Observed Feedback Between Winter Sea Ice and the North Atlantic Oscillation Nathan Workman Atmospheric Sciences By Courtenay Strong, Hal Sturn And Gudrun Magnusdottir Nathan Workman Atmospheric Sciences

 The North Atlantic Oscillation is a climatic phenomenon in the North Atlantic Ocean of fluctuations in the difference of atmospheric pressure at sea level between the Icelandic low and the Azores high.  Discovered in the 1920s by Sir Gilbert Walker  NAO is one of the largest causes of climate fluctuations in North America and the surrounding climates.  Closely related to the Arctic Oscillation  The Icelandic Low and the Azores high pressure systems control the magnitude and strength of the Westerlies in Europe  These winds have a great impact on the weather in Europe, which is why understanding the NAO is very Important. What Is The North Atlantic Oscillation? (NAO)

NAO Continued  Large impact on Sea Surface Temps in the North Atlantic  Impact of the amount of sea ice in the North Atlantic  The NAO accounts for over 31 % percent of the variance in SST in the winter  Not as dominant in the summer months

Difference in SST Positive NAONegative NAO

 National Snow and Ice Data Center sea ice concentrations were used.  These were derived from Nimbus-7 imager radiances.  Sea level pressure and wind velocity data also used.  The ice data was measured every two days from and once daily from  However, the study focuses on processes occurring at weekly time scales during the winter months.  The time frame used for this study was from December 4 th to April 23 rd. Data Collection Tools

Why Sea Ice?  Sea Ice is a very important component of the climate system  Affects the atmosphere through surface Albedo and exchange of heat, moisture and momentum between the atmosphere and the ocean  Also has an influence on the upper ocean stratification and is important for deep water formation

 The biggest issue that the researchers were trying to solve is whether negative feedback from the sea ice to NAO could be detected in observations, and if so the amount found.  Tested for feedback and its effects on the NAO index and sea ice concentrations  Study was done in the winter months, which is when NAO and sea ice concentrations are at a maximum. Why the study was done..

 EOF (Empirical Orthogonal Function) analysis is used  NAO index (N) – Sea Level Pressure  Greenland Sea Ice Dipole (G)- Sea Ice Variability Pattern (Found by researchers in 2000) Indices', Formulas and Terms used Fig. 1. (a) The EOF associated with the NAO index N contoured at 0.01 with negative values dashed and the zero contour suppressed. The arrows show the correlation between surface wind velocity and the NAO index when each is averaged over the 21-week extended winter.

Linear Scholastic Model  The VAR has two equations, one for the value of G at week t, denoted G t, and one for the value of N at week t denoted N  The system cannot be estimated directly unless one of the ϕ terms is restricted to zero  The VAR provides a means for exploring the relationship between N and G and invoking the testable definitions of causality and feedback Log Likelihood Model Used two different types of models Restricted and Unrestricted The relative strength of models is assessed using a log-likelihood ratio test of the model residuals at the 95% confidence level

 Reflects the ability of NAO-driven circulations to generate sea ice advection anomalies on the time scale of days to a week  Over several weeks, if N leads G, during the first week, the correlation strengthens between the two and it remains positive  Proves that thermodynamics are essential to connection between sea ice and the NAO When N Leads G Examples of the indices N (bold with circles) and G (thin lines). The weekly values in the gray shaded regions are used only when calculating lagged correlations for the data in the unshaded, 21-week windows

When G leads N  Correlations drop rapidly towards zero and then become increasingly negative after 3 weeks  Shows observational evidence of negative feedback from sea ice to NAO  However, when averaged over 21 weeks the correlation is positive.

 Spatial patterns of the EOFs associated with N and G suggest relationship between the two.  Used the Granger study to quantify correlation between the two Results Composite time series in the temporal vicinity of local extrema of G or N as indicated in the title of each panel; N is bold with filled circles, G is a thin curve, and shading shows the interquartile range of the time series it bounds.

 The composite results indicate that locally extreme values of N tend to be followed by like-signed locally extreme values of G  Presence of negative feedback between N and G dampens the variability of sea ice concentrations over the North Atlantic.  N and G are more sensitive to the initial value of G than to an initial value of N  G like sea anomalies decay after a few weeks, which limit the time frame that the anomalies generate large scale, negative NAO like anomalies. Findings

 Analysis of coupled model output further indicates that NAO circulation anomalies induce sea ice melting or freezing anomalies in the Labrador and Barents Seas via wind- driven oceanic heat transport  N and G are correlated on a variety of time scales and lags  Multi-month sustained sea ice anomaly patterns may be of increasing relevance over the next century  Study has provided an observational perspective for interpreting boundary forcing experiments in which the atmosphere is exposed to sustained sea ice anomalies Findings Continued..

 The NAO plays a large contributing factor on sea ice.  In positive NAO years, there is anomalously large sea ice concentrations over the Labrador Sea  In these positive years, there are anomalously low concentrations over the Barents Sea.  Opposite occurs in years of negative NAO How does the NAO affect Sea Ice?

 The research in understanding the NAO and Sea Ice is something that is continually ongoing.  Strong and Magnusdottir released another study in 2010 showing a large scale multi century perspective of sea ice and NAO.  Further experimentation with coupled climate models will be useful for investigating the interaction between NAO and winter sea ice as each evolves under projected climate change. Direction of Research Courtenay Strong Gudrun Magnusdottir

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