The winter (December thru March) station-based index of the NAO is based on the difference of normalized sea level pressure (SLP) between Lisbon, Portugal and Stykkisholmur/Reykjavik, Iceland since 1864. Positive values of the NAO index are typically associated with stronger-than-average westerlies over the middle latitudes, more intense weather systems over the North Atlantic and wetter/milder weather over western Europe. Monthly, seasonal and annual indices using slightly different data sources for the southern station are also available.
Since there is no unique way to define the spatial structure of the NAO, it follows that there is no universally accepted index to describe the temporal evolution of the phenomenon. Most modern NAO indices are derived either from the simple difference in surface pressure anomalies between various northern and southern locations, or from the PC time series of the leading (usually regional) EOF of sea level pressure (SLP). Many examples of the former exist, usually based on instrumental records from individual stations near the NAO centers of action, but sometimes from gridded SLP analyses. A major advantage of most of these indices is their extension back to the mid-19th century or earlier.
A disadvantage of station-based indices is that they are fixed in space. Given the movement of the NAO centers of action through the annual cycle, such indices can only adequately capture NAO variability for parts of the year. Moreover, individual station pressures are significantly affected by small-scale and transient meteorological phenomena not related to the NAO and, thus, contain noise.
An advantage of the PC time series approach is that such indices are more optimal representations of the full NAO spatial pattern; yet, as they are based on gridded SLP data, they can only be computed for parts of the 20th century, depending on the data source.
For a more detailed discussion of issues related to the NAO indices and related indices such as the Northern Annular Mode (NAM) and Arctic Oscillation (AO), see Hurrell and Deser (2009) and Hurrell et. al (2003), linked in Key Publications 2 and 3 below.
- James Hurrell, NCAR
The station-based NAO indices produced by NCAR's Climate Analysis Section are based on Hurrell (1995). They are currently offered as ascii text files for winter, monthly, seasonal, and annual values.
Station-based NAO index calculation procedures
Monthly Index:
Observational data is subject to corrections after it has been published and used in our indices. Once noted, these corrections are applied to our input data, and the corresponding climate indices may change. It is thus recommended that one downloads an entire climate index each time they wish to update their holdings.
Questions about these datasets? Contact Adam Phillips (asphilli (AT) ucar.edu) and/or Jim Hurrell (jhurrell (AT) ucar.edu).
Winter index of the NAO based on the difference of normalized sea level pressures (SLP) between Lisbon, Portugal and Stykkisholmur/Reykjavik, Iceland since 1864. (Missing Value = -999.) Note: The station index value for year N refers to an average of December year N-1 and January, February, and March year N. (Example: The 1899 value contains the average of December 1898 and January, February, and March 1899.)
The SLP values at each station were normalized by removing the long-term mean and by dividing by the long-term standard deviation. Both the long-term means and standard deviations are based on the period 1864-1983. Normalization is used to avoid the series being dominated by the greater variability of the northern station.
The values in the files above differ slightly from those in Hurrell (1995) because of continual updates to the data and a change in the base period. The SLP anomalies at each station were normalized relative to the 120-year period 1864--1983. Hurrell (1995) normalized relative to 1864--1994.
Note: The 1997 value was changed from -0.20 to -0.17 after it was discovered that the World Monthly Surface Station Climatology December 1996 SLP value for Reykjavik had changed. It was initially reported to be 1014.0, and had since been corrected to 1013.3hPa.
Monthly, Seasonal, and Annual indices of the NAO are based on the difference of normalized sea level pressures (SLP) between Ponta Delgada, Azores and Stykkisholmur/Reykjavik, Iceland since 1865. (Missing Value = -999.). Only 2 months of data are required for a 3-month seasonal average to be computed.
The SLP values at each station were normalized by removing the long-term mean and by dividing by the long-term standard deviation. Both the long-term means and standard deviations are based on the period 1864-1983. Normalization is used to avoid the series being dominated by the greater variability of the northern station.
From June 2003 through February 2010, the Ponta Delgada station reports were intermittent, with a large gap in reports from June 2003 through May 2008. To allow this timeseries to be updated, we use the nearest NCEP/NCAR Reanalysis grid point as a substitute. The calculated timeseries use Ponta Delgada observational data from Jan. 1865 - May 2003, June 2008- Jan 2010, and Mar 2010-Mar 2013, and NCEP/NCAR Reanalysis point data from June 2003-May 2008 and for Feb 2010. The correlations between timeseries constructed with the Ponta Delgada observational data and those constructed with NCEP/NCAR Reanalysis data are ~ 0.99 (1948-2003). We also used NCEP/NCAR Reanalysis point data to fill in July 2012 in the Reykjavik SLP record.
Annual North Atlantic Oscillation Index (Station-Based) [1.82 KB file] NAO Index Data provided by the Climate Analysis Section, NCAR, Boulder, USA, Hurrell (2003). Updated regularly. Accessed DD Month YYYY [list date you accessed the data].
DJFM North Atlantic Oscillation Index (Station-Based) [1.84 KB file] NAO Index Data provided by the Climate Analysis Section, NCAR, Boulder, USA, Hurrell (2003). Updated regularly. Accessed DD Month YYYY [list date you accessed the data]
Monthly North Atlantic Oscillation Index (Station-Based) [11.62 KB file] NAO Index Data provided by the Climate Analysis Section, NCAR, Boulder, USA, Hurrell (2003). Updated regularly. Accessed DD Month YYYY [list date you accessed the data].
Seasonal North Atlantic Oscillation Index (Station-Based) [11.62 KB file] NAO Index Data provided by the Climate Analysis Section, NCAR, Boulder, USA, Hurrell (2003). Updated regularly. Accessed DD Month YYYY [list date you accessed the data].
Click the thumbnails to view larger sizes
Thumbnails |
Captions |
|---|---|
 |
Winter (December through March) index of the NAO based on the difference of normalized sea level pressure (SLP) between Lisbon, Portugal and Stykkisholmur/Reykjavik, Iceland since 1864. The SLP values at each station were normalized by removing the long-term mean and by dividing by the long-term standard deviation. Both the long-term means and standard deviations are based on the period 1864-1983. Normalization is used to avoid the series being dominated by the greater variability of the northern station. (Climate Data Guide; A. Phillips) |
 |
The station based NAO index may not be an optimal representation of the associated spatial pattern. The principal component (PC) time series of the leading EOF of seasonal (December through March) SLP anomalies over the Atlantic sector (20-80N, 90W-40E) serves as an alternative index (Hurrell 1995). The PC based NAO is in color; the station based index is the black line. The correlation is 0.93 over 1899-2017. The black dots on the EOF panel show the location of the stations used for the station-based NAO index. (Climate Data Guide; A. Phillips) |
Hurrell, James & National Center for Atmospheric Research Staff (Eds). Last modified 07 Nov 2017. "The Climate Data Guide: Hurrell North Atlantic Oscillation (NAO) Index (station-based)." Retrieved from https://climatedataguide.ucar.edu/climate-data/hurrell-north-atlantic-oscillation-nao-index-station-based.
Funding: NSF | National Science Foundation
Based at: NCAR | National Center for Atmospheric Research
A Project of: Climate Analysis Section in Climate and Global Dynamics Laboratory
Created by: Climate Data Guide PIs and Staff
