Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind
El Nino Southern Oscillation (ENSO) is an irregular climate oscillation induced by sea surface temperature anomalies (SSTA) in the Equatorial Pacific Ocean. An anomalous warming in this area is known as El Nino, while an anomalous cooling bears the name of La Nina. The objectives of this study are ...
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| Format: | Article |
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MO.RI Publishing
2022-12-01
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| Series: | Indonesian Journal of Earth Sciences |
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| Online Access: | http://journal.moripublishing.com/index.php/injoes/article/view/428 |
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| author | Jen-Yang Lin Ming-Chung Tang Febrianto Wijaya |
| author_facet | Jen-Yang Lin Ming-Chung Tang Febrianto Wijaya |
| author_sort | Jen-Yang Lin |
| collection | DOAJ |
| description |
El Nino Southern Oscillation (ENSO) is an irregular climate oscillation induced by sea surface temperature anomalies (SSTA) in the Equatorial Pacific Ocean. An anomalous warming in this area is known as El Nino, while an anomalous cooling bears the name of La Nina. The objectives of this study are to: reproduce Oceanic Nino Index (ONI) based on MW OISST; produce Nino Region 3.4 wind and Sea Surface High (SSH); analyze the correlation between SST and Wind & SSH; discuss Typhoon Soudelor based on SST, Wind, and SSH; and analyze the correlation of El Nino and Precipitation in specific area. MWOI-SST was used to produce monthly mean SST over Nino 3.4 region from January 1998 – May 2020. Monthly wind data was obtained from QuickScat. Daily Sea Surface High (SSH) was obtained from Copernicus Marine Environment Monitoring Service (CMEMS). Daily precipitation from TRMM 3B42 over Bandung City (Indonesia) was used to assess the correlation between El Nino and precipitation in specific area. The results show that in Nino 3.4 region, 2015 is the hottest year during 1998-2020 period with average SST of 28.5oC, and 1999 is the coldest year with average SST of 25.7oC. The result shows that the MWOI-SST Ocean Nino Index has very strong correlation with ERSST.v5 with coefficient of correlation is 0.92 and RMSE is 0.36oC. the wind speed of Nino 3.4 region is range from 5.23 m/s to 7.97 m/s. Unlike Sea Surface Temperature (SST), annual average wind speed is more stable with monthly variation. The wind speed is observed high in the beginning and the end of years. Sea Surface Height (SSH) over Nino 3.4 region varied from 65.8 cm to 106.8 cm. 2015 is the highest SSH with annual average of 96 cm, whereas 1999 is the lowest SSH with annual average of 71.4 cm. It is observed that Sea Surface Temperature (SST) has negative correlation with wind speed with coefficient of correlation of 0.28. Conversely, Sea Surface Temperature (SST) over Nino 3.4 region has positive correlation with Sea Surface High (SSH) with coefficient of correlation of 0.30. which mean the higher temperature, the higher Sea Surface Height. During the passage of Typhoon Soudelor, there is evident cool trail along its track with rightward bias. We can assume that the decreasing precipitation in Bandung City might be affected by strong El Nino occurrence in 2015.
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| first_indexed | 2024-04-11T04:42:17Z |
| format | Article |
| id | doaj.art-5981a782f6f04218a4393f720e4e64f5 |
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| issn | 2798-1134 2797-3549 |
| language | English |
| last_indexed | 2024-04-11T04:42:17Z |
| publishDate | 2022-12-01 |
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| spelling | doaj.art-5981a782f6f04218a4393f720e4e64f52022-12-27T21:01:39ZengMO.RI PublishingIndonesian Journal of Earth Sciences2798-11342797-35492022-12-012210.52562/injoes.v2i2.428Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and WindJen-Yang Lin0Ming-Chung Tang1Febrianto Wijaya2Department of Oceanography, National Sun Yat-sen University, TaiwanDepartment of Marine Environmental Informatics, National Taiwan Ocean University, TaiwanGraduate Institute of Hydrological & Oceanic Sciences, National central University, Taiwan El Nino Southern Oscillation (ENSO) is an irregular climate oscillation induced by sea surface temperature anomalies (SSTA) in the Equatorial Pacific Ocean. An anomalous warming in this area is known as El Nino, while an anomalous cooling bears the name of La Nina. The objectives of this study are to: reproduce Oceanic Nino Index (ONI) based on MW OISST; produce Nino Region 3.4 wind and Sea Surface High (SSH); analyze the correlation between SST and Wind & SSH; discuss Typhoon Soudelor based on SST, Wind, and SSH; and analyze the correlation of El Nino and Precipitation in specific area. MWOI-SST was used to produce monthly mean SST over Nino 3.4 region from January 1998 – May 2020. Monthly wind data was obtained from QuickScat. Daily Sea Surface High (SSH) was obtained from Copernicus Marine Environment Monitoring Service (CMEMS). Daily precipitation from TRMM 3B42 over Bandung City (Indonesia) was used to assess the correlation between El Nino and precipitation in specific area. The results show that in Nino 3.4 region, 2015 is the hottest year during 1998-2020 period with average SST of 28.5oC, and 1999 is the coldest year with average SST of 25.7oC. The result shows that the MWOI-SST Ocean Nino Index has very strong correlation with ERSST.v5 with coefficient of correlation is 0.92 and RMSE is 0.36oC. the wind speed of Nino 3.4 region is range from 5.23 m/s to 7.97 m/s. Unlike Sea Surface Temperature (SST), annual average wind speed is more stable with monthly variation. The wind speed is observed high in the beginning and the end of years. Sea Surface Height (SSH) over Nino 3.4 region varied from 65.8 cm to 106.8 cm. 2015 is the highest SSH with annual average of 96 cm, whereas 1999 is the lowest SSH with annual average of 71.4 cm. It is observed that Sea Surface Temperature (SST) has negative correlation with wind speed with coefficient of correlation of 0.28. Conversely, Sea Surface Temperature (SST) over Nino 3.4 region has positive correlation with Sea Surface High (SSH) with coefficient of correlation of 0.30. which mean the higher temperature, the higher Sea Surface Height. During the passage of Typhoon Soudelor, there is evident cool trail along its track with rightward bias. We can assume that the decreasing precipitation in Bandung City might be affected by strong El Nino occurrence in 2015. http://journal.moripublishing.com/index.php/injoes/article/view/428ENSONino 3.4SSTSSHWind |
| spellingShingle | Jen-Yang Lin Ming-Chung Tang Febrianto Wijaya Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind Indonesian Journal of Earth Sciences ENSO Nino 3.4 SST SSH Wind |
| title | Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind |
| title_full | Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind |
| title_fullStr | Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind |
| title_full_unstemmed | Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind |
| title_short | Satellite Oceanographic Data Processing and Analysis: Correlation Between Nino 3.4 Sea Surface Temperature & Sea Surface High and Wind |
| title_sort | satellite oceanographic data processing and analysis correlation between nino 3 4 sea surface temperature sea surface high and wind |
| topic | ENSO Nino 3.4 SST SSH Wind |
| url | http://journal.moripublishing.com/index.php/injoes/article/view/428 |
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