Interannual variability of high potential vorticity in South Atlantic

2011 ◽  
Vol 12 (4) ◽  
pp. 368-374 ◽  
Author(s):  
T. F. Barbosa ◽  
V. B. Rao ◽  
I. F. A. Cavalcanti
Keyword(s):  
Interannual Variability ◽  
Potential Vorticity ◽  
South Atlantic ◽  
High Potential ◽  
High Potential Vorticity

An air mass with high potential vorticity preceding the formation of the Marcus Convergence Zone

2005 ◽  
Vol 32 (17) ◽  
Author(s):  
N. Sato ◽  
K. Sakamoto ◽  
M. Takahashi
Keyword(s):  
Potential Vorticity ◽  
High Potential ◽  
Convergence Zone ◽  
Air Mass ◽  
High Potential Vorticity

scholarly journals The South Atlantic–South Indian Ocean Pattern: a Zonally Oriented Teleconnection along the Southern Hemisphere Westerly Jet in Austral Summer

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 259 ◽  
Author(s):  
Zhongda Lin
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Southern Hemisphere ◽  
Austral Summer ◽  
South Atlantic ◽  
The South ◽  
South Indian Ocean ◽  
Westerly Jet ◽  
South Indian ◽  
Zonal Wavenumber

Extratropical teleconnections significantly affect the climate in subtropical and mid-latitude regions. Understanding the variability of atmospheric teleconnection in the Southern Hemisphere, however, is still limited in contrast with the well-documented counterpart in the Northern Hemisphere. This study investigates the interannual variability of mid-latitude circulation in the Southern Hemisphere in austral summer based on the ERA-Interim reanalysis dataset during 1980–2016. A stationary mid-latitude teleconnection is revealed along the strong Southern Hemisphere westerly jet over the South Atlantic and South Indian Ocean (SAIO). The zonally oriented SAIO pattern represents the first EOF mode of interannual variability of meridional winds at 200 hPa over the region, with a vertical barotropic structure and a zonal wavenumber of 4. It significantly modulates interannual climate variations in the subtropical Southern Hemisphere in austral summer, especially the opposite change in rainfall and surface air temperature between Northwest and Southeast Australia. The SAIO pattern can be efficiently triggered by divergences over mid-latitude South America and the southwest South Atlantic, near the entrance of the westerly jet, which is probably related to the zonal shift of the South Atlantic Convergence Zone. The triggered wave train is then trapped within the Southern Hemisphere westerly jet waveguide and propagates eastward until it diverts northeastward towards Australia at the jet exit, in addition to portion of which curving equatorward at approximately 50° E towards the southwest Indian Ocean.

scholarly journals A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1359 ◽  
Author(s):  
Scott Curtis ◽  
Thomas Crawford ◽  
Munshi Rahman ◽  
Bimal Paul ◽  
M. Miah ◽  
...  
Keyword(s):  
Interannual Variability ◽  
River Basin ◽  
Significant Relationship ◽  
Large Scale ◽  
Monsoon Rainfall ◽  
Southern Oscillation ◽  
Wave Train ◽  
Principal Component ◽  
South Atlantic ◽  
The Ganges

Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

scholarly journals South Atlantic Variability Arising from Air–Sea Coupling: Local Mechanisms and Tropical–Subtropical Interactions

2007 ◽  
Vol 20 (14) ◽  
pp. 3345-3365 ◽  
Author(s):  
Sylwia Trzaska ◽  
Andrew W. Robertson ◽  
John D. Farrara ◽  
Carlos R. Mechoso
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Wave Train ◽  
Circulation Model ◽  
South Atlantic ◽  
Ocean Dynamics ◽  
Shortwave Radiation ◽  
Tropical Atlantic ◽  
Shallow Clouds ◽  
The Tropics

Abstract Interannual variability in the southern and equatorial Atlantic is investigated using an atmospheric general circulation model (AGCM) coupled to a slab ocean model (SOM) in the Atlantic in order to isolate features of air–sea interactions particular to this basin. Simulated covariability between sea surface temperatures (SSTs) and atmosphere is very similar to the observed non-ENSO-related covariations in both spatial structures and time scales. The leading simulated empirical coupled mode resembles the zonal mode in the tropical Atlantic, despite the lack of ocean dynamics, and is associated with baroclinic atmospheric anomalies in the Tropics and a Rossby wave train extending to the extratropics, suggesting an atmospheric response to tropical SST forcing. The second non-ENSO mode is the subtropical dipole in the SST with a mainly equivalent barotropic atmospheric anomaly centered on the subtropical high and associated with a midlatitude wave train, consistent with atmospheric forcing of the subtropical SST. The power spectrum of the tropical mode in both simulation and observation is red with two major interannual peaks near 5 and 2 yr. The quasi-biennial component exhibits a progression between the subtropics and the Tropics. It is phase locked to the seasonal cycle and owes its existence to the imbalances between SST–evaporation and SST–shortwave radiation feedbacks. These feedbacks are found to be reversed between the western and eastern South Atlantic, associated with the dominant role of deep convection in the west and that of shallow clouds in the east. A correct representation of tropical–extratropical interactions and of deep and shallow clouds may thus be crucial to the simulation of realistic interannual variability in the southern and tropical Atlantic.

scholarly journals The South Atlantic Subtropical High: Climatology and Interannual Variability

2017 ◽  
Vol 30 (9) ◽  
pp. 3279-3296 ◽  
Author(s):  
Xiaoming Sun ◽  
Kerry H. Cook ◽  
Edward K. Vizy
Keyword(s):  
Interannual Variability ◽  
Annual Cycle ◽  
Large Scale ◽  
Austral Summer ◽  
Southern Annular Mode ◽  
South Atlantic ◽  
Subtropical High ◽  
Interannual Variations ◽  
The South ◽  
The North

ERA-Interim and JRA-55 reanalysis products are analyzed to document the annual cycle of the South Atlantic subtropical high (SASH) and examine how its interannual variability relates to regional and large-scale climate variability. The annual cycle of the SASH is found to have two peaks in both intensity and size. The SASH is strongest and largest during the solstitial months when its center is either closest to the equator and on the western side of the South Atlantic basin during austral winter or farthest poleward and in the center of the basin in late austral summer. Although interannual variations in the SASH’s position are larger in the zonal direction, the intensity of the high decreases when it is positioned to the north. This relationship is statistically significant in every month. Seasonal composites and EOF analysis indicate that meridional changes in the position of the SASH dominate interannual variations in austral summer. In particular, the anticyclone tends to be displaced poleward in La Niña years when the southern annular mode (SAM) is in its positive phase and vice versa. Wave activity flux vectors suggest that ENSO-related convective anomalies located in the central-eastern tropical Pacific act as a remote forcing for the meridional variability of the summertime SASH. In southern winter, multiple processes operate in concert to induce interannual variability, and none of them appears to dominate like ENSO does during the summer.

scholarly journals An Intrinsic Mode of Interannual Variability in the Indian Ocean

2017 ◽  
Vol 47 (3) ◽  
pp. 701-719 ◽  
Author(s):  
Christopher L. Wolfe ◽  
Paola Cessi ◽  
Bruce D. Cornuelle
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Baroclinic Instability ◽  
Ocean Model ◽  
South Atlantic ◽  
Global Ocean ◽  
Leeuwin Current ◽  
The Indian Ocean ◽  
Atmospheric State

AbstractAn intrinsic mode of self-sustained, interannual variability is identified in a coarse-resolution ocean model forced by an annually repeating atmospheric state. The variability has maximum loading in the Indian Ocean, with a significant projection into the South Atlantic Ocean. It is argued that this intrinsic mode is caused by baroclinic instability of the model’s Leeuwin Current, which radiates out to the tropical Indian and South Atlantic Oceans as long Rossby waves at a period of 4 yr. This previously undescribed mode has a remarkably narrowband time series. However, the variability is not synchronized with the annual cycle; the phase of the oscillation varies chaotically on decadal time scales. The presence of this internal mode reduces the predictability of the ocean circulation by obscuring the response to forcing or initial condition perturbations. The signature of this mode can be seen in higher-resolution global ocean models driven by high-frequency atmospheric forcing, but altimeter and assimilation analyses do not show obvious signatures of such a mode, perhaps because of insufficient duration.

scholarly journals Interannual Variability of European Winter Weather: The Potential Vorticity Insight

2001 ◽  
Vol 2 (1-4) ◽  
pp. 52-60 ◽  
Author(s):  
A Massacand
Keyword(s):  
Interannual Variability ◽  
Potential Vorticity ◽  
Winter Weather

scholarly journals Transport Variability of the Brazil Current from Observations and a Model

2017 ◽  
Author(s):  
Claudia Schmid ◽  
Sudip Majumder
Keyword(s):  
Interannual Variability ◽  
Three Dimensional ◽  
Austral Summer ◽  
Southern Annular Mode ◽  
South Atlantic ◽  
Meridional Transport ◽  
Sea Level Pressure ◽  
Brazil Current ◽  
Coordinate Model ◽  
The Impact

Abstract. Brazil Current transports from observations and a model are analyzed to improve our understanding of its structure and variability. The observed transports are derived from a three-dimensional field of the velocity in the South Atlantic covering the years 1993 to 2015 (hereinafter called Argo & SSH). The mean transport of the Brazil Current from 3.8 ± 2.2 Sv (1 Sv is 106 m3s−1) at 25° S to 13.9 ± 2.6 Sv at 32° S, which corresponds to a mean slope of 1.4 ± 0.4 Sv per degree. The Hybrid Coordinate Model (HYCOM) has somewhat higher transports than Argo & SSH (5.2 ± 2.7 Sv and 18.7 ± 7.1 Sv at 25° S and 32° S), but these differences are small when compared with the standard deviations. Overall, the observed latitude dependence of the transport of the Brazil Current is in agreement with the wind-driven circulation in the super gyre of the subtropical South Atlantic. A mean annual cycle with highest (lowest) transports in austral summer (winter) is found to exist at selected latitudes (24° S, 35° S and 38° S). The significance of this signal shrinks with increasing latitude, mainly due to the mesoscale and interannual variability. In addition, it is found that the interannual variability at 24° S is correlated with the Southern Annular Mode and the Niño 3.4 index. A coupled EOF of the meridional transport and the sea level pressure is used to improve the understanding of the impact of these ocean indexes.

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