, A. Gronell, K. Ridgway, and J. A. Church (2008), Changing expendable bathythermograph fall rates and their impact on estimates of thermosteric sea level rise, J. Clim., 21, 5657–5672.

—Tim P. Boyer, Hernan E. Garcia, Ricardo A. Locarnini, and Melissa M. Zweng; National Oceanographic Data Center (NODC), U.S. National Oceanic and Atmospheric Administration (NOAA), Silver Spring, Md.; ­email: tim​.­boyer@​noaa​.gov; Alexey V. Mishonov and James R. Reagan, NODC and Cooperative Institute for Climate and Satellites (CICS), Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park; John I. Antonov, NODC and University Corporation for Atmospheric Research, Boulder, Colo.; Olga K. Baranova, NODC; Mathew M. Biddle, NODC and CICS; and Daphne R. Johnson, and Christopher R. Paver, NODC

© 2014. American Geophysical Union. All rights reserved.

© 2014. American Geophysical Union. All rights reserved.