Increasing Trends in Air and Sea Surface Temperature in the Central Adriatic Sea (Croatia)

The Adriatic Sea and its coastal region have experienced significant environmental changes in recent decades, aggravated by climate change. The most prominent effects of climate change (namely, an increase in sea surface and air temperature together with changes in the precipitation regime) could have an adverse effect on social and environmental processes. In this study, we analyzed the time series of sea surface temperature and air temperature measured at three meteorological stations in the Croatian part of the Adriatic Sea. To assess the trends and variations in the time series of sea surface and air temperature, different statistical methods were employed, i.e., linear and quadratic regressions, Mann–Kendall test, Rescaled Adjusted Partial Sums method, and autocorrelation. The results evidenced increasing trends in the mean annual sea surface temperature and air temperature; furthermore, sudden variations in values were observed in 1998 and 1992, respectively. Increasing trends in the mean monthly sea surface temperature and air temperature occurred in the warmer parts of the year (from March to August). The results of this study could provide a foundation for stakeholders, decision–makers, and other scientists for developing effective measures to mitigate the negative effects of climate change in the scattered environment of the Adriatic islands and coastal region.

Download Full-text

Global air temperature variability independent of sea-surface temperature influences

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133312460074 ◽

2012 ◽

Vol 37 (1) ◽

pp. 29-35

Author(s):

Andrew C. Comrie ◽

Gregory J. McCabe

Keyword(s):

Time Series ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Air Temperature ◽

Recent Literature ◽

Surface Air Temperature ◽

Warming Trend ◽

Sea Surface ◽

Sst Variability ◽

Global Surface

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

Download Full-text

Analyses of Climate Variations at Four Meteorological Stations on Remote Islands in the Croatian Part of the Adriatic Sea

Atmosphere ◽

10.3390/atmos11101044 ◽

2020 ◽

Vol 11 (10) ◽

pp. 1044

Author(s):

Ognjen Bonacci ◽

Matko Patekar ◽

Marco Pola ◽

Tanja Roje-Bonacci

Keyword(s):

Climate Change ◽

Time Series ◽

Water Resources ◽

Air Temperature ◽

Climate Models ◽

Adriatic Sea ◽

Temperature And Precipitation ◽

Intensive Exploitation ◽

Increasing Trends ◽

The Impact

The Mediterranean region is one of the regions in the world that is most vulnerable to the impact of imminent climate change. In particular, climate change has an adverse effect on both the ecosystem and socioeconomic system, influencing water availability for both human and environmental purposes. The most endangered water resources are along the coasts and on islands since they have relatively small volumes and are intensively exploited. We analyzed the time series of air temperature and precipitation measured at four meteorological stations (Komiža, Palagruža, Lastovo, and Biševo) located on small islands in the Croatian part of the Adriatic Sea in this study. The investigated time series extend from the 1950s to the present, being contemporaneous for approximately 50 years. Despite possessing discontinuity, they can be considered as representative for assessing climate change and variability in the scattered environment of the Croatian islands. The results showed increasing trends in the annual air temperature, while the annual cumulative precipitation did not show significant variations. In addition, the analyses of the monthly air temperature showed that statistically significant increasing trends occurred from April to August, suggesting a more severe impact during these months. These results are in accordance with regional and local studies and climate models. Although the climate variability during the analyzed period can be considered as moderate, the impact on water resources could be severe due to the combined effect of the increase in air temperature during warm periods and the intensive exploitation for tourism purposes.

Download Full-text

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

10.21203/rs.3.rs-905960/v1 ◽

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.

Download Full-text

Hubungan Antara Kelembaban Relatif Dengan Beberapa Variabel Iklim Dengan Pendekatan Korelasi Pearson di Samudera Hindia

Jurnal Siger Matematika ◽

10.23960/jsm.v2i1.2753 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Miftahuddin Miftahuddin ◽

◽

Ananda Pratama ◽

Ichsan Setiawan ◽

◽

...

Keyword(s):

Climate Change ◽

Wind Speed ◽

Relative Humidity ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Air Temperature ◽

Sea Surface ◽

Aceh Province ◽

Relationship Of ◽

The Relationship

The earth's climate is constantly changing, it's just that climate change in the past took place naturally. But until now, climate change has been very closely related to human activity, so the nature of the event has become faster and more drastic. Relative humidity is a parameter that can affect climate change in Indonesia, especially in Aceh Province. Aceh province is one of the provinces located on the island of Sumatra and directly facing the Indian Ocean. Thus, Aceh Province has a considerable impact on climate change. Changes in relative humidity will lead to changes in climate elements. There are several climate elements including air temperature, rainfall, sea surface temperature, wind speed, solar radiation, and dynamic altitude. One of the methods used to look at the relationship of each climate element is the Correlation method. The purpose of this study is to find out the relationship of each variable of the climate elements. The results showed that the relationship between variables X1 (air temperature) and X3 (sea surface temperature) had the highest closeness relationship with a positive correlation value of 0.77. The lowest closeness relationships are variables X2 (rainfall) and X4 (wind speed) with a negative weak correlation value of -0.01.

Download Full-text

Is summer sea surface temperature over the Arctic Ocean connected to winter air temperature over North America?

Climate Research ◽

10.3354/cr01412 ◽

2016 ◽

Vol 70 (1) ◽

pp. 19-27

Author(s):

M Ogi ◽

S Rysgaard ◽

DG Barber ◽

T Nakamura ◽

B Taguchi

Keyword(s):

North America ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Arctic Ocean ◽

Air Temperature ◽

Sea Surface ◽

The Arctic ◽

The Arctic Ocean ◽

Winter Air Temperature

Download Full-text

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

Proceedings of International Conference "Managinag risks to coastal regions and communities in a changinag world" (EMECS'11 - SeaCoasts XXVI) ◽

10.31519/conferencearticle_5b1b943a9e4336.75393991 ◽

2017 ◽

Author(s):

Diaz Juan Navia ◽

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.

Download Full-text

Influence of North Atlantic sea surface temperature anomalies on springtime surface air temperature variation over Eurasia in CMIP5 models

Climate Dynamics ◽

10.1007/s00382-021-05826-5 ◽

2021 ◽

Author(s):

Shangfeng Chen ◽

Renguang Wu ◽

Wen Chen

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Temperature Variation ◽

Air Temperature ◽

North Atlantic ◽

Surface Air Temperature ◽

Sea Surface ◽

Cmip5 Models ◽

Temperature Anomalies ◽

Sea Surface Temperature Anomalies

Download Full-text

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

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10080500 ◽

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.

Download Full-text