The low efficiency of the Fall and early Winter cooling does not balance the overall Sea Surface Temperature warming in the Mediterranean Cilician Basin

doi:10.21203/rs.3.rs-4912077/v1

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The low efficiency of the Fall and early Winter cooling does not balance the overall Sea Surface Temperature warming in the Mediterranean Cilician Basin

https://doi.org/10.21203/rs.3.rs-4912077/v1

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The continuous and significant rise of the sea surface temperature (SST) in the Eastern Mediterranean Sea over the past three decades is not uniform both in temporal and spatial scales. This study aimed to investigate the temporal evolution of the SST in the Cilician Basin on monthly to decadal scales within two partially overlapping periods (1983–2023 and 1995–2023) by utilising three datasets obtained with different methodologies. “The High-Resolution Daily Optimum Interpolation SST” (OISST V2.1), the fifth generation reanalysis (ERA5) “monthly averaged data on single-level”, and the available in-situ observations (1995–2023) were utilised to compare all datasets and analyse the temporal evolution of the SST in the region.

The annual mean SST results of the OISST (0.043 ℃/year) and In-Situ (0.042 ℃/year) datasets were almost identical. In both datasets, the highest warming is recorded in fall, and June is recorded with a decreasing trend. In the ERA5 dataset, the SST is increased by 0.054 ℃/year, and the highest warming is recorded in summer. Continuous and consecutive positive SST anomalies have been observed since 2013. The highest three annual mean SSTs since 1983 were recorded in the last six years, and 2018 was the warmest year in the studied period. On the decadal scale, a cooling of the SST was recorded between 1983 and 1993, and the highest warming occurred in the following decade, between 1993 and 2003.

The rise of the In-Situ SST in November and December was drastic, especially in 2017 and 2018. This excessive warming (low-efficient cooling) in the fall/early winter is of particular concern as it may affect the physical/biochemical characteristics of the water column, hence the circulation and coastal ecosystem.

Sea Surface Temperature

Cilician Basin

Climate Change

OISST/ERA5/In-situ data

Fall/early Winter Warming

Monthly to Decadal Trends

Sea Surface Temperature defines and influences local and global climate regimes, oceanic and atmospheric circulation, weather patterns, and regional phenomena. At the ocean-atmosphere interface, SST modulates the fluxes (i.e. heat, gases, momentum) between the two phases and affects the oceanic and atmospheric circulations, properties of the seawater, biochemical processes, primary production, weather patterns, and local phenomena (Trenberth 2009; Deser et al. 2010; O’Carroll et al. 2019; Pisano et al. 2020). The SST responds to anthropogenic and natural climate changes and variabilities in different time scales (i.e., seasonal, interannual, decadal and multidecadal) (Trenberth 2009; Deser et al. 2010; Reid et al. 2016; Schroeder et al. 2017; Pisano et al. 2020). The solar forcing, volcanic forcing, wind forcing, cloudiness, ocean-atmosphere interactions, and ocean-atmosphere circulations affect and modulate SST on different temporal and spatial scales (Hurrell and Deser 2009; Gastineau and Frankignoul 2015; Reid et al. 2016; Schroeder et al. 2017; Pisano et al. 2020; Rencurrel and Rose 2020). Along with the global natural forcing, greenhouse gas emissions caused by anthropogenic processes have changed the heat energy balance of the planet Earth on a global scale, especially in the last 50 years. About 90% of this additional heat energy generated by anthropogenic greenhouse gases is absorbed in the ocean, resulting in a warming of the SST of the world ocean (Stocker et al. 2013; Trenberth et al. 2014; Core Writing Team et al. 2015; Reid et al. 2016; Pastor et al. 2018). The increase in the SST enhances ocean acidification, deoxygenation, sea level rise, ocean circulation, water mass formations, heat, nutrient and carbon fluxes, primary production and weather phenomena such as marine heat waves, severe storms, extreme precipitation and evaporation. These processes and phenomena affect the global ocean systems, coastal ecosystems, and populations in coastal regions (Mohamed et al. 2019; O’Carroll et al. 2019; Reale et al. 2022; Biguino et al. 2023). Therefore, the SST is a crucial and essential parameter for monitoring the ocean’s present state and predicting future climatic events on global and regional scales.

The semi-enclosed Mediterranean Sea can be considered a laboratory for responding to climate change with continuous and rapid warming. The warming trend in the Mediterranean Sea, especially in the last three decades, is much more than the global ocean warming trend (Seneviratne et al. 2016; Pastor et al. 2020; Pisano et al. 2020; El-Geziry 2021; El-Geziry et al. 2023). Since the 1990s, a gradually increasing trend of SST has been observed in the Mediterranean Sea, while the highest SST warming has been recorded in the Levantine Basin of the Eastern Mediterranean Sea (Skliris et al. 2012; Macias et al. 2013; Samuel-Rhoads et al. 2013; Shaltout and Omstedt 2014; Pastor et al. 2018; Pisano et al. 2020; El-Geziry 2021). The rapid and continuous SST warming of the Levantine Basin recorded in the last few decades has been reported in several studies by using different methods (i.e., in-situ observations, model simulations, remote sensing and reanalysis data sets) with a rate ranging between 0.025–0.065 ℃/year (Macias et al. 2013; Samuel-Rhoads et al. 2013; Shaltout and Omstedt 2014; Ozer et al. 2017, 2022a; Pastor et al. 2018; Bengil and Mavruk 2019; Pisano et al. 2020; El-Geziry 2021; Saraçoğlu et al. 2021). It is worth mentioning that the study conducted in the southern Levantine Basin revealed a negative (decreasing) trend on the SST from 1975 to 1991 at about − 0.06 ^oC/year and an increasing (warming) trend from 2002 to 2018 at about 0.2 ^oC/year (El-Geziry 2021), and about 0.3 ^oC/year between 2007 and 2018 (El-Geziry et al. 2023).

Along with the anthropogenic events, the SST of the Mediterranean Sea is affected by and affects external and internal oceanic and atmospheric processes and events. The relationship between the Mediterranean Sea SST and the global atmospheric and oceanic events such as the North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Nino Southern Oscillation (ENSO) on the Mediterranean Sea are well studied in the literature (Hurrell and Deser 2009; Sun and Yuan 2009; Macias et al. 2013; Gastineau and Frankignoul 2015; Pisano et al. 2020; Yan et al. 2023; Li et al. 2024). The NOA, AMO, and ENSO are global events that influence and affect each other. The Mediterranean Sea SST is highly correlated with the AMO (Macias et al. 2013; Pisano et al. 2020). The NAO affects the atmospheric conditions of the whole Mediterranean. However, the influence of the NAO on the Mediterranean Sea SST is more pronounced in the Western than in the Eastern Mediterranean (Yan et al. 2023). The SST of the Eastern Mediterranean Sea is affected mainly by internal processes and features (Yan et al. 2023). Regional wind patterns, topographic and bathymetric features, energetic eddies, permanent gyres, water formations, surface and thermohaline circulation in the Eastern Mediterranean Sea, and phenomena like the Eastern Mediterranean Transient (EMT), reversal of the North Ionian Gyre and Bimodal Oscillation System (BIOS) are the internal processes that affect the seawater properties and characteristics of the Eastern Mediterranean Sea, hence the Levantine and the Cilician Basins (Ozer et al. 2017; Schroeder et al. 2017; Estournel et al. 2021).

The Eastern Mediterranean Sea and the Atlantic Ocean exchange water masses and heat through the straits of Sicily and Gibraltar by relatively cool and fresh Atlantic Water (AW) inflow at surface layers and relatively warm and salty Mediterranean outflow at intermediate layers (The POEM Group 1992; Robinson and Golnaraghi 1993; Fach et al. 2021). This communication affects the physical and biochemical properties of the Mediterranean Sea. The Levantine Basin is critical in this communication as it is the formation site of the Mediterranean outflow (The POEM Group 1992; Onken and Yuce 2000; The LIWEX Group 2003; Fach et al. 2021). The physical oceanographic properties and processes, such as vertical mixing of the water column and local water mass formations in the northern Levantine Basin, i.e., the Levantine Surface Water (LSW), Levantine Intermediate Water (LIW) and Levantine Deep Water (LDW), are well studied in the literature (Robinson et al. 1991; The POEM Group 1992; Onken and Yuce 2000; The LIWEX Group 2003; Kucuksezgin and Pazi 2006; Ozer et al. 2017; Salihoglu et al. 2019; Fach et al. 2021). The LIW is formed by vertical mixing or sinking of LSW to the intermediate depth by evaporative cooling during winter at several locations in the Levantine Basin, including the Cilician Basin (Fach et al. 2021). The SST, along with the salinity, is a fundamental parameter that affects and determines the physical oceanographic characteristics of the Levantine Basin, where the Cilician Basin is embedded (Malanotte-Rizzoli and Robinson 1988; Özsoy et al. 1989; Robinson and Golnaraghi 1993; Fach et al. 2021). The changes in the SST may affect the circulation and water mass formations in the Levantine Basin and, hence, in the Cilician Basin, as reported in the recent studies conducted in the southeastern and northeastern (Cilician) Levantine Basin (Fach et al. 2021; Ozer et al. 2022b; Deliceirmak et al. 2024, unpublished document).

In the Cilician Basin, the number of systematic in-situ oceanographic studies is temporally and spatially limited (Deliceırmak and Salihoğlu, 2020; Fach et al., 2021; Kucuksezgin and Pazi, 2006; Salihoglu et al., 2019; The POEM Group, 1992); hence the regional SST analyses mostly rely on model simulations, remote sensing and reanalysis data sets (Bengil and Mavruk 2019; Saraçoğlu et al. 2021). The study of (Saraçoğlu et al. 2021) between 1982 and 2020 revealed an increasing trend of the annual mean SST at about 0.032–0.042 ^oC/year in the Cilician Basin. Another study conducted in the Cilician Basin between 1981 and 2014 revealed warming of the annual mean SST by 0.032 ^oC/year (Bengil and Mavruk 2019).

In ocean studies, scientific and systematic in-situ observations are probably the best, especially in coastal regions and meso/sub-meso scales, but the most challenging method due to temporal and spatial difficulties. Despite their limitations, model simulations, remote sensing and reanalysis data sets are very beneficial and powerful tools and are widely used in ocean sciences and climate analysis, primarily due to the temporal and spatial coverage and resolution (Romanou et al. 2010; Shaltout and Omstedt 2012; Jordà et al. 2017; O’Carroll et al. 2019; Minnett et al. 2019; Hersbach et al. 2020; Huang et al. 2021). In coastal studies, in-situ observations are also used to verify and improve remote sensing and reanalysis data, which may not determine the local processes due to spatial resolution or gridded points of the datasets (O’Carroll et al. 2019).

This study aimed;

to investigate the temporal evolution of the SST in the Cilician Basin in two different periods (1983–2023 and 1995–2023) with available data by using three datasets obtained with different methodologies (i.e., satellite, reanalysis and in-situ observations),

to analyse decadal, annual, seasonal and monthly SST, warming rates, trends and anomalies, and also compare the consistency and differences between the datasets (i.e. satellite, reanalyses and in-situ) to determine the optimal methods for future studies to use in the region,

to evaluate and discuss the potentiality and plausibility of using in-situ observational data sets of shore-based meteorological stations as a supplementary method in oceanographic studies, especially in coastal regions.

Three different SST data sets, obtained by different methods (i.e. satellite, reanalysis and in-situ observations), were used in this study to investigate the temporal evolution of the SST on the northern coast of Cyprus. The studied area was about 785 km², off the coast of Kyrenia. As the first dataset, from now on, the NOAA dataset (blue coloured in all figures), “NOAA OISST V2.1 (NOAA 1/4^o Daily Optimum Interpolation SST High Resolution Dataset)” provided by NOAA PSL (Physical Sciences Laboratory), Boulder, Colorado, USA (https://psl.noaa.gov/) was downloaded for the period between 01/01/1983 and 31/12/2023 (Huang et al. 2021). The SST data of four relevant gridded points of the daily NOAA data set were processed by the R version 4.3.3 (R Core Team, 2024), using ncdf4 (Pierce, 2023) and tidyverse (Wickham, 2019) packages. In this study, the SST of four gridded points of the NOAA dataset was averaged and used as the NOAA mean SST (Fig. 1, blue dots).

As the second dataset, from now on, the ERA5 dataset (red coloured in all figures), “ECMWF ERA5 monthly averaged data on single levels from 1940 to the present”, the fifth generation of the ECMWF reanalysis for the global climate and weather, provided by the European Union Copernicus Climate Change Services (C3S) (https://doi.org/10.24381/cds.f17050d7) was downloaded for the period between 01/01/1983 and 31/12/2023 (Hersbach et al. 2020). The SST data of one relevant selected gridded point with a 0.25^o x 0.25^o spatial resolution of the ERA5 data set were processed by the R version 4.3.3 (R Core Team, 2024), using ncdf4 (Pierce, 2023) and tidyverse (Wickham, 2019) packages (Fig. 1, red dot).

As the third data set, from now on, the In-Situ dataset (green coloured in all figures), daily SST measurements of the Kyrenia Meteorological Station, the only station which has available SST data on the north coast of Cyprus, provided by the Meteorological Office of the Turkish Republic of Northern Cyprus (http://www.kktcmeteor.org/) was obtained for the period between 01/01/1995 and 31/12/2023. The SST has been measured daily by the Kyrenia Meteorological Station at the entrance of the Port of Kyrenia since 1995 (Fig. 1, green dot).

Temporal resolution for the NOAA and ERA5 SST datasets was selected to cover the last forty years between 1983 and 2023. However, the available In-Situ SST dataset was dated back to 1995. Therefore, two different periods (1983–2023 and 1995–2023) were used in this study. Additionally, all datasets were analysed over ten-year periods (i.e. 1983–1993, 1993–2003, 2003–2013, 2013–2023) to investigate the temporal evolution of the SST in the region.

Monthly means, seasonal means, annual means, trends and anomalies were calculated from the daily SST measurements. Pearson’s Product Moment was used to calculate correlations, and linear regression (95%) was used to calculate the trends. The SST trends were calculated and plotted independently for (i) the entire period and (ii) ten-year periods for each data set. The SST anomalies were calculated by removing the mean SST of the entire period from the annual mean SSTs. All plots and statistical analyses were conducted by using Sigma Plot Version 14.

The monthly time series of the AMO and ENSO indexes provided by NOAA PSL (Physical Sciences Laboratory), Boulder, Colorado, USA (https://psl.noaa.gov/) were downloaded for the period between 01/01/1983 and 31/12/2023. The monthly time series of the NAO index for the same period was downloaded from the website of the NOAA National Weather Service, Climate Prediction Center ( http://www.nws.noaa.gov/).

The temporal evolution of the annual mean SST of all datasets was presented in (Fig. 2). In the first period (1983–2023), the mean SST of the NOAA dataset was observed to be 0.40 ^oC higher than the ERA5 dataset. The mean SST of the two datasets were calculated as 21.92 ^oC and 21.52 ^oC, respectively (Fig. 2). The highest annual mean SST in both datasets was recorded in 2018, with 22.95 ^oC and 22.80 ^oC, respectively, in the NOAA and ERA5 datasets. The lowest annual mean SST in both datasets was recorded in 1992, with 21.00 ^oC and 20.23 ^oC in the NOAA and ERA5 datasets (Fig. 2). Linear trend calculations of the annual mean SST between 1983 and 2023 revealed an increasing trend in both data sets. During the investigated period, about 0.037 ℃/year and, in total, 1.48 ℃ of the SST increase was recorded in the NOAA dataset. In the ERA5 dataset, about 0.053 ℃/year and, in total, 2.12 ℃ of the SST increase was recorded in the region (Fig. 2).

In the second period (1995–2023), the highest mean SST was recorded in the In-Situ dataset with 22.23 ℃. The mean SST of the NOAA and ERA5 datasets was recorded at 22.14 ℃ and 21.85 ℃, respectively. The highest annual mean SST in all datasets was recorded in 2018 with 22.95 ℃, 22.80 ℃ and 23.35 ℃ in the NOAA, ERA5 and In-Situ datasets, respectively (Fig. 2). The lowest annual mean SST in NOAA and In-Situ datasets was recorded in 1996 with 21.25 ℃ and 21.32 ℃, respectively. In the ERA5 dataset, 20.63 ℃ recorded in 1995 was the lowest annual mean SST of the investigated period (Fig. 2). Linear trend calculations of the annual mean SST between 1995 and 2023 revealed an increasing trend in all data sets. During the investigated period, about 0.043 ℃/year and, in total, 1.20 ℃ of the SST increase was recorded in the NOAA dataset. In the ERA5 dataset, about 0.054 ℃/year and, in total, 1.48 ℃ of the SST increase was recorded. In the In-Situ dataset, the SST warming was recorded at 0.042 ℃/year and, in total, 1.18 ℃ during the investigated period between 1995 and 2023 (Fig. 2).

The results of mean SST and SST trends over ten-year periods were presented in (Fig. 3 and Table 1). In the first ten-year period (1983–1993), negative (decreasing) trends were observed in NOAA and ERA5 datasets with − 0.045 ℃/year and − 0.054 ℃/year, respectively. In the same period, no data was available for the In-Situ dataset. In all other ten-year periods (i.e. 1993–2003, 2003–2013 and 2013–2023), positive (increasing) trends were recorded in all datasets. The highest increasing trends were recorded in the second ten-year period (1993–2003) with 0.106 ℃/year, 0.142 ℃/year and 0.088 ℃/year, respectively, in the NOAA, ERA5 and In-Situ datasets (Fig. 3 and Table 1). The mean SST over ten-year periods revealed continuous increases in all datasets. From 1983–1993 to 2013–2023, the mean SST increased by 1.13 ℃ and 1.61 ℃ in the NOAA and ERA5 datasets, respectively. In the In-Situ dataset, the mean SST increased from 21.87 ℃ to 22.57 ℃ from 1995–2003 to 2013–2023 (Fig. 3 and Table 1).

Table 1

The annual mean SST and SST trends in ten-year periods and entire periods (1983–2023 and 1995–2023).
	NOAA Dataset		ERA5 Dataset		In-Situ Dataset
Period	Mean ^oC	Trend ^oC/year	Mean ^oC	Trend ^oC/year	Mean ^oC	Trend ^oC/year
1983–1993	21.34	-0.045	20.69	-0.054	NA	NA
1993–2003	21.70	0.106	21.27	0.142	21.87	0.088
2003–2013	22.03	0.041	21.76	0.092	22.15	0.055
2013–2023	22.47	0.056	22.30	0.053	22.57	0.060
1983–2023	21.92	0.037	21.52	0.053	NA	NA
1995–2023	22.14	0.043	21.85	0.054	22.23	0.042

The analyses of annual mean SST anomalies of all the datasets revealed continuous and consecutive positive anomalies in the last ten years (Fig. 4). The highest positive SST anomalies in all data sets were recorded in 2018, at about 1.03 ℃ in the NOAA, 1.28 ℃ in the ERA-5, and 1.12 ℃ in the In-Situ dataset. The highest negative SST anomaly in the NOAA and ERA5 datasets was recorded in 1992, at -0.93 ℃ and − 1.29 ℃, respectively. In the In-Situ data set, the highest negative SST anomaly was recorded in 1996 at -0.91 ℃ (Fig. 4).

The results of the monthly mean SST and SST trends were presented in (Fig. 5 and Table 2). The results revealed that August was the warmest month and February was the coldest month in all datasets. The highest monthly mean SST in the NOAA dataset was recorded in August 2021 and August 2023 at about 29.32 ℃ and 29.43 ℃, respectively. In the ERA5 dataset, the highest monthly mean SST were recorded in August 2010 (29.51 ℃), August 2021 (29.41 ℃ ) and August 2023 (29.31 ℃). In the In-Situ dataset, the highest monthly mean SST were recorded with over 30.00 ℃ in August 1998 (30.25 ℃), August 2010 (30.30 ℃), August 2021 (30.20 ℃) and August 2023 (30.00 ℃), The lowest monthly mean SST of the NOAA, ERA5 and In-Situ datasets were recorded in March 1993 (15.67 ℃), February 1993 (14.68 ℃), February 1997 (15.14 ℃), respectively (Table 2).

Between 1983 and 2023, increasing trends in all months were observed in NOAA and ERA5 datasets (Table 2). In the NOAA dataset, the highest increasing trends of the monthly mean SST were recorded in October (0.045 ℃/year) and November (0.053 ℃/year), while the lowest increasing trend was recorded in June (0.021 ℃/year) (Table 2). In the ERA5 dataset, the highest increasing trends of the monthly mean were recorded in July (0.073 ℃/year) and August (0.070 ℃/year), while the lowest increasing trend was recorded in February (0.036 ℃/year) (Table 2).

Between 1995 and 2023, in the ERA5 dataset, increasing trends were observed in all months (Fig. 5 and Table 2). However, decreasing trends were recorded in June at the NOAA and In-Situ datasets (Fig. 5 and Table 2). In the NOAA dataset, the highest increasing trends of the monthly mean SST were recorded in September (0.069 ℃/year) and November (0.065 ℃/year). A decreasing trend was observed in June with − 0.002 ℃/year (Fig. 5 and Table 2). In the ERA5 dataset, the highest increasing trends of the monthly mean SST were recorded in August (0.066 ℃/year), September (0.086 ℃/year) and November (0.067 ℃/year), while the lowest increasing trend was recorded in June (0.030 ℃/year) (Fig. 5 and Table 2). In the In-Situ dataset, the highest increasing trends of the monthly mean SST were recorded in November (0.097 ℃/year) and December (0.086 ℃/year). A decreasing trend was observed in June with − 0.017 ℃/year (Fig. 5 and Table 2).

Table 2

Monthly mean SST and SST trends of all datasets from 1983 to 2023 (left) and 1995 to 2023 (right).
1983–2023							1995–2023
	NOAA Dataset		ERA5 Dataset		In-Situ Dataset			NOAA Dataset		ERA5 Dataset		In-Situ Dataset
Month	Mean ^oC	Trend ^oC/yr	Mean ^oC	Trend ^oC/yr	Mean ^oC	Trend ^oC/yr	Month	Mean ^oC	Trend ^oC/yr	Mean ^oC	Trend ^oC/yr	Mean ^oC	Trend ^oC/yr
Jan	17.22	0.035	16.98	0.039	NA	NA	Jan	17.36	0.057	17.18	0.051	16.61	0.047
Feb	16.60	0.026	16.33	0.036	NA	NA	Feb	16.74	0.033	16.56	0.039	16.19	0.020
Mar	16.83	0.034	16.39	0.041	NA	NA	Mar	17.03	0.036	16.65	0.044	17.03	0.024
Apr	17.95	0.035	17.49	0.040	NA	NA	Apr	18.13	0.048	17.72	0.049	18.19	0.035
May	20.72	0.035	20.27	0.052	NA	NA	May	20.94	0.039	20.61	0.049	21.21	0.016
Jun	24.18	0.021	23.72	0.048	NA	NA	Jun	24.39	-0.002	24.10	0.030	24.87	-0.017
Jul	27.25	0.040	26.77	0.073	NA	NA	Jul	27.56	0.026	27.31	0.057	28.22	0.025
Aug	28.37	0.037	27.98	0.070	NA	NA	Aug	28.62	0.033	28.43	0.066	29.37	0.036
Sep	27.42	0.043	27.08	0.066	NA	NA	Sep	27.60	0.069	27.43	0.086	28.24	0.064
Oct	25.16	0.045	24.83	0.059	NA	NA	Oct	25.39	0.058	25.17	0.062	25.70	0.069
Nov	21.98	0.053	21.63	0.063	NA	NA	Nov	22.28	0.065	22.01	0.067	22.26	0.097
Dec	19.01	0.042	18.77	0.046	NA	NA	Dec	19.27	0.049	19.07	0.049	18.87	0.086

The results of the seasonal (oceanographic winter, spring, summer and fall) mean SST and SST trends between 1995 and 2023 were presented in (Fig. 6). The analyses of the seasonal SST trends between 1995 and 2023 revealed warming of all seasons. The lowest warming occurred in the oceanographic spring in all datasets, with 0.028 ℃/year in the NOAA, 0.043 ℃/year in the ERA5 and 0.010 ℃/year in the In-Situ datasets (Fig. 6). The highest warming rate in the ERA5 dataset was observed in the oceanographic summer with 0.070 ℃/year. On the other hand, the highest warming rates in the NOAA and In-Situ datasets were observed in the oceanographic fall with 0.057 ℃/year and 0.084 ℃/year, respectively (Fig. 6). The lowest seasonal mean SST was recorded at 16.61 ℃, and the highest seasonal mean SST was recorded at 28.61 ℃, both in the In-Situ dataset(Fig. 6). The seasonal mean SST between 1995 and 2023 were recorded at 16.61 ℃, 21.42 ℃, 28.61 ℃ and 22.28 ℃, respectively, in winter, spring, summer and fall (Fig. 6). In all datasets, the highest winter SST was recorded in 2011, 2018 and 2021, the highest spring SST in 2018, and the highest summer SST in 2018 and 2023. In the fall, the highest SST was recorded in 2020 and 2023 in the NOAA and ERA5 datasets. On the other hand, 2018, 2023, 2017 and 2021 were the warmest summers in the In-situ dataset, respectively (Fig. 6).

The results of the annual maximum (max) and minimum (min) SST and SST trends between 1995 and 2023 were presented in (Fig. 7). The means and trends of the annual max SST were calculated as 28.62 ℃ and 0.033 ℃/year in the NOAA, 28.43 ℃ and 0.069 ℃/year in the ERA5 and 29.37 ℃ and 0.036 ℃/year in the In-Situ dataset, respectively. The means and trends of the annual min SST were calculated as 16.68 ℃ and 0.040 ℃/year in the NOAA, 16.46 ℃ and 0.042 ℃/year in the ERA5 and 16.10 ℃ and 0.027 ℃/year in the In-Situ dataset, respectively (Fig. 7). In the ERA5 and In-Situ datasets, the warming rate of the annual max SST was higher than the annual min SST, contrary to the NOAA dataset (Fig. 7). The highest warming rate was observed in ERA5 annual max SST, while the lowest was in the In-Situ annual min SST. The highest annual max SST and the lowest annual min mean SST were recorded in the In-Situ dataset (Fig. 7). The highest annual max SST (~ 30 ℃ and over) was recorded in 1998, 2010, 2017 and consecutively in 2021, 2022 and 2023. The lowest annual max SST in all datasets was recorded in 1997. The highest annual min SST in all datasets was recorded in 2021 with 17.71 ℃, 17.51 ℃ and 17.10 ℃, respectively, in the NOAA, ERA5 and In-Situ datasets (Fig. 7).

The correlations between the results of this study and global atmospheric and oceanic processes, such as the AMO, NAO and ENSO, which affect the SST of the Mediterranean Sea, were presented in (Table 3). The results of all datasets in this study were highly correlated with the AMO. On the annual scale, there was a positive correlation with the AMO and a negative correlation with the ENSO. There is no statistically significant relationship between the results of this study and the NAO on the annual scale. However, a negative correlation is observed with the NAO on the monthly scale.

The correlation between the AMO and the NOAA dataset is 8.184e-01, the ERA5 dataset is 8.468e-01, and the In-Situ dataset is 6.668e-01. All correlation coefficients marked with (**) in (Table 3) were statistically significant, with P values of < 0.050.

Table 3

Pearson correlation coefficients between the results of this study and the AMO, NAO and ENSO Indexes.
	NOAA Dataset		ERA5 Dataset		In-Situ Dataset
Annual	Correlation Coefficient	P Value	Correlation Coefficient	P Value	Correlation Coefficient	P Value
AMO	8.184e-01**	1.915e-09	8.468e-01**	1.447e-10	6.668e-01**	5.109e-04
NAO	-1.459e-01	3.626e-01	2.332e-01	1.422e-01	6.973e-02	7.193e-01
ENSO	-3.859e-01**	1.2703e-02	-3.609e-01**	2.043e-02	-2.212e-01	2.488e-01
Monthly
NAO	-2.620e-01**	3.635e-09	-2.778e-01**	3.622e-10	-2.670e-01**	4.310e-07
** Statistically significant (P values are < 0.050)

The continuous warming of SST in the Eastern Mediterranean Sea has been well-studied in the literature (Samuel-Rhoads et al. 2013; Shaltout and Omstedt 2014; Ozer et al. 2017; Pastor et al. 2018, 2020; Mohamed et al. 2019; Pisano et al. 2020; El-Geziry 2021; García-Monteiro et al. 2022). Most of these studies are conducted spatially on a basin scale and temporally on an annual scale. The effects of warming SST in the Cilician Basin, particularly in the southern Cilician Basin (northern coast of Cyprus), are not well-known, especially on monthly, seasonal, and regional scales. This study investigated the temporal evolution (i.e. annual, seasonal and monthly) of SST in the southern Cilician Basin between 1983 and 2023 with two datasets (i.e. NOAA and ERA5) and between 1995 and 2023 with three datasets (i.e. NOAA, ERA5 and In-Situ) to analyse warming rates and trends and also compared the consistency and differences between the datasets (i.e. satellite, reanalyses and in-situ) to determine the optimal methods to be used in the region for the future studies.

Remarkably, the mean SST and the warming rate of the NOAA (22.14 ^oC and 0.043 ^oC/year) and In-Situ (22.23 ^oC and 0.042 ^oC/year) datasets are very similar and consistent on the annual scale between 1995 and 2023. On the other hand, the annual mean SST and the warming rate of the ERA5 revealed a higher warming rate (0.054 ^oC /year) and a lower mean SST (21.85 ^oC) in the same period (Fig. 2 and Table 1). This difference could be because of either the spatial resolution (gridded points) of the ERA5 in the region, where there is only one gridded point in the studied area or the estimation issues (over or under-estimation) of the ERA5, especially in the coastal regions, as concluded in the literature (Romanou et al. 2010; Jordà et al. 2017). The increasing trends of the annual mean SST on all datasets in this study are consistent and within the same range as the results of several other studies in the literature, which reported an SST increase of about 0.025–0.065 ℃/year in the Levantine Basin in the last few decades (Skliris et al. 2012; Macias et al. 2013; Samuel-Rhoads et al. 2013; Shaltout and Omstedt 2014; Ozer et al. 2017, 2022a; Pastor et al. 2018; Bengil and Mavruk 2019; Pisano et al. 2020; El-Geziry 2021; Saraçoğlu et al. 2021).

The annual mean SST is increased by a total of 1.48 ℃ in the NOAA and 2.12 ℃ in the ERA5 datasets from 1983 to 2023. The increase of the annual mean SST from 1995 to 2023 is a total of 1.20 ℃, 1.51 ℃ and 1.18 ℃, respectively, in the NOAA, ERA5 and In-Situ datasets. However, analyses of the annual mean SST over ten-year periods (1983–1993, 1993–2003, 2003–2013 and 2013–2023) revealed that warming in the region is not linear (Fig. 3 and Table 1). The highest increasing trends in all datasets are recorded between 1993 and 2003 (NOAA 0.106 ℃/year, ERA5 0.142 ℃/year and In-Situ 0.088 ℃/year).

On the other hand, decreasing (negative) trends of the annual mean SST of about − 0.045 ℃/year in the NOAA and − 0.054 ℃/year in the ERA5 datasets are recorded in the region between 1983 and 1993 (Fig. 3 and Table 1). Although no data is available in the In-Situ dataset before 1995, the highest increasing trend recorded between 1995 and 2003 may indicate a decreasing trend in the previous period, as in the NOAA and ERA5 datasets.

The decreasing trend of the annual mean SST between 1983 and 1993 is consistent with the study (El-Geziry 2021), which revealed a decreasing trend of about − 0.06 ℃/year in the southern Levantine Basin between 1975 and 1991. The cooling of the SST in the 1980s and early 1990s may be related to the external oceanic processes such as the AMO, which is highly correlated with the results (Table 3) and was in a negative phase during the period (Skliris et al. 2012; Pisano et al. 2020), or the regime shift that occurred in the 1980s due to volcanic eruptions, which had a global impact on climate (Reid et al. 2016), or internal dynamics such as intense atmospheric forcing and oceanic processes which affect the thermohaline circulation of the Eastern Mediterranean Sea (Schroeder et al. 2017). The highest increasing trend observed between 1993 and 2003, following the cooling of the SST in the region, shall be explained by the recovery of the climate system, enhanced by the anthropogenic forcing.

On the annual scale, all datasets (i.e. NOAA, ERA5 and In-Situ) generally revealed consistent and satisfactory results, especially in temporal evolution, trends and anomalies observed in the annual mean SST (Fig. 2 and Table 1). It is important to note that the highest three annual mean SSTs of the last forty years are recorded in the last six years (Fig. 2), and there has been a continuous and significant positive annual mean SST anomaly in the last ten years (Fig. 4). In all datasets, the warmest annual mean SST was recorded in 2018, followed by 2023, 2021 and 2010, respectively (Fig. 2). Despite 2023 being affected by a strong El Nino, which leads an unprecedented increase in the SST all around the globe (Li et al. 2024), 2018 is still the year that the highest annual mean SST and the highest positive annual mean SST anomalies are recorded in all datasets (Fig. 2 and Fig. 4).

The record-breaking annual mean SST of 2018 is also reported by the study of (Ozer et al. 2022b) conducted in the southern Levantine Basin, which associated the warming in 2018 with the BIOS mechanism (reversal of the North Ionian Gyre). The BIOS mechanism affects the thermohaline circulation of the Eastern Mediterranean Sea by limiting the exchange of water masses (i.e. Atlantic Water and the LIW) at the Strait of Sicily (Ozer et al. 2017; Schroeder et al. 2017; Estournel et al. 2021).

This study does not aim to discuss the thermohaline circulation or circulation time of surface waters; however, it shall be noted that the effects of the BIOS mechanism may not be similar simultaneously in different spaces, and it is not the first time that the Northern Ionian Gyre has reversed, but such warming, as experienced in 2018, has never been evidenced. The warming in 2018 may be related to the BIOS mechanism, as concluded by (Ozer et al. 2022b), or along with the BIOS mechanism, it may be related to a combination of regional atmospheric and oceanic conditions (i.e. changes in wind regimes, atmospheric pressure and circulation), which requires further investigation.

The record-breaking annual mean SST and anomalies recorded in 2018 are mainly caused by the unusual warming observed in the winter and especially in the spring of 2018 (Fig. 6), which may also be related to and influenced by the high SSTs recorded in the summer and fall of 2017. The summer of 2017 was one of the hottest seasons of the last forty years in all datasets, and the fall of 2017 was recorded as one of the hottest in the In-Situ dataset (not observed in the NOAA and ERA5 datasets) (Fig. 6). It should be noted that with the lack of the local Poyraz wind (not shown here), a cold and dry north-northeasterly wind blowing in mid-fall and winter, the SST is not cooling down efficiently in the Cilician Basin.

Contrary to the annual mean SST, significant differences between the datasets were observed in monthly and seasonal SST trends and warming rates. At this point, it is worth mentioning that the climatological seasons in the Eastern Mediterranean Sea are defined as long, hot and dry summers with mild and wet winters. Early spring and mid-fall shall be characterised as the transition period between summer and winter (Özsoy et al. 1989). In the Levantine Basin, the time lag of the effect of atmospheric forcing (i.e. air temperature) on the SST is about fifteen to thirty days (Ozer et al. 2022a). Therefore, in this study, the seasons (oceanographical seasons) are defined according to the monthly mean SSTs, in which January, February, and March are classified as Winter; April, May, and June are classified as Spring; July, August, and September are classified as Summer; and October, November, and December are classified as Fall.

The oceanographic spring season, particularly June, has the lowest increasing trend in all datasets between 1995 and 2023. Moreover, in June, even decreasing trends are recorded in the NOAA (-0.002 ^oC/year) and In-Situ (-0.017 ^oC/year) datasets in the same period. The ERA5 dataset revealed an increasing trend with 0.030 ^oC/year in June (Fig. 5 and Fig. 6). This result contradicts the results of (Skliris et al. 2012; Pastor et al. 2018; El-Geziry 2021), which concluded that a high warming rate of the SST in the region occurred in the spring.

On the other hand, variabilities are observed on the highest warming trend between all datasets on monthly and seasonal scales. In the NOAA dataset, the highest warming rate is recorded in early to mid-fall (September to November). In the ERA5 dataset, the highest warming occurred in mid-summer (August, September) and November. In the In-Situ dataset, the highest warming trend is recorded in the fall, especially in November and December (Fig. 5 and Fig. 6).

One of the most significant differences between the datasets on a monthly/seasonal scale is observed in November and December of 2017 and 2018, with excessive warming recorded in the In-Situ dataset but not in the NOAA and ERA5 datasets. This difference between the datasets shall be explained by local atmospheric and oceanographic processes, which cannot monitored or measured by satellite and reanalyses, or it should be an observational error. The latter is unlikely due to the observation methodology, and it was observed consecutively in 2017 and 2018.

The results of the monthly/seasonal ERA5 dataset in this study revealed consistent and similar results to the studies that conclude the highest increasing trend on the SST is observed in the summer season (Samuel-Rhoads et al. 2013; Shaltout and Omstedt 2014). However, contrary to the ERA5 dataset of this study and the studies mentioned above, the highest increasing trend of the SST in the NOAA and In-Situ datasets from 1995 to 2023 is recorded in the fall, which supports the results of (Saraçoğlu et al. 2021) conducted in the northern Cilician Basin.

Probably the most important outcome of this study is the warming of the SST recorded in the fall. In the Levantine Basin, the SST in late fall (November and December) is crucial for vertical mixing processes and water mass formations. Cooling of the SST in November and December is the precondition of these processes (The POEM Group 1992; The LIWEX Group 2003; Kucuksezgin and Pazi 2006; Salihoglu et al. 2019; Deliceirmak and Salihoglu 2020; Fach et al. 2021). Therefore, excessive warming recorded in these months may affect the vertical mixing and stratification of the water column and the formation of the LIW, hence the circulation and the coastal ecosystem.

Furthermore, as concluded in the past (Hurrell and Deser 2009; Trenberth 2009; Deser et al. 2010; Gastineau and Frankignoul 2015; Pisano et al. 2020; Rencurrel and Rose 2020), the results of this study revealed that the rising trend of SST is non-linear on the temporal scale. Hence, the effect of warming SST on the seawater’s physical properties may be observed in long-term (i.e. decadal) and short-term (i.e. annual, seasonal and monthly) scales. The short-term effect of warming SST shall be reflected as salinity shifts and changes in physical and biochemical oceanographic characteristics observed on the upper thermocline in the Levantine Basin (Ozer et al. 2017; Fach et al. 2021; Deliceirmak et al. 2024, unpublished document) and may be correlated with the increasing SST in the region, especially in the last ten years.

As a final point, methods used widely in ocean sciences, such as reanalysis, remote sensing and model simulation, are continually improving, and they are powerful and beneficial tools, primarily due to temporal and spatial coverage and resolution. However, limitations in their estimations, especially in coastal regions, are subject to discussions (Romanou et al. 2010; Jordà et al. 2017; O’Carroll et al. 2019; Pisano et al. 2020; Meng et al. 2023). Keeping this in mind, the encouraging results of this study may shed light on improving the accuracy of the methods mentioned above for coastal regions and, if consistently verified, may encourage the use of in-situ data sets of coastal meteorological stations as a supplementary or validation method in coastal ocean studies.

All datasets investigated in this study revealed consistent results on the annual scale and a clear-cut increasing trend of the SST in the Cilician Basin since 1995. The warming rates of the annual mean SSTs are recorded as 0.043 ℃/year, 0.054 ℃/year and 0.042 ℃/year in the NOAA, ERA5 and In-Situ datasets. Remarkably, the results of the NOAA OISST V2.1 and In-Situ datasets are very similar and consistent, suggesting the best or optimal methods to be used in the Cilician Basin.

The most important outcome of this study is probably the differences observed on monthly and seasonal scales. The highest warming observed in the fall, inferred from the NOAA and In-Situ datasets, may be crucial and affect the physical oceanographic properties of the Cilician Basin, especially the formation and characteristics of the LIW.

The increasing trend of the SST observed in the Cilician Basin in the last thirty years may affect the regional oceanographic and atmospheric variables and processes on different temporal and spatial scales. Therefore, especially in the coastal regions, mesoscale or sub-mesoscale oceanographic and climatological time series observations, such as remote sensing, reanalyses and in-situ observations, are crucial to investigate the effects of rising SST on the oceanographic and atmospheric properties on different temporal and spatial scales and shall be carefully monitored and well-assessed.

Statement and Declarations

Funding

The authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript.

Competing Interests

The authors declare that they have no known competing financial and non-financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author Contribution

All authors contributed to the study’s conception and design. Cagri Deliceirmak and Ilkay Salihoglu performed material preparation, data collection, analysis, visualisation, writing and reviewing. Ilkay Salihoglu supervises the study. All authors read and approved the final manuscript.

Data Sharing and Availability

The NOAA OISST V2.1 High Resolution Dataset is available at NOAA PSL, Boulder, Colorado, USA, https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html. The AMO index is available at the NOAA PSL, Boulder, Colorado, USA, https://psl.noaa.gov/data/timeseries/AMO/. The ENSO index is available at the NOAA PSL, Boulder, Colorado, USA, https://psl.noaa.gov/enso/mei/. The NAO index is available at the Climate Prediction Center of the NOAA, https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml. The ECMWF ERA5 monthly averaged data on single levels from 1940 to the present is available at the EU C3S, https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview (https://doi.org/10.24381/cds.f17050d7). The in-situ SST data of the Kyrenia Meteorological Station is available upon request from the corresponding author.

Acknowledgements

The authors acknowledge the Meteorological Office of the Turkish Republic of Northern Cyprus (TRNC) for providing the in-situ SST dataset, the National Oceanic and Atmospheric Administration (NOAA) of the United States for providing the gridded “1/4^o Daily Optimum Interpolation SST High Resolution Dataset” (OISSTV2), Atlantic Multidecadal Oscillation (AMO) and El Nino Southern Oscillation (ENSO) datasets, the NOAA National Weather Service, Climate Prediction Center for providing the North Atlantic Oscillation (NAO) dataset, the Copernicus Climate Change Services (C3S) and European Center for Medium-Range Weather forecasts of the European Union for providing the fifth generation of the ECMWF reanalysis for the global climate and weather, the “ERA5 monthly averaged data on single levels from 1940 to the present”.

All the datasets used in this study were processed. The authorities and organisations mentioned in the previous paragraph are not responsible for any results presented in this study.

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The low efficiency of the Fall and early Winter cooling does not balance the overall Sea Surface Temperature warming in the Mediterranean Cilician Basin

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Abstract

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1. Introduction

2. Data and Methods

3. Results

4. Discussion

5. Conclusion

Declarations

References

Additional Declarations

Status:

Version 1