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Maritimes Ecosystem Indicator Catalogue

9 Arctic Oscillation Index

Data Type: Tabular Data

Spatial Scope: Northern Hemisphere

Duration 1950-2025

Source: NOAA CPC, https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/

9.1 Introduction to Indicator

The Arctic Oscillation describes the variability in atmospheric pressure between the Arctic and surrounding mid-latitude regions of the Northern Hemisphere, and is linked to fluctuations in the strength of the polar vortex (Thompson and Wallace 1998). The trend of AO over time does not follow a particular periodicity.

Effects of strong AO anomalies are most pronounced in the Northern Hemisphere winter. Positive AO anomaly values represent lower-than-average pressure in Arctic regions and higher-than-average pressure in mid-latitudes, resulting in a stronger polar vortex and contained winter storm activity in the Arctic region. Negative AO values represent the opposite – higher-than-average pressures in the Arctic and lower-than-average pressures in the mid-latitudes. In negative phases, the jet stream is weaker and can meander, leading to anomalous cold events in mid-latitudes, particularly in Eastern North America and Eurasia (Li et al. 2017; He et al. 2017).

The AO is highly correlated with the North Atlantic Oscillation (NAO) and some discussion exists around whether the two are distinct (refs), but the AO index better reflects changes occurring at high arctic latitudes.

9.2 View Data 

library(plotly)
plotly_df <- data@data %>%
  mutate(date = lubridate::make_date(year, month, day = 1),
         smooth_1yr = zoo::rollapply(anomaly_value, mean, width = 12, partial = TRUE),
         smooth_10yr = zoo::rollapply(anomaly_value, mean, width = 120, partial = TRUE),
         overall_mean = mean(anomaly_value))

p <- plot_ly(plotly_df, x = ~date) %>%
  add_lines(y = ~anomaly_value,
            name = "Monthly Anomaly",
            line = list(color = "lightgrey"),
            hovertemplate = "Anomaly Value: %{y:.2f} <extra></extra>"
  ) %>%
  add_lines(y = ~smooth_1yr,
            name = "1-yr Smooth",
            line = list(color = "blue", width = 2),
            hovertemplate = "1-yr Smooth: %{y:.2f} <extra></extra>"
  ) %>%
  add_lines(y = ~smooth_10yr,
            name = "10-yr Smooth",
            line = list(color = "red", width = 2),
            hovertemplate = "10-yr Smooth: %{y:.2f} <extra></extra>") %>%
  add_lines(y = ~overall_mean,
            name = "Overall Mean",
            line = list(color = "black", width = 2, dash = "dash"),
            hovertemplate = "Timeseries Mean: %{y:.2f} <extra></extra>") %>%
  layout(
    title = "Arctic Oscillation Index for Northern Hemisphere",
    xaxis = list(title = "Date",
                 hoverformat = "%b %Y" ),
    yaxis = list(title = "AO Index",
                 fixedrange = T),
    hovermode = "x unified",
    margin = list(t = 80)
    
  ) %>%
  config(displayModeBar = FALSE)

p

Figure 9.1: AO Index Value; 1950-2025

9.4 Relevance to Research and Stock Assessments

Direct examples of AO’s effect on fisheries are less common compared to other atmospheric variables, but the index has potential effects to stocks through its association with sea ice coverage and freshwater input in the Arctic and North Atlantic oceans (Greene et al. 2013).

In Canada, some fisheries responses to AO have been identified. Positive springtime AO values have been associated with decreased recruitment and of juvenile movement arctic cod in the Beaufort Sea, and positive AO years result in increased transport of fish towards eastern waters (Herbig et al. 2023). AO has also shown an important predictor of exploitable snow crab biomass, with effects that vary across regions and timescales (Mullowney et al. 2023).

9.5 Variable Definitions

Table 9.2: Column names and definitions in the AO dataset.
variable description unit
year Year of Model-projected value
month Month of Model-projected value
anomaly_value Standardized index for AO anomalies

9.6 Additional Data

No additional data for AO.

9.7 Get the Data 

library(marea)
data('ao')
plot(ao)

References

Greene, Charles H, Erin Meyer-Gutbrod, Bruce C Monger, Louise P McGarry, Andrew J Pershing, Igor M Belkin, Paula S Fratantoni, et al. 2013. “Remote Climate Forcing of Decadal-Scale Regime Shifts in Northwest Atlantic Shelf Ecosystems.” Limnology and Oceanography 58 (3): 803–16.
He, Shengping, Yongqi Gao, Fei Li, Huijun Wang, and Yanchun He. 2017. “Impact of Arctic Oscillation on the East Asian Climate: A Review.” Earth-Science Reviews 164: 48–62.
Herbig, Jennifer, Jonathan Fisher, Caroline Bouchard, Andrea Niemi, Mathieu LeBlanc, Andrew Majewski, Stephane Gauthier, and Maxime Geoffroy. 2023. “Climate and Juvenile Recruitment as Drivers of Arctic Cod (Boreogadus Saida) Dynamics in Two Canadian Arctic Seas.” Elem Sci Anth 11 (1): 00033.
Li, Zhenhua, Alan H Manson, Yanping Li, and Chris Meek. 2017. “Circulation Characteristics of Persistent Cold Spells in Central–Eastern North America.” Journal of Meteorological Research 31 (1): 250–60.
Mullowney, Darrell RJ, Krista D Baker, Cody S Szuwalski, Stephanie A Boudreau, Frédéric Cyr, and Brooks A Kaiser. 2023. “Sub-Arctic No More: Short-and Long-Term Global-Scale Prospects for Snow Crab (Chionoecetes Opilio) Under Global Warming.” PLOS Climate 2 (10): e0000294.
Thompson, David WJ, and John M Wallace. 1998. “The Arctic Oscillation Signature in the Wintertime Geopotential Height and Temperature Fields.” Geophysical Research Letters 25 (9): 1297–1300.