scholarly journals Recent changes (2013-2017) in scyphomedusan fauna in the Boka Kotorska Bay, Montenegro (Southeast Adriatic)

2019 ◽  
Vol 60 (1) ◽  
pp. 25-39
Author(s):  
Ivana Violić ◽  
Davor Lučić ◽  
Ivona Milić Beran ◽  
Vesna Mačić ◽  
Branka Pestorić ◽  
...  
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Water Column ◽  
Sea Surface ◽  
Long Term Trends ◽  
Sst Anomalies ◽  
Chrysaora Hysoscella

A semi- quantitative time series (2013-2017) was used to present the recent events of scyphomedusae appearance and abundance in the Boka Kotorska Bay, Montenegro, Southeast Adriatic. Six meroplanktonic species were recorded: Aurelia spp, Chrysaora hysoscella, Cotylorhiza tuberculata ̧ Discomedusa lobata, Drymonema dalmatinum and Rhizostoma pulmo. Among them, C. hysoscella and D. lobata dominated in the water column during winter and spring, forming dense aggregations in March and May, and February to May, respectively. Our description of the D. lobata blooms are actually the first known records of blooms for this species. C. tuberculata was observed in the Bay principally in August and September. The bloom was occurred only in 2017, being the first information of C. tuberculata mass appearance in this area. We hypothesized that global warming phenomena could trigger the observed changes, and in this respect, long-term trends of sea surface temperature (SST) fluctuations were analysed. The scyphomedusae blooms coincided with high positive SST anomalies, noted in the last seven years for this area. To better understand the mechanisms underlying changes in their phenology and abundance, detailed studies on benthic stages in the Bay are essential.

scholarly journals Long term trends in the sea surface temperature of the Black Sea

Ocean Science ◽  
2010 ◽  
Vol 6 (2) ◽  
pp. 491-501 ◽  
Author(s):  
G. I. Shapiro ◽  
D. L. Aleynik ◽  
L. D. Mee
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Black Sea ◽  
Sea Surface ◽  
The Black Sea ◽  
The North ◽  
Sst Variability ◽  
Long Term Trends ◽  
Cooling Trend

Abstract. There is growing understanding that recent deterioration of the Black Sea ecosystem was partly due to changes in the marine physical environment. This study uses high resolution 0.25° climatology to analyze sea surface temperature variability over the 20th century in two contrasting regions of the sea. Results show that the deep Black Sea was cooling during the first three quarters of the century and was warming in the last 15–20 years; on aggregate there was a statistically significant cooling trend. The SST variability over the Western shelf was more volatile and it does not show statistically significant trends. The cooling of the deep Black Sea is at variance with the general trend in the North Atlantic and may be related to the decrease of westerly winds over the Black Sea, and a greater influence of the Siberian anticyclone. The timing of the changeover from cooling to warming coincides with the regime shift in the Black Sea ecosystem.

scholarly journals Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic

2009 ◽  
Vol 66 (7) ◽  
pp. 1467-1479 ◽  
Author(s):  
Sarah L. Hughes ◽  
N. Penny Holliday ◽  
Eugene Colbourne ◽  
Vladimir Ozhigin ◽  
Hedinn Valdimarsson ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Sea Surface ◽  
The North ◽  
Spatial Coverage ◽  
The North Atlantic

Abstract Hughes, S. L., Holliday, N. P., Colbourne, E., Ozhigin, V., Valdimarsson, H., Østerhus, S., and Wiltshire, K. 2009. Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic. – ICES Journal of Marine Science, 66: 1467–1479. Analysis of the effects of climate variability and climate change on the marine ecosystem is difficult in regions where long-term observations of ocean temperature are sparse or unavailable. Gridded sea surface temperature (SST) products, based on a combination of satellite and in situ observations, can be used to examine variability and long-term trends because they provide better spatial coverage than the limited sets of long in situ time-series. SST data from three gridded products (Reynolds/NCEP OISST.v2., Reynolds ERSST.v3, and the Hadley Centre HadISST1) are compared with long time-series of in situ measurements from ICES standard sections in the North Atlantic and Nordic Seas. The variability and trends derived from the two data sources are examined, and the usefulness of the products as a proxy for subsurface conditions is discussed.

scholarly journals Long term trends in the sea surface temperature of the Black Sea

2010 ◽  
Vol 7 (1) ◽  
pp. 91-119
Author(s):  
G. I. Shapiro ◽  
D. L. Aleynik ◽  
L. D. Mee
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Black Sea ◽  
Sea Surface ◽  
The Black Sea ◽  
The North ◽  
Sst Variability ◽  
Long Term Trends ◽  
Cooling Trend

Abstract. There is growing understanding that recent deterioration of the Black Sea ecosystem was partly due to changes in the marine physical environment. This study uses high resolution 0.25° climatology to analyze sea surface temperature variability over the 20th century in two contrasting regions of the sea. Results show that the deep Black Sea was cooling during the first three quarters of the century and was warming in the last 15–20 years; on aggregate there was a statistically significant cooling trend. The SST variability over the Western shelf was more volatile and it does not show statistically significant trends. The cooling of the deep Black Sea is at variance with the general trend in the North Atlantic and may be related to the decrease of westerly winds over the Black Sea, and a greater influence of the Siberian anticyclone. The timing of the changeover from cooling to warming coincides with the regime shift in the Black Sea ecosystem.

A process-oriented approach for mining marine heatwaves with a time series of raster formatted products

2020 ◽  
Author(s):  
Cunjin Xue ◽  
Changfeng Jing
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Spatial Structure ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Evolution ◽  
Sea Surface ◽  
The Third ◽  
Oriented Approach

<p>A marine heatwave (MHW) is defined as a coherent area of extreme warm sea surface temperature that persists for days to months, which has a property of evolution from production through development to death in space and time. MHWs usually relates to climatic extremes that can have devastating and long-term impacts on ecosystems, with subsequent socioeconomic consequences. Long term remote sensing products make it possible for mining successive MHWs at global scale. However, more literatures focus on a spatial distribution at a fixed time snapshot or a temporal statistic at a fixed grid cell of MWHs. As few considering the temporal evolution of MWHs, it is greater challenge to mining their dynamic changes of spatial structure. Thus, this manuscript proposes a process-oriented approach for identifying and tracking MWHs, named as PoAITM. The PoAITM considers a dynamic evolution of a MWH, which consists of three steps. The first step uses the threshold-based algorithm to identifying the time series of grid pixels which meets the MWH definition, called as MWH pixels; the second adopts the spatial proximities to connect the MWH pixels at the snapshots, and transforms them spatial objects, called as MWH objects; the third combines the dynamic characteristics and spatiotemporal topologies of MWH objects between the previous and next snapshots to identify and track them belonging to the same ones. The final extract MWH with a property from production through development to death is defined as a MWH process. Comparison with the prevail methods of tracking MHWs, The PoAITM has three advantages. Firstly, PoAITM combines the spatial distribution and temporal evolution of MWH to identify and track the MWH objects. The second considers not only the spatial structure of MWH at current snapshot, also the previous and next ones, to track the MWH process, which ensures the MWH completeness in a temporal domain. The third is the dynamic behaviors of MWH, e.g. developing, merging, splitting, are also found between the successive MWH objects. Finally, we address the global MWHs exploring from the sea surface temperature products during the period of January 1982 to December 2018. The results not only show well-known knowledge, but also some new findings about evolution characteristics of MWHs, which may provide new references for further study on global climate change.</p>

scholarly journals Long-term trends of biogenic sulfur aerosol and its relationship with sea surface temperature in Arctic Finland

2013 ◽  
Vol 118 (20) ◽  
pp. 11,770-11,776 ◽  
Author(s):  
James R. Laing ◽  
Philip K. Hopke ◽  
Eleanor F. Hopke ◽  
Liaquat Husain ◽  
Vincent A. Dutkiewicz ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Long Term Trends

scholarly journals The influence of low-frequency variability and long-term trends in North Atlantic sea surface temperature on Irish waters

2009 ◽  
Vol 66 (7) ◽  
pp. 1480-1489 ◽  
Author(s):  
Heather Cannaby ◽  
Y. Sinan Hüsrevoğlu
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Low Frequency ◽  
Warming Trend ◽  
Sea Surface ◽  
Low Frequency Variability ◽  
Warm Anomaly ◽  
Long Term Trends

Abstract Cannaby, H., and Hüsrevoğlu, Y. S. 2009. The influence of low-frequency variability and long-term trends in North Atlantic sea surface temperature on Irish waters. – ICES Journal of Marine Science, 66: 1480–1489. Sea surface temperature (SST) time-series collected in Irish waters between 1850 and 2007 exhibit a warming trend averaging 0.3°C. The strongest warming has occurred since 1994, with the warmest years in the record being 2005, 2006, and 2007. The warming trend is superimposed on significant interannual to multidecadal-scale variability, linked to basin-scale oscillations of the ocean–atmosphere system. The dominant modes of low-frequency variability in North Atlantic SST records, investigated using an empirical orthogonal function (EOF) analysis, correspond to the Atlantic Multidecadal Oscillation (AMO), the East Atlantic Pattern (EAP), and the North Atlantic Oscillation (NAO) index, respectively, accounting for 23, 16, and 9% of the total variance in the dataset. Interannual variability in Irish SST records is dominated by the AMO, which, currently in its warm phase, explains approximately half of the current warm anomaly in the record. The EAP and the NAO influence variability in Irish SST time-series on a smaller scale, with the EAP also contributing to the current warm anomaly. After resolving the prevalent oscillatory modes of variability in the SST record, the underlying warming trend compares well with the global greenhouse effect warming trend. The anthropogenic contribution to the current warm anomaly in Irish SSTs was estimated at 0.41°C for 2006, and this is predicted to increase annually.

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