scholarly journals Marine climate change over the eastern Agulhas Bank of South Africa

2020 ◽  
Author(s):  
Mark R. Jury
Keyword(s):  
South Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rate Of Change ◽  
Sea Surface ◽  
Ensemble Model ◽  
Agulhas Current ◽  
Near Shore ◽  
Marine Climate ◽  
High Phase

Abstract. The rate of change in the marine environment along the south coast of South Africa (32–37 S, 20–30 E) is studied using reanalysis observations 1900–2015 and coupled ensemble model projections 1980–2100. Outcomes are influenced by resolution and time-span: ~1 degree datasets covering the whole period capture large-scale changes, while ~0.5 degree datasets in the satellite era better distinguish the cross-shelf gradients. Although sea surface temperatures off-shore are warming rapidly (.05 °C/yr since 1980), a trend toward easterly winds and a stronger Agulhas Current have intensified near-shore upwelling (-.03 °C/yr). The sub-tropical ridge during summer is drawn poleward by global warming and high phase southern oscillation index. Cooler inshore sea temperatures suppress latent heat flux and contribute to coastal desiccation (-.005 mm day−1/yr) and vegetation warming (.1 °C/yr) since 1980. Coupled ensemble projections from the Hadley and European models indicate that the shift toward drier weather and easterly winds may be sustained through the 21st century.

scholarly journals Marine climate change over the eastern Agulhas Bank of South Africa

Ocean Science ◽  
2020 ◽  
Vol 16 (6) ◽  
pp. 1529-1544
Author(s):  
Mark R. Jury
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Large Scale ◽  
Time Span ◽  
Rate Of Change ◽  
Sea Surface ◽  
Ensemble Model ◽  
Agulhas Current ◽  
Marine Climate ◽  
Subtropical Ridge

Abstract. The rate of change in the marine environment over the eastern Agulhas Bank along the south coast of South Africa (32–37∘ S, 20–30∘ E) is studied using reanalysis observations for 1900–2015 and coupled ensemble model projections for 1980–2100. Outcomes are influenced by resolution and time span: ∼ 1∘ datasets covering the whole period capture large-scale changes, while ∼ 0.5∘ datasets in the satellite era better distinguish the cross-shelf gradients. Although sea surface temperatures offshore are warming rapidly (0.05 ∘C yr−1 since 1980), a trend toward easterly winds and a locally stronger Agulhas Current have intensified nearshore upwelling (−0.03 ∘C yr−1). The subtropical ridge is gradually moving poleward, leading to a drier climate.

scholarly journals Effects of Climatic Drivers and Teleconnections on Late 20th Century Trends in Spring Freshet of Four Major Arctic-Draining Rivers

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 179
Author(s):  
Roxanne Ahmed ◽  
Terry Prowse ◽  
Yonas Dibike ◽  
Barrie Bonsal
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rate Of Change ◽  
The Arctic ◽  
Late 20Th Century ◽  
Basin Scale ◽  
The Arctic Ocean ◽  
Spring Freshet ◽  
Climatic Drivers

Spring freshet is the dominant annual discharge event in all major Arctic draining rivers with large contributions to freshwater inflow to the Arctic Ocean. Research has shown that the total freshwater influx to the Arctic Ocean has been increasing, while at the same time, the rate of change in the Arctic climate is significantly higher than in other parts of the globe. This study assesses the large-scale atmospheric and surface climatic conditions affecting the magnitude, timing and regional variability of the spring freshets by analyzing historic daily discharges from sub-basins within the four largest Arctic-draining watersheds (Mackenzie, Ob, Lena and Yenisei). Results reveal that climatic variations closely match the observed regional trends of increasing cold-season flows and earlier freshets. Flow regulation appears to suppress the effects of climatic drivers on freshet volume but does not have a significant impact on peak freshet magnitude or timing measures. Spring freshet characteristics are also influenced by El Niño-Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation and the North Atlantic Oscillation, particularly in their positive phases. The majority of significant relationships are found in unregulated stations. This study provides a key insight into the climatic drivers of observed trends in freshet characteristics, whilst clarifying the effects of regulation versus climate at the sub-basin scale.

Ocean Salinity Aspects of the Ningaloo Niño

2021 ◽  
pp. 1
Author(s):  
Yaru Guo ◽  
Yuanlong Li ◽  
Fan Wang ◽  
Yuntao Wei
Keyword(s):  
Fresh Water ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Near Surface ◽  
Ocean Salinity

AbstractNingaloo Niño – the interannually occurring warming episode in the southeast Indian Ocean (SEIO) – has strong signatures in ocean temperature and circulation and exerts profound impacts on regional climate and marine biosystems. Analysis of observational data and eddy-resolving regional ocean model simulations reveals that the Ningaloo Niño/Niña can also induce pronounced variability in ocean salinity, causing large-scale sea surface salinity (SSS) freshening of 0.15–0.20 psu in the SEIO during its warm phase. Model experiments are performed to understand the underlying processes. This SSS freshening is mutually caused by the increased local precipitation (~68%) and enhanced fresh-water transport of the Indonesian Throughflow (ITF; ~28%) during Ningaloo Niño events. The effects of other processes, such as local winds and evaporation, are secondary (~18%). The ITF enhances the southward fresh-water advection near the eastern boundary, which is critical in causing the strong freshening (> 0.20 psu) near the Western Australian coast. Owing to the strong modulation effect of the ITF, SSS near the coast bears a higher correlation with the El Niño-Southern Oscillation (0.57, 0.77, and 0.70 with Niño-3, Niño-4, and Niño-3.4 indices, respectively) than sea surface temperature (-0.27, -0.42, and -0.35) during 1993-2016. Yet, an idealized model experiment with artificial damping for salinity anomaly indicates that ocean salinity has limited impact on ocean near-surface stratification and thus minimal feedback effect on the warming of Ningaloo Niño.

Paleoclimate Sampling as a Sensor Placement Problem

2015 ◽  
Vol 28 (19) ◽  
pp. 7717-7740 ◽  
Author(s):  
Maud Comboul ◽  
Julien Emile-Geay ◽  
Gregory J. Hakim ◽  
Michael N. Evans
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
System Model ◽  
Surface Salinity ◽  
Placement Problem ◽  
Climate System Model ◽  
Optimal Networks

Abstract This study formulates the design of optimal observing networks for past surface climate conditions as the solution to a data assimilation problem, given a realistic proxy system model (PSM), paleoclimate observational uncertainties, and a network of current and proposed observing sites. The method is illustrated with the design of optimal networks of coral δ18O records, chosen among candidate sites, and used to jointly infer sea surface temperature (SST) and sea surface salinity (SSS) fields from the Community Climate System Model, version 4, last millennium simulation over the 1850–2005 period. It is shown that an existing paleo-observing network accounts for approximately 20% of the SST variance, and that adding 25 to 100 optimal pseudocoral sites would boost this fraction to 35%–52%. Characterizing the SST variance alone, or jointly with the SSS, leads to similar optimal networks, which justifies using coral δ18O records for SST reconstructions. In contrast, the network design for reconstructing SSS alone is fundamentally different, emphasizing the hydroclimatic centers of action of El Niño–Southern Oscillation. In all cases, network design depends strongly on the amplitude of the observational error, so replicates may be more beneficial than the exploration of new sites; these replicates tend to be chosen where proxies are already informative of the large-scale climate field(s). Finally, extensions to other types of paleoclimatic observations are discussed, and a path to operationalization is outlined.

Sea Surface Temperatures along the Coast of British Columbia: Regional Evidence for a Warming Trend

1990 ◽  
Vol 47 (2) ◽  
pp. 346-350 ◽  
Author(s):  
Howard J. Freeland
Keyword(s):  
British Columbia ◽  
Time Series ◽  
Large Scale ◽  
Southern Oscillation ◽  
Warming Trend ◽  
Global Scale ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Mean Values ◽  
Surface Temperatures

Sea-surface temperature has been measured at a large number of sites around the coast of British Columbia for periods well in excess of 50 yr. These time series are long enough to give clear evidence of a large scale secular warming. For the purposes of this paper the daily SST observations are decimated to monthly mean values. The observations are of particular value because observation methods have remained invariant throughout the observation period, and many of the stations are remote from civilisation allowing trends to be estimated that have not been contaminated with urbanization effects. Eighteen out of nineteen stations that are currently being sampled show a warming trend, the one that shows a cooling trend is the shortest time series, only in its eleventh year. The sea-surface temperatures at sites exposed to the Pacific Ocean show very high coherence with global scale air temperature variations but no relationship to the El Niño/Southern Oscillation signal.

Global monthly sea surface temperature and sea ice reconstruction for historical simulations

2020 ◽  
Author(s):  
Eric Samakinwa ◽  
Stefan Brönnimann
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Sea Surface ◽  
Annual Variability ◽  
Instrumental Records

<p>Variability in Sea Surface Temperature (SST) is one of the prime sources of intra-annual variability, and also an important boundary condition for Atmospheric General Circulation Models (AGCMs). In many AGCM simulations, SST and Sea Ice Concentration (SIC) are prescribed. While SSTs are specified according to observations available in recent period of instrumental records (1850 – present), SIC depends on climatological averages with less variability prior to the inception of satellite measurements. This limits our understanding of large-scale climate variations in the past.</p><p>In this study, we augment multi-proxy reconstructed annual mean temperature of Neukom et al. (2019) with intra-annual variability from HadISST (v2.0), for 850 years (1000 – 1849). Intra-seasonal variability, such as the phase-locking of El-Nino Southern Oscillation, Indian Ocean Dipole and Tropical Atlantic SST indices to annual-cycle, are utilized. The intra-annual component of HadISST and SST indices estimated from the multi-proxy reconstructed annual mean, are used to develop grid-based multivariate linear regression models using the Frisch-Waugh-Lovell theorem, in a monthly stratified approach. Furthermore, we introduce a scaling technique to ensure homogeneous mean and variance, similar to that of the target. SST observations obtained from ship measurements by ICOADS before 1850, will be integrated in an off-line data assimilation approach.</p><p>Similarly, we reconstruct SIC via analogue resampling of HadISST SIC (1941 – 2000), for both hemispheres. We pool our analogues in four seasons, comprising of 3 months each, such that for each month within a season, there are 180 possible analogues. The best analogues are selected based on correlation coefficients between reconstructed SST and its target.</p>

scholarly journals Coupled network analysis revealing global monthly scale co-variability patterns between sea-surface temperatures and precipitation in dependence on the ENSO state

2021 ◽  
Author(s):  
Nikoo Ekhtiari ◽  
Catrin Ciemer ◽  
Catrin Kirsch ◽  
Reik V. Donner
Keyword(s):  
Network Analysis ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Climate Impacts ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Surface Temperatures ◽  
Ocean Atmosphere

AbstractThe Earth’s climate is a complex system characterized by multi-scale nonlinear interrelationships between different subsystems like atmosphere and ocean. Among others, the mutual interdependence between sea surface temperatures (SST) and precipitation (PCP) has important implications for ecosystems and societies in vast parts of the globe but is still far from being completely understood. In this context, the globally most relevant coupled ocean–atmosphere phenomenon is the El Niño–Southern Oscillation (ENSO), which strongly affects large-scale SST variability as well as PCP patterns all around the globe. Although significant achievements have been made to foster our understanding of ENSO’s global teleconnections and climate impacts, there are many processes associated with ocean–atmosphere interactions in the tropics and extratropics, as well as remote effects of SST changes on PCP patterns that have not yet been unveiled or fully understood. In this work, we employ coupled climate network analysis for characterizing dominating global co-variability patterns between SST and PCP at monthly timescales. Our analysis uncovers characteristic seasonal patterns associated with both local and remote statistical linkages and demonstrates their dependence on the type of the current ENSO phase (El Niño, La Niña or neutral phase). Thereby, our results allow identifying local interactions as well as teleconnections between SST variations and global precipitation patterns.

scholarly journals The Hadley Circulation in Reanalyses: Climatology, Variability, and Change

2013 ◽  
Vol 26 (10) ◽  
pp. 3357-3376 ◽  
Author(s):  
H. Nguyen ◽  
A. Evans ◽  
C. Lucas ◽  
I. Smith ◽  
B. Timbal
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Average Rate ◽  
Hadley Circulation ◽  
Hadley Cell ◽  
Momentum Balance ◽  
Annular Modes ◽  
Modes Of Variability ◽  
Summer Hemisphere ◽  
High Phase

Abstract Analysis of the annual cycle of intensity, extent, and width of the Hadley circulation across a 31-yr period (1979–2009) from all existent reanalyses reveals a good agreement among the datasets. All datasets show that intensity is at a maximum in the winter hemisphere and at a minimum in the summer hemisphere. Maximum and minimum values of meridional extent are reached in the respective autumn and spring hemispheres. While considering the horizontal momentum balance, where a weakening of the Hadley cell (HC) is expected in association with a widening, it is shown here that there is no direct relationship between intensity and extent on a monthly time scale. All reanalyses show an expansion in both hemispheres, most pronounced and statistically significant during summer and autumn at an average rate of expansion of 0.55° decade−1 in each hemisphere. In contrast, intensity trends are inconsistent among the datasets, although there is a tendency toward intensification, particularly in winter and spring. Correlations between the HC and tropical and extratropical large-scale modes of variability suggest interactions where the extent of the HC is influenced by El Niño–Southern Oscillation (ENSO) and the annular modes. The cells tend to shrink (expand) during the warm (cold) phase of ENSO and during the low (high) phase of the annular modes. Intensity appears to be influenced only by ENSO and only during spring for the southern cell and during winter for the northern cell.

scholarly journals Meridional displacement of the Antarctic Circumpolar Current

2014 ◽  
Vol 372 (2019) ◽  
pp. 20130273 ◽  
Author(s):  
Sarah T. Gille
Keyword(s):  
Antarctic Circumpolar Current ◽  
Large Scale ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Altimeter Data ◽  
Eddy Heat Transport ◽  
Circumpolar Current

Observed long-term warming trends in the Southern Ocean have been interpreted as a sign of increased poleward eddy heat transport or of a poleward displacement of the entire Antarctic Circumpolar Current (ACC) frontal system. The two-decade-long record from satellite altimetry is an important source of information for evaluating the mechanisms governing these trends. While several recent studies have used sea surface height contours to index ACC frontal displacements, here altimeter data are instead used to track the latitude of mean ACC transport. Altimetric height contours indicate a poleward trend, regardless of whether they are associated with ACC fronts. The zonally averaged transport latitude index shows no long-term trend, implying that ACC meridional shifts determined from sea surface height might be associated with large-scale changes in sea surface height more than with localized shifts in frontal positions. The transport latitude index is weakly sensitive to the Southern Annular Mode, but is uncorrelated with El Niño/Southern Oscillation.

scholarly journals An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature

2013 ◽  
Vol 4 (2) ◽  
pp. 743-783 ◽  
Author(s):  
A. Tantet ◽  
H. A. Dijkstra
Keyword(s):  
Community Structure ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Interaction Network ◽  
Sea Surface ◽  
Global Mean Surface Temperature ◽  
Global Mean

Abstract. On interannual-to-multidecadal time scales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure as well as the first neighbour maps can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation and teleconnections. The community detection method allows to overcome some shortcomings of Empirical Orthogonal Function analysis or composite analysis and hence provides additional information with respect to these classical analysis tools. The community analysis provides also new insight into the relationship between patterns of sea surface temperature and the global mean surface temperature (GMST). On the decadal-to-multidecadal time scale, we show that only two communities (Indian Ocean and North Atlantic) determine most of the GMST variability.

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