scholarly journals THE CHARACTERISTIC AND VARIABILITY OF SEA SURFACE TEMPERATURE IN JAVA SEA

2010 ◽  
Vol 4 (1) ◽  
Author(s):  
Widada Sulistya ◽  
Agus Hartoko ◽  
S.Budi Prayitno
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Water ◽  
Temporal Analysis ◽  
Sea Surface ◽  
Fishing Ground ◽  
Sst Variability ◽  
Java Sea ◽  
Spatio Temporal ◽  
Marine Climate

The phenomena of marine climate can be identified by the sea surface temperature, as Illahude (1999) reported that one of the parameters of oceanography which characterized of sea water mass is sea surface temperature (SST). The distribution of sea surface temperature can be used as an indicator of fishing ground. However, as understanding of marine climate variability it does not well enough (Hartoko,2000). The characteristic and variability of ST in Java Sea are not sufficiently enough understood. In order to better understand, we need the Spatial-Temporal Analysis of SST. The Spectral Analysis Method is used to study the characteristic and seasonal variation of SST, while GIS Analysis is used to study SST spatial distribution pattern. Temporally, the highest temperature at Java Sea occurs in April-May and November, whereas the lowest temperature in February and August. The SST fluctuation of Java Sea ranges from 27.48 degree of celcius to 29.66 degree of celcius and its periodic cycle generally occurs for 6 months, 1 year and 8 years. Keyword: SST, Variability, Spatio-Temporal Analysis

scholarly journals Sea Surface Temperature Variability and Marine Heat Waves over the Aegean, Ionian, and Cretan Seas from 2008–2021

2022 ◽  
Vol 10 (1) ◽  
pp. 42
Author(s):  
Yannis S. Androulidakis ◽  
Yannis N. Krestenitis
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Water ◽  
Heat Waves ◽  
Hot Spot ◽  
Sea Surface ◽  
The Black Sea ◽  
Sst Variability ◽  
Eastern Aegean ◽  
Increasing Trends

The sea surface temperature (SST) is an important factor and indicator of the sea water quality, with various ecological and anthropogenic implications. We used high-resolution satellite-derived SST data, in tandem with field observations and long-term meteorological data, to investigate the spatial and interannual SST variability over the Aegean, Ionian, and Cretan (AIC) Seas during the recent 14-year period (2008–2021). Increasing trends were identified for most of the sub-basins of the AIC Seas. The numbers and durations (days) of the marine heat waves (MHWs) have significantly increased, especially during the last quadrennial period (2018–2021). Changes have been detected in both the maximum and minimum values; however, the trend of the mean annual values is mainly associated with the interannual increases in the lowest values (weaker minima during the cold seasons). The interannual variability and the increasing positive trends of the air temperature are very similar to the SST variations, showing a 5-to-10-day lag between the seasonal time series of the two parameters for all regions; however, extreme atmospheric events (e.g., cold fronts or heat waves) have a more direct impact on the SST variability (zero lag). MHWs were more frequent over the northern Aegean Sea, especially in Thermaikos Gulf, which is characterized as a “hot spot” for MHWs. MHWs were rarer over the southern regions, especially over the southeastern Aegean and Cretan Seas. A stratified upper ocean, controlled by buoyant brackish plumes, such as the Black Sea Waters (BSW) in the northern Aegean, may increase the heat storage capacity of the surface water masses, contributing to the further warming of the ocean. This was the case in the summer of 2021, which was a unique year for the AIC Seas, and especially for the northern Aegean, which revealed the highest SST values among all the study years. The satellite-derived observations of the 2008–2021 period showed increasing trends for all coastal waters, strong trend slopes for most of the coasts of the northern Aegean and central Ionian Seas, and milder trend slopes in the eastern Aegean.

scholarly journals ANALISIS SPASIAL DAN TEMPORAL AKTIVITAS KAPAL IKAN DI PERAIRAN SELATAN ARU MENGGUNAKAN CITRA MODIS DAN RADARSAT-2

2016 ◽  
Vol 9 (2) ◽  
pp. 155
Author(s):  
Dendy Mahabror ◽  
Abdul Rohman Zaky
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Temporal Analysis ◽  
Sea Surface ◽  
Fishing Ground ◽  
The West ◽  
Chlorophyll A Concentration ◽  
Fishing Vessels ◽  
Spatial And Temporal Analysis

<p class="ColorfulList-Accent11CxSpFirst"><em>Perairan selatan Aru merupakan daerah penangkapan  ikan yang potensial dengan sumberdaya ikannya yang berlimpah. Kapal-kapal ikan melakukan penangkapan ikan dengan mempertimbangkan kondisi kesuburan perairan yaitu fenomena upwelling melalui parameter suhu permukaan laut dan kelimpahan konsentrasi klorofil-a. Penggunaan citra MODIS secara periodik dapat menggambarkan waktu dan lokasi upwelling. Variabilitas suhu permukaan laut dan konsentrasi klorofil-a di lintang 7 LS dan 7.5 LS, bujur 133.1 – 136 BT menunjukkan fenomena upwelling pada musim Timur dimana suhu permukaan laut menurun hingga 24 <sup>o</sup>C sedangkan konsentrasi klorofil-a rata-rata meningkat hingga 3.61 mg/m<sup>3</sup>. Fenomena downwelling terjadi di musim Barat dimana suhu permukaan laut di lintang yang sama menjadi hangat berkisar 30<sup> o</sup>C dengan konsentrasi rata-rata klorofil-a &lt;1 mg/m<sup>3</sup>. Jumlah kapal ikan yang beroperasi di daerah penangkapan diketahui dengan menggunakan citra Radarsat-2 dan data VMS yang disesuaikan dengan waktu pengambilan citra di setiap bulannya dengan lokasi yang sama. Analisis spasial dan temporal dilakukan untuk mengetahui sebaran kapal ikan pada musim timur saat kesuburan perairan tinggi dimana konsentrasi klorofil-a di titik penangkapan mencapai 5.01 mg/m<sup>3</sup> dan jumlah kapal ikan yang beroperasi &gt;150 unit/hari. Pada musim Barat kesuburan perairan rendah dimana konsentrasi klorofil-a di titik penangkapan &lt;1 mg/m<sup>3 </sup>dan jumlah kapal ikan yang beroperasi &lt;40 unit/hari.</em></p><p class="ColorfulList-Accent11CxSpMiddle"> </p><p class="ColorfulList-Accent11CxSpMiddle"><strong>KATA KUNCI</strong></p><p class="ColorfulList-Accent11CxSpLast">klorofil-a, Modis, perairan selatan Aru, Radarsat-2, suhu permukaan laut.</p><p class="ColorfulList-Accent11CxSpLast"> </p><p align="center"><strong><em>SPATIAL AND TEMPORAL ANALYSIS OF WATER PRODUCTIVITY AFFECTING ACTIVITIES IN FISHING VESSEL AT SOUTH ARU FISHING GROUND USING MODIS IMAGE AND RADARSAT-2</em></strong><strong><em></em></strong></p><p class="ColorfulList-Accent11CxSpFirst"><em>Southern Aru waters is a potential fishing areas with abundant fish resources. Fishing boats catch fish by considering the condition of the waters productivity such as upwelling phenomenon through the parameters of sea surface temperatures and an abundance of chlorophyll-a concentration. The use of MODIS imagery can periodically describe the timing and location of upwelling. Variability of sea surface temperature and chlorophyll-a concentration in latitude 7 LS and 7.5 LS, longitude 133.1 - 136 BT showed the phenomenon of upwelling in the east season where sea surface temperature decreased from 30° C to 24° C while the chlorophyll-a concentration increased by an average of 0,3 mg/m<sup>3</sup> to 3.61 mg/m<sup>3</sup>. Downwelling phenomenon took place in the west season where the sea surface temperature in the same latitude range 30° C to be warm with an average concentration of chlorophyll-a &lt;1 mg/m<sup>3</sup>. The number of fishing vessels operating in the fishing area known using RADARSAT-2 imagery and data VMS were later adapted to capture images of each month at the same location. Based on the spatial and temporal analysis was conducted to determine the distribution of fishing vessels in the eastern summer time high waters productivity where the concentration of chlorophyll-a at the point reached 5:01 mg m<sup>3</sup>, the number of fishing vessels in operation increased to 150 units/ ay. While in the West season low waters productivity where the concentration of chlorophyll-a at the point of &lt;1 mg/m<sup>3</sup> and the number of ships in operation decreased to below 40 units/day. This suggests that the increase in the number of fishing fleets affected by the level of waters productivity or fishing season in the East to Transition II at the southern Aru Islands waters.</em></p><p class="ColorfulList-Accent11CxSpMiddle"><em> </em></p><p class="ColorfulList-Accent11CxSpLast"><strong>Keywords: </strong><em>Chlorophyll-a, Modis, the south of Aru, RADARSAT-2, Sea surface temperature.</em></p>

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 Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Spatio Temporal ◽  
Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

scholarly journals On the Interpretation of the North Atlantic Averaged Sea Surface Temperature

2020 ◽  
Vol 33 (14) ◽  
pp. 6025-6045
Author(s):  
Jing Sun ◽  
Mojib Latif ◽  
Wonsun Park ◽  
Taewook Park
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Climate Models ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
The North ◽  
Sst Variability ◽  
The North Atlantic ◽  
Different Time Scales

AbstractThe North Atlantic (NA) basin-averaged sea surface temperature (NASST) is often used as an index to study climate variability in the NA sector. However, there is still some debate on what drives it. Based on observations and climate models, an analysis of the different influences on the NASST index and its low-pass filtered version, the Atlantic multidecadal oscillation (AMO) index, is provided. In particular, the relationships of the two indices with some of its mechanistic drivers including the Atlantic meridional overturning circulation (AMOC) are investigated. In observations, the NASST index accounts for significant SST variability over the tropical and subpolar NA. The NASST index is shown to lump together SST variability originating from different mechanisms operating on different time scales. The AMO index emphasizes the subpolar SST variability. In the climate models, the SST-anomaly pattern associated with the NASST index is similar. The AMO index, however, only represents pronounced SST variability over the extratropical NA, and this variability is significantly linked to the AMOC. There is a sensitivity of this linkage to the cold NA SST bias observed in many climate models. Models suffering from a large cold bias exhibit a relatively weak linkage between the AMOC and AMO and vice versa. Finally, the basin-averaged SST in its unfiltered form, which has been used to question a strong influence of ocean dynamics on NA SST variability, mixes together multiple types of variability occurring on different time scales and therefore underemphasizes the role of ocean dynamics in the multidecadal variability of NA SSTs.

scholarly journals Centennial-Scale Sea Surface Temperature Analysis and Its Uncertainty

2014 ◽  
Vol 27 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Shoji Hirahara ◽  
Masayoshi Ishii ◽  
Yoshikazu Fukuda
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Specific Area ◽  
Sea Surface ◽  
Sampling Errors ◽  
Sea Ice Concentration ◽  
Sst Variability ◽  
Analysis Errors ◽  
Global Mean

Abstract A new sea surface temperature (SST) analysis on a centennial time scale is presented. In this analysis, a daily SST field is constructed as a sum of a trend, interannual variations, and daily changes, using in situ SST and sea ice concentration observations. All SST values are accompanied with theory-based analysis errors as a measure of reliability. An improved equation is introduced to represent the ice–SST relationship, which is used to produce SST data from observed sea ice concentrations. Prior to the analysis, biases of individual SST measurement types are estimated for a homogenized long-term time series of global mean SST. Because metadata necessary for the bias correction are unavailable for many historical observational reports, the biases are determined so as to ensure consistency among existing SST and nighttime air temperature observations. The global mean SSTs with bias-corrected observations are in agreement with those of a previously published study, which adopted a different approach. Satellite observations are newly introduced for the purpose of reconstruction of SST variability over data-sparse regions. Moreover, uncertainty in areal means of the present and previous SST analyses is investigated using the theoretical analysis errors and estimated sampling errors. The result confirms the advantages of the present analysis, and it is helpful in understanding the reliability of SST for a specific area and time period.

scholarly journals Intraseasonal Sea Surface Temperature Variability across the Indonesian Seas*

2015 ◽  
Vol 28 (22) ◽  
pp. 8710-8727 ◽  
Author(s):  
Asmi M. Napitu ◽  
Arnold L. Gordon ◽  
Kandaga Pujiana
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Intraseasonal Variability ◽  
Longwave Radiation ◽  
Active Phase ◽  
Ocean Model ◽  
Sea Surface ◽  
Indonesian Seas ◽  
Sst Variability ◽  
Slab Ocean

Abstract Sea surface temperature (SST) variability at intraseasonal time scales across the Indonesian Seas during January 1998–mid-2012 is examined. The intraseasonal variability is most energetic in the Banda and Timor Seas, with a standard deviation of 0.4°–0.5°C, representing 55%–60% of total nonseasonal SST variance. A slab ocean model demonstrates that intraseasonal air–sea heat flux variability, largely attributed to the Madden–Julian oscillation (MJO), accounts for 69%–78% intraseasonal SST variability in the Banda and Timor Seas. While the slab ocean model accurately reproduces the observed intraseasonal SST variations during the northern winter months, it underestimates the summer variability. The authors posit that this is a consequence of a more vigorous cooling effect induced by ocean processes during the summer. Two strong MJO cycles occurred in late 2007–early 2008, and their imprints were clearly evident in the SST of the Banda and Timor Seas. The passive phase of the MJO [enhanced outgoing longwave radiation (OLR) and weak zonal wind stress) projects on SST as a warming period, while the active phase (suppressed OLR and westerly wind bursts) projects on SST as a cooling phase. SST also displays significant intraseasonal variations in the Sulawesi Sea, but these differ in characteristics from those of the Banda and Timor Seas and are attributed to ocean eddies and atmospheric processes independent from the MJO.

Sign in / Sign up

Export Citation Format

Share Document