Antarctic Wind Field anomalies and polar lows

Antarctica, the fifth continent on the planet, is a vast region near the South Pole that plays a role like a beating heart in the rhythm of Earth's life by controlling thermal balance and developing the ocean-atmospheric systems. This continent has singular importance in various scientific, political, and economic aspects, which has attracted the attention of different countries. The extreme atmospheric and oceanic phenomena of this area have an effect on the earth's climate. One of the significant extreme phenomena is mesoscale cyclones. These cyclones convert to polar lows in the special conditions that make modeling and forecasting conditions more difficult. In this research, wind field anomalies are evaluated using satellite scatterometery and reanalysis data in the period from 2000-2020. Different parts of Antarctica have been investigated for the formation of mesoscale cyclones and then presented with polar lows in the study area. 

The Antarctic region has a vital role in controlling the temperature and the climate of our planet. Due to the geographical conditions of Antarctica, various cyclones are formed in this region, and they not only have an effect on the region's climate but also play a determinant role in the earth’s climate. Meso-scale cyclones that have a diameter of less than 2000 km and surface winds stronger than 14 m/s as a result of the main fronts at the poles are classified as polar lows. To investigate this issue, the surface wind data of the National Center for Atmospheric Research (NCEP/NCAR) used a 0.25 degree mesh grid. Then, an anomaly of surface wind is extracted using the Empirical Orthogonal Functions. In the following, different identified polar lows were investigated using the surface wind of satellite scattometry, the temperature of the surface of 500 hp and the polar low life stability obtained from the ERA5 post-processing data set. The cyclone tracking algorithm was used to check all the characteristics of meso-scale cyclones.

Analyzing the anomaly using empirical orthogonal functions shows that the first component represents about 51% of the total surface wind variance. This component has a stronger anomaly pattern in winter seasons than in summer, and this component indicates the dominant wind pattern of the region, and extreme variance is observed in the west of Antarctica. Also, this component shows that in the dry part of the region, the wind anomaly is higher than in the water part, this can happen because of the structure of the Antarctic basin. In the blue part of the study area, on the Amundsen Sea, which is located along the South Pacific Ocean in the west of Antarctica, the wind anomaly is estimated to be higher than other blue areas of Antarctica. This pattern can be caused by hot and cold water currents in the region, which needs serious study and investigation. The second component of the surface wind anomaly accounts for about 20% of the total variance. It shows the highest anomaly in the Weddell Sea. In this region, the Weddell Gyre is dominant and can be caused by the atmosphere-ocean interaction and the atmospheric systems ruling over the region. The third and fourth anomaly components each show about 10% of the total variance. The third component is the most anomaly in Ross Sea and Ross Ice Shelf and the fourth component shows the most changes in Weddelle Sea in addition to Ross Sea and Ross Ice Shelf. Accordingly, Ross Gyre and Weddell Gyre play a significant role in determining the Antarctic wind pattern. According to the criteria provided for identifying mesoscale gyres, polar low pressures can be identified and investigated using satellite spectrometric data and reanalysis.

Extreme weather in high latitudes and near the north and south poles of the earth causes air-sea interaction to happen. The strong winds of these regions generate rogue waves in the oceans. Among these phenomena, there are a series of meso-scale phenomena such as polar lows, with limited information. Therefore, such phenomena are not considered in global models and post-processed data. Consequently, it is necessary to modify the global dynamic ocean-atmospheric models in the Southern Ocean by considering different polar lows.