Frequently used climate patterns, also called climate indices, are briefly described in this section. The internal dynamics of the ocean and atmosphere is an important factor that determines the Earth's climate. Interactions between the various elements of the system influence its variability in addition to external forcing mechanisms. This variability can be investigated and represented using mathematical methods, resulting in typical patterns. The resulting time series are referred to as climate indices. A comprehensive list of climate indices can be found at NAAO: https://www.esrl.noaa.gov/psd/data/climateindices/list/
The following important climate patterns are presented as an example:
The NAO is an atmospheric pressure pattern with strongest impact at the region of the North Atlantic that was originally defined as the difference between normalized anomalies in sea level air pressure between meteorological stations in the Azores and Iceland. For example, a high NAO index is associated with above-average strong west winds in the middle latitudes of the North Atlantic. The level of the NAO index also influences the storm tracks, the rainfall patterns in Europe and the heat and moisture transport from the North Atlantic to the surrounding land.
There are now various mathematical methods to study the NAO. It is common today to calculate the NAO index using a so-called rotated principal component analysis. This method finds the primary teleconnection patterns and from this the monthly time series of the patterns can be created and the NAO index can be derived. See also the references for more information on the calculation and impact of the NAO.
The data is available in daily and monthly resolution for the period from 1950 to the present day and is provided, for example, by the NOAA https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml
- The North Atlantic Oscillation: Climatic Significance and Environmental Impact, Volume 134, Editors: James W. Hurrell et al. (2003), American Geophysical Union, DOI:10.1029/GM134
NAO at NOAA: https://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtml
A connection could be established between the phenomena of Southern Oscillation (SO), which is related to the atmosphere, and the El Niño / La Niña phenomena resulting from changes in ocean currents. The corresponding pattern has since been referred to as El Niño - Southern Oscillation (ENSO).
The SOI is calculated using the pressure differences between Tahiti and Darwin. A negative phase of the SOI is characterised by below-normal atmospheric pressure at Tahiti and above-normal atmospheric pressure at Darwin. Long periods of negative SOI are associated with warmer than normal ocean waters across the eastern tropical Pacific (El Niño). The opposite is true for long periods of positive SOI (La Niña). Low atmospheric pressure tends to occur over warm water and high pressure occurs over cold water. El Niño episodes are defined as sustained warming of the central and eastern tropical Pacific Ocean. This results in a decrease in the strength of the Pacific trade wind, and a reduction in rainfall over eastern and northern Australia. Two of the strongest El Niño episodes of the century occurred on 1982/83 and 1997/98.
NINO3 is one of several climate indicators for El Niño - Southern Oscillation derived from sea surface temperature anomalies in the eastern tropical Pacific (5N-5S, 150W-90W). A long-term mean is usually subtracted from the NINO3 index, whereby an El Niño or La Niña event can be identified. In the specific example from Trenberth (1997), it was considered an event if the 5-month average of the index was exceeded by 0.4 ° C for at least 6 consecutive months.
An NINO3 index with monthly resolution covering the period from 1950 to the present day is provided by NOAA http://www.esrl.noaa.gov/psd/data/correlation/nina3.data
The SOI with monthly resolution covering the period from 1951 to the present day is provided by NOAA https://www.cpc.ncep.noaa.gov/data/indices/soi
Trenberth, K. E., 1997. The Definition of El Niño. Bull. Amer. Met. Soc., 78, 2771-2777.
Zhang, Y., J.M. Wallace and D.S. Battisti 1997: ENSO-like Interdecadal Variability: 1900-93. Journal of Climate, Vol. 10, 1004-1020.
Gershunov, A. and T. P. Barnett. Interdecadal modulation of ENSO teleconnections. Bull. Amer. Meteor. Soc., 79: 2715-2725.
ENSO at NOAA https://www.climate.gov/enso
The Pacific Decadal Oscillation (PDO) is similar to the El-Niño pattern, but is long-living and describes most of the climate variability of the Pacific. There appear to be two modes with different spatial and temporal characteristics of the surface temperature of the North Pacific. PDO affects the southern Hemisphere and effects on surface climate anomalies over the central South Pacific, Australia and South America have been observed. Inter-decadal changes in the Pacific climate have far-reaching effects on natural systems, including water resources in America and many marine fisheries in the North Pacific. The mechanisms that cause the variability of PDO are still unclear.
Pacific Decadal Oscillation is defined as the leading PC of monthly SST anomalies in the North Pacific Ocean. The extreme phases of the PDO are classified as warm or cool, derived as the leading principal component of monthly sea surface temperature anomalies in the North Pacific Ocean poleward of 20°N (Zhang et. al. 1997). Several independent studies have shown only two complete PDO cycles in the past century: "cool" PDO regimes prevailed from 1890 to 1924 and again from 1947 to 1976, while "warm" PDO regimes dominated from 1925 to 1946 and from 1977 to the mid-1990' (Mantua et al. 2002). The main difference of PDO to ENSO is that PDO is acting on longer time scales (20-30 years) and affecting mainly the North Pacific sector.
The data can be found on monthly resolution covering the period from 1948 to 2012, provided by NOAA https://www.esrl.noaa.gov/psd/data/correlation/pdo.data
- Bond, N.A. and D.E. Harrison (2000): The Pacific Decadal Oscillation, air-sea interaction and central north Pacific winter atmospheric regimes. Geophys. Res. Lett., 27(5), 731-734.
Zhang, Y., J.M. Wallace, D.S. Battisti, 1997: ENSO-like interdecadal variability: 1900-93. J. Climate, 10, 1004-1020.
Mantua, N.J. and S.R. Hare, Y. Zhang, J.M. Wallace, and R.C. Francis,1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bulletin of the American Meteorological Society, 78, pp. 1069-1079.
Mantua, N.J. & Hare, S.R. : The Pacific Decadal Oscillation. Journal of Oceanography (2002) 58: 35. doi.org/10.1023/A:1015820616384
The IOD is defined as the SST anomaly difference between the western equatorial Indian Ocean (50E-70E, 10S-10N) and the south eastern equatorial Indian Ocean (90E-110E, 10S-0N), referred to as Dipole Mode Index (DMI). IOD is a coupled ocean-atmosphere phenomenon. Positive IOD values are characterised by cooler than normal water in the tropical eastern Indian Ocean and warmer than normal water in the tropical western Indian Ocean, while positive IOD is also associated with a decrease in rainfall over parts of central and southern Australia. The opposite is true for negative IOD periods.
The data can be found on monthly resolution covering the period from 1958 to present, provided by JAMSTEC http://www.jamstec.go.jp/aplinfo/sintexf/e/iod/about_iod.html
- Saji N.H., Goswami B.N., Vinayachandran P.N., Yamagata T., 1999: A dipole mode in the tropical Indian Ocean, Nature,401, 360-363
The Southern Annular Mode (SAM) is defined as the normalised difference mean sea-level pressure between 40°S and 65°S. A high SAM index is associated with stronger westerlies in a broad band around 55°S and anomalously dry conditions over southern South America, New Zealand and Tasmania and wet conditions over much of Australia and South Africa. Over the ocean, the stronger westerly winds tend to generate stronger eastward currents which diverge at the ocean surface due to enhanced wind-driven Ekman transport leading to stronger upwelling in ˜60°S. The departures of SAM from its annular pattern enhance meridional exchanges and thus large heat transport.
The data can be found on monthly resolution covering the period from 1957 to present, provided by LASG http://www.nerc-bas.ac.uk/public/icd/gjma/newsam.1957.2007.txt
And a variant is here: https://legacy.bas.ac.uk/met/gjma/sam.html
- Marshall, G.J., 2003: Trends in the Southern Annular Mode from Observations and Reanalyses.J. Climate,16, 4134–4143, https://doi.org/10.1175/1520-0442(2003)016<4134:TITSAM>2.0.CO;2