Near-inertial oscillations are an important feature of the climate system. The output of a high-resolution ocean model of the North Atlantic was used to investigate interannual variability of wind power input (WPI) to near-inertial currents with respect to the North Atlantic Oscillation (NAO). The model is forced with NCEP/NCAR reanalysis wind stress for JFM of the years 1989 (strong positive NAO-phase) and 2010 (negative NAO).
Atmospheric parameters are tightly related to the NAO. The storm track in 1989 is intensified and channels storms into the subpolar North Atlantic, while it is more fanned out in 2010, allowing single storms to travel into the Mediterranean Sea.
Similar patterns emerge from the distribution of near-inertial wind stress magnitude (NIWSM), i.e. the part of the wind stress spectrum that is most efficient in generating near-inertial energy (NIE). Seasonally averaged NIWSM, however, is not anchored to the storm track but is shifted to the south. This behaviour is due to the latitude-dependent inertial frequency, which decouples synoptic variability from the
near-inertial frequency band.
WPI for the two considered years is consistent with the different distributions of storms: While 1989 produced a total rate of WPI of 6.48 x 109 W (= GW) and a secondary centre of weakly increased WPI in the eastern subpolar North Atlantic corresponding to the intensified storm track in this region, total WPI in 2010 amounted to 9.64 GW and was associated with a strongly enhanced secondary centre of WPI in the subtropics. Although anomalies both in the storm track and mean NIWSM are more pronounced in the subpolar ocean basin, WPI prefers the
subtropics. It is proposed that a mixture of atmospheric and oceanic processes is responsible for this asymmetry, chief among them the variation of the Coriolis frequency with latitude.
Patterns of WPI, mixed layer NIE, and NIE in the deep ocean are similar to each other. NIE decreases drastically with depth.
Mean NIWSM is a promising atmospheric proxy to WPI. Linear statistical models of WPI built from this quantity allow the estimation of total WPI for each winter (JFM) from 1980 to 2013 in low, mid-, and high-latitudes. Total WPI as well as mid-latitude WPI is only weakly correlated with the NAO. Low- and high-latitude
WPI on the other hand is strongly correlated with the NAO, with the magnitude of correlation coefficients exceeding values of 0.8, suggesting that the relationship of WPI to the NAO lies in shifting the patterns of WPI. During negative NAO phases, WPI is pulled towards the subtropics (and thus intensified), whereas it shifts towards the polar ocean during positive NAO phases, both in accordance with changes in the configuration of the storm track tail. Since the response of WPI to comparable mean NIWSM is weakening with latitude, total WPI is more strongly influenced by lowlatitude WPI. It is concluded that the relationship between WPI in the North Atlantic
and the NAO is of a twofold nature: While total WPI is only weakly and inversely related to the NAO, the distribution of WPI is strongly depending on it.
Course of study: MSc Climate Physics