scholarly journals Analisis Spasial dan Temporal Sebaran Suhu Permukaan Laut di Perairan Sumatera Barat

2017 ◽  
Vol 4 (1) ◽  
pp. 65
Author(s):  
Alfajri Alfajri ◽  
Mubarak Mubarak ◽  
Aras Mulyadi
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temperature Fluctuation ◽  
Water Mass ◽  
El Nino ◽  
Sea Surface ◽  
Temperature Influence ◽  
Daily Data ◽  
West Sumatra ◽  
Sunlight Intensity

This study was conducted on March-April 2016 in West Sumatra Waters. This study aimed to know distribution and sea surface temperature fluctuation daily and monthly in West Sumatra Waters and to know the factor that influences distribution and fluctuation of sea surface temperature in West Sumatra Waters. Sea surface temperature has taken from 3 stations which: Pariaman Waters, Padang-Pariaman Regency Waters and Bungus Waters, Padang. The result of daily data sea surface temperature by Aqua-Modis from 15 February, 20 February, 25 February, 2 March, 7 March and 12 March 2016 On West Sumatra Waters showed that the highest sea surface temperature was 34,54°C occured on 15 February and the lowest was 27,41°C on 12 March 2016. Average of monthly sea surface temperature on April 2015-March 2016 was about 27,07-34,98°C. The highest sea surface temperature occured on February and March 2016 and the lowest occurred on April and October 2015. Based on observation of monthly sea surface temperature knowed that sea surface temperature on western season increased and sea surface temperature and eastern season decreased. Observation showed that sea surface temperature influence by water mass moved because muson wind. Water mass moved impact to distribution of sea surface temperature on waters. The high or low of sea surface temperature in waters estimated because of sunlight intensity and rain on waters. As high the sunlight intensity to the waters so sea surface temperature on waters will increased and as high the rain so the sea surface temperature will decreased. El Nino phenomenon that occurred on February and March 2016 because sea surface temperature on that month was increased.

Humboldt penguins outmanoeuvring El Nino

2000 ◽  
Vol 203 (15) ◽  
pp. 2311-2322 ◽  
Author(s):  
B. Culik ◽  
J. Hennicke ◽  
T. Martin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Wind Direction ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Dive Duration ◽  
Sea Surface ◽  
Day Length

We satellite-tracked five Humboldt penguins during the strong 1997/98 El Nino Southern Oscillation (ENSO) from their breeding island Pan de Azucar (26 degrees 09′S, 70 degrees 40′W) in Northern Chile and related their activities at sea to satellite-derived information on sea surface temperature (SST), sea surface temperature anomaly (SSTA), wind direction and speed, chlorophyll a concentrations and statistical data on fishery landings. We found that Humboldt penguins migrated by up to 895 km as marine productivity decreased. The total daily dive duration was highly correlated with SSTA, ranging from 3.1 to 12.5 h when the water was at its warmest (+4 degrees C). Birds travelled between 2 and 116 km every day, travelling further when SSTA was highest. Diving depths (maximum 54 m), however, were not increased with respect to previous years. Two penguins migrated south and, independently of each other, located an area of high chlorophyll a concentration 150 km off the coast. Humboldt penguins seem to use day length, temperature gradients, wind direction and olfaction to adapt to changing environmental conditions and to find suitable feeding grounds. This makes Humboldt penguins biological in situ detectors of highly productive marine areas, with a potential use in the verification of trends detected by remote sensors on board satellites.

scholarly journals Seasonal Covariability of Dryness or Wetness in China and Global Sea Surface Temperature

2020 ◽  
Vol 33 (2) ◽  
pp. 727-747
Author(s):  
Chunxiang Li ◽  
Chunzai Wang ◽  
Tianbao Zhao
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Sea Surface ◽  
Interdecadal Variability ◽  
Coupled Modes ◽  
Indian Ocean Basin Mode ◽  
Global Sea Surface Temperature

AbstractSeasonal covariability of the dryness/wetness in China and global sea surface temperature (SST) is investigated by using the monthly self-calibrated Palmer drought severity index (PDSI) data and other data from 1950 to 2014. The singular value decomposition (SVD) analysis shows two recurring PDSI–SST coupled modes. The first SVD mode of PDSI is associated with the warm phases of the eastern Pacific–type El Niño–Southern Oscillation (ENSO), the interdecadal Pacific oscillation (IPO) or Pacific decadal oscillation (PDO), the Indian Ocean basin mode (IOBM) in the autumn and winter, and the cold phase of the IOBM in the spring. Meanwhile, the Atlantic multidecadal oscillation (AMO) pattern appears in every season except the autumn. The second SVD mode of PDSI is accompanied by a central Pacific–type El Niño developing from the winter to autumn over the tropical Pacific and a positive phase of IPO or PDO from the winter to summer. Moreover, an AMO pattern is observed in all seasons except the summer, whereas the SST over the tropical Indian Ocean shows negligible variations. The further analyses suggest that AMO remote forcing may be a primary factor influencing interdecadal variability of PDSI in China, and interannual to interdecadal variability of PDSI seems to be closely associated with the ENSO-related events. Meanwhile, the IOBM may be a crucial factor in interannual variability of PDSI during its mature phase in the spring. In general, the SST-related dryness/wetness anomalies can be explained by the associated atmospheric circulation changes.

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