Long-term sea surface temperature baselines—time series, spatial covariation and implications for biological processes

2007 ◽  
Vol 68 (3-4) ◽  
pp. 405-420 ◽  
Author(s):  
Brian R. MacKenzie ◽  
Doris Schiedek
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Biological Processes

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 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.

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 Future temperature and salinity in Puget Sound, Washington State, under CMIP6 climate change scenarios

2021 ◽  
Author(s):  
Stevie Walker ◽  
Hem Nalini Morzaria-Luna ◽  
Isaac Kaplan ◽  
David Petatán-Ramírez
Keyword(s):  
Climate Change ◽  
Time Series ◽  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Puget Sound ◽  
Washington State ◽  
Trophic Levels ◽  
Sea Surface

Abstract In Washington State, climate change will reshape the Puget Sound marine ecosystem through bottom-up and top-down processes, directly affecting species at all trophic levels. To better understand future climate change effects on sea surface temperature and salinity in Puget Sound, we used empirical downscaling to derive high-resolution time series of future sea surface temperature and salinity. Downscaling was based on scenario outputs of two coarse-resolution General Circulation Models, GFDL-CM4 and CNRM-CM6-1-HR, developed as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). We calculated 30-year climatologies for historical and future simulations, calculated the anomalies between historical and future projections, interpolated to a high resolution, and applied the resulting downscaled anomalies to a Regional Ocean Modeling System (ROMS) time series, yielding short-term (2020–2050) and long-term (2070–2100) delta-downscaled forecasts. Downscaled output for Puget Sound showed temperature and salinity variability between scenarios and models, but overall, there was strong model agreement. Model variability and uncertainty was higher for long-term projections. Spatially, we found regional differences for both temperature and salinity, including higher temperatures in the South Basin of Puget Sound and higher salinity in the North Basin. This study is a first step to translating CMIP6 outputs to higher resolution predictions of future conditions in Puget Sound. Interpreting downscaled projections of temperature and salinity in Puget Sound will help inform future ecosystem-based management decisions, such as supporting end-to-end ecosystem modeling simulations and assessing local-scale exposure risk to climate change.

EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN

2017 ◽  
Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Extreme Values ◽  
Sea Surface ◽  
Absolute Maximum ◽  
Data Set ◽  
Arctic Oscillation Index ◽  
Colombian Pacific

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.

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.

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.

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