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Southwest North Atlantic Regional Climatology

The Southwest North Atlantic (SWNA) region is a resource-rich coastal zone with abundant fisheries and other material resources adjacent to the area covered by the Northwest Atlantic Regional Climatology. Together, they provide complete coverage of the Gulf Stream system, which is critical to northward heat transport and the Atlantic Meridional Overturning Circulation. The climatology is a collection of high-resolution quality-controlled temperature and salinity fields on standard depth levels from the sea surface to 4,900 m depth. It can be employed to assess ocean climate change over the 1955-2017 time period and utilized in many climate studies, environmental research projects, and related applications.

Southwest North Atlantic

The SWNA climatology is based on temperature and salinity observations from the 2018 release of the World Ocean Database. Coverage includes 1955 to 2017, or roughly six decades, with annual, seasonal, and monthly time resolutions for each of the six decades.

Metadata

Temperature

Salinity

Citation

Seidov, Dan; Baranova, Olga K.; Boyer, Tim P.; Cross, Scott L.; Mishonov, Alexey V.; Parsons, Arthur R.; Reagan, James R.; Weathers, Katharine A. (2019). Southwest North Atlantic Regional Climatology (NCEI Accession 0201696). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/s3ag-2p18. Accessed [date].

Parameters

The Southwest North Atlantic Regional Climatology (SWNA RC) is based on the updated 2018 edition of the World Ocean Atlas (WOA18). The climatology is comprised of objectively analyzed temperature and salinity fields, and additional parameters which may be useful for applied climate studies and other applications:

  • Simple statistical means
  • Data distributions
  • Standard deviations
  • Standard errors of the mean
  • Observed minus analyzed
  • Seasonal minus annual distributions for both temperature and salinity

Analysis Methods

Seasonal and annual fields are based on complete monthly analyses of all three horizontal grids (1°x1°, a 1/4°x1/4°, and 1/10°x1/10°), which are computed by averaging six decadal monthly analyses from 1955 to 2012. Seasonal fields at all depths above 1500 meters are computed from the average of the three months comprising each season (e.g., January, February and March for winter), while annual mean fields are computed by averaging the four seasonal fields at all depths. The annual analysis of measurements below 1500 meters is the mean of the four seasonal analyses, and only shows annual and seasonal fields (the monthly fields are not shown).

Using High Resolution Fields

The high-resolution monthly temperature and salinity data coverage on the 1/10°x1/10° grid have more gaps than seasonal and annual fields computed from the monthly fields. In general, all high-resolution analyzed fields should be reviewed carefully before using them in critical mission applications, particularly high-resolution monthly fields. Users should review the data distribution and statistical mean arrays before deciding whether to use the high-resolution analyzed temperature and salinity fields or their climatological means. Moreover, the monthly maps of objectively analyzed data on 1/10°x1/10° may show too strong eddy-like irregularities in some regions due to interpolation and plotting combined. Although these cases are rare, it’s important to carefully review fields with such occurrences before using analyzed variables in research or applications.

Temperature and Salinity

Temperature and salinity climatologies are calculated separately, because there are significantly more temperature data than salinity data. Because of this disparity, there are not always concurrent temperature and salinity measurements.

As a result, instabilities in the vertical density field can occur when density is calculated from standard level climatologies of temperature and salinity. Appendices A and B in (Locarnini et al., 2013) describe a method employed to stabilize the water column anywhere in the world ocean by minimally altering climatological temperature and salinity profiles. All analyses shown in the NWA regional climatology have been performed using this stabilizing method.;

Area

Longitude
85.0°W—60.0°W
Latitude
10.0°N—35.0°N

Temporal Resolution

All data from the WOD18 for the SWNA domain were used to calculate six decadal climatologies within the following time periods: 1955-1964; 1965-1974; 1975-1984; 1985-1994; 1995-2004; 2005-2017. The averaged decadal climatology was calculated by averaging six individual decades listed above (see World Ocean Database 2018 Introduction). Each decadal climatology consists of:

Annual Fields
Computed as 12-months averages
Seasonal Fields
Winter (Jan.-Mar.), Spring (Apr.-Jun.), Summer (Jul.-Sep.), Fall (Oct.-Dec.) computed as 3-months averages
Monthly Fields
Grids above 1500 m

Spatial Resolution

Annual, Seasonal and Monthly Fields
1°x1°, 1/4°x1/4°, and 1/10°x1/10° latitude/longitude grids
Monthly Fields
Grids above 1500 m

Vertical Resolution

Annual and Seasonal Fields
0 to 5500 m depth on 102 standard levels
Monthly Fields
0 to 1500 m on 57 standard levels

Standard depth levels in the NWA regional climatology are the same as in the WOA13 (see Table 3 in the WOA13 documentation).

Objectives

Higher spatial resolutions – here the 1/10°x1/10° grid – provide major advantages in areas where they are feasible and supported by data availability. The quality control on a higher-resolution grid reveals more outliers than an analysis on coarser grids. More importantly, with the significantly shorter radius of influence in the objective analysis procedure, the structure of the gridded fields is far better sustained, especially in regions with sharp gradients of the essential oceanographic parameter (temperature and salinity). Residual effect of quasi-stationary meanders and transient mesoscale eddies on climatological fields is clearly seen at 1/10°x1/10° resolution. They are better preserved in high-resolution climatological fields, which make them more valuable for ocean modeling and other applications.

Units

Temperature
°C
Salinity
Unitless on the Practical Salinity Scale-1978.

Bathymetry

For all three grid resolutions, mean depth values at the center of a grid square with the respective resolution were extracted from the ETOPO2 World Ocean bathymetry.

Method

The mean climatological field calculation methods are described in the following publications: Temperature: Locarnini et al., 2018, Salinity: Zweng et al., 2018. Additional details on high-resolution climatological calculations can be found in Boyer et al., 2005. The updated table from (Boyer et al., 2005), including the 1/10° grid resolution, provides radii of influence for the analysis procedure as:

Pass 1° radius of influence 1/4° radius of influence 1/10° radius of influence
1 892 km 321 km 253 km
2 669 km 267 km 198 km
3 446 km 214 km 154 km

Most of the procedures used for generating NCEI regional climatologies are similar to those used for WOA18, e.g., (Locarnini et al., 2018; Zweng et al., 2018). Several recently published studies of long-term ocean climate change are based on SWNARC (Seidov et al., 2015; Seidov et al., 2017; Seidov et al., 2018).

Related Publications

  • Boyer, T., S. Levitus, H. Garcia, R. A. Locarnini, C. Stephens, J. Antonov, 2005: Objective analyses of annual, seasonal, and monthly temperature and salinity for the world ocean on a 0.25 degree grid. Int. J. Clim., 25, 931-945.
  • Boyer, T. P., O. K. Baranova, C. Coleman, H. E. . Garcia, A. Grodsky, R. A. Locarnini, A. V. Mishonov, C. R. Paver, J. R. Reagan, D. Seidov , I. V. Smolyar, K. Weathers, M. M. Zweng, 2018: World Ocean Database 2018. A. V. Mishonov, Technical Ed.; NOAA Atlas NESDIS 87, 209 pp.
  • Levitus, S., 1982: Climatological Atlas of the World Ocean, NOAA Professional Paper 13, U.S. Gov. Printing Office, Rockville, M.D., 190 pp.
  • Locarnini, R. A., A. V. Mishonov, O. K. Baranova, T. P. Boyer, M. M. Zweng, H. E. Garcia, J. R. Reagan, D. Seidov, K. Weathers, C. R. Paver, I. Smolyar, 2018: World Ocean Atlas 2018, Volume 1: Temperature. A. V. Mishonov Technical Ed.; NOAA Atlas NESDIS 81, 40 pp.
  • Seidov, D., O. K. Baranova, T. Boyer, S. L. Cross, A. V. Mishonov, and A. R. Parsons, 2016: Northwest Atlantic Regional Ocean Climatology, in NOAA Atlas NESDIS 80, edited, p. 56, 
  • NOAA/NESDIS, Washington, DC, i https://repository.library.noaa.gov/view/noaa/12209">doi:10.7289/V5/ATLAS-NESDIS-80; https://repository.library.noaa.gov/view/noaa/12209.
  • Seidov, D., A. Mishonov, J. Reagan, and R. Parsons, 2017: Multidecadal variability and climate shift in the North Atlantic Ocean, Geophys. Res. Let., 44(10), 4985-4993, doi:10.1002/2017GL073644.
  • Seidov, D., A. Mishonov, J. Reagan, O. Baranova, S. Cross, and R. Parsons, 2018: Regional climatology of the Northwest Atlantic Oceanhigh-resolution mapping of ocean structure and change, Bulletin of the American Meteorological Society, 9(10), doi:doi:10.1175/BAMS-D-17-0205.1.
  • Seidov, D., Mishonov, A., Reagan, J., Parsons, R., 2019: Eddy-Resolving In Situ Ocean Climatologies of Temperature and Salinity in the Northwest Atlantic Ocean. Journal of Geophysical Research: Oceans, 124, 41-58, doi:10.1029/2018JC014548
  • Zweng, M. M, J. R. Reagan, D. Seidov, T. P. Boyer, R. Locarnini, H. E. Garcia, A. V. Mishonov, O. K. Baranova, K. Weathers, C. R. Paver, I. Smolyar, 2018: World Ocean Atlas 2018, Volume 2: Salinity. A.Mishonov, technical editor, NOAA Atlas NESDIS 82, 39 pp.