scholarly journals Relationship between sea surface temperature anomalies in the Southwestern Atlantic Continental Shelf and atmospheric variability on intraseasonal timescales

2021 ◽  
Author(s):  
Moira Luz Clara ◽  
Mariano S. Alvarez ◽  
Carolina Vera ◽  
Claudia G. Simionato ◽  
Andrés J. Jaureguizar
Keyword(s):  
Surface Temperature ◽  
Continental Shelf ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Southwestern Atlantic ◽  
Atmospheric Variability ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies

scholarly journals On the Angola Low Interannual Variability and Its Role in Modulating ENSO Effects in Southern Africa

2019 ◽  
Vol 32 (15) ◽  
pp. 4783-4803 ◽  
Author(s):  
Salvatore Pascale ◽  
Benjamin Pohl ◽  
Sarah B. Kapnick ◽  
Honghai Zhang
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Africa ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Atmospheric Variability ◽  
Coupled Modes ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies

Abstract The Angola low is a summertime low pressure system that affects the convergence of low-level moisture fluxes into southern Africa. Interannual variations of the Angola low reduce the seasonal prediction skills for this region that arise from coupled atmosphere–ocean variability. Despite its importance, the interannual dynamics of the Angola low, and its relationship with El Niño–Southern Oscillation (ENSO) and other coupled modes of variability, are still poorly understood, mostly because of the scarcity of atmospheric data and short-term duration of atmospheric reanalyses in the region. To bypass this issue, we use a long-term (3500 year) run from a 50-km-resolution global coupled model capable of simulating the summertime southern African large-scale circulation and teleconnections. We find that the meridional displacement and strength of the Angola low are moderately modulated by local sea surface temperature anomalies, especially those in proximity of the southeastern African coast, and to a lesser extent by ENSO and the subtropical Indian Ocean dipole. Comparison of the coupled run with a 1000-yr run driven by climatological sea surface temperatures reveals that the interannual excursions of the Angola low are in both cases associated with geopotential height anomalies over the southern Atlantic and Indian Ocean related to extratropical atmospheric variability. Midlatitude atmospheric variability explains almost 60% of the variance of the Angola low variability in the uncoupled run, but only 20% in the coupled run. Therefore, while the Angola low appears to be intrinsically controlled by atmospheric extratropical variability, the interference of the atmospheric response forced by sea surface temperature anomalies weakens this influence.

Copepod and monogenean infection of fish under sea surface temperature anomalies

2021 ◽  
pp. 102098
Author(s):  
F. Neptalí Morales-Serna ◽  
Lorenia Olivas-Padilla ◽  
Emigdio Marín-Enriquez ◽  
Juan M. Osuna-Cabanillas ◽  
Hugo Aguirre-Villaseñor ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies ◽  
Monogenean Infection

scholarly journals A Process-Oriented Approach to Identify Evolutions of Sea Surface Temperature Anomalies with a Time-Series of a Raster Dataset

2021 ◽  
Vol 10 (8) ◽  
pp. 500
Author(s):  
Lianwei Li ◽  
Yangfeng Xu ◽  
Cunjin Xue ◽  
Yuxuan Fu ◽  
Yuanyu Zhang
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Global Climate ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Global Climate Changes ◽  
Space And Time ◽  
Novel Approach ◽  
Sea Surface Temperature Anomalies

It is important to consider where, when, and how the evolution of sea surface temperature anomalies (SSTA) plays significant roles in regional or global climate changes. In the comparison of where and when, there is a great challenge in clearly describing how SSTA evolves in space and time. In light of the evolution from generation, through development, and to the dissipation of SSTA, this paper proposes a novel approach to identifying an evolution of SSTA in space and time from a time-series of a raster dataset. This method, called PoAIES, includes three key steps. Firstly, a cluster-based method is enhanced to explore spatiotemporal clusters of SSTA, and each cluster of SSTA at a time snapshot is taken as a snapshot object of SSTA. Secondly, the spatiotemporal topologies of snapshot objects of SSTA at successive time snapshots are used to link snapshot objects of SSTA into an evolution object of SSTA, which is called a process object. Here, a linking threshold is automatically determined according to the overlapped areas of the snapshot objects, and only those snapshot objects that meet the specified linking threshold are linked together into a process object. Thirdly, we use a graph-based model to represent a process object of SSTA. A node represents a snapshot object of SSTA, and an edge represents an evolution between two snapshot objects. Using a number of child nodes from an edge’s parent node and a number of parent nodes from the edge’s child node, a type of edge (an evolution relationship) is identified, which shows its development, splitting, merging, or splitting/merging. Finally, an experiment on a simulated dataset is used to demonstrate the effectiveness and the advantages of PoAIES, and a real dataset of satellite-SSTA is used to verify the rationality of PoAIES with the help of ENSO’s relevant knowledge, which may provide new references for global change research.

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