博碩士論文 109022602 詳細資訊




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姓名 席曼朱(Febryanto Simanjuntak)  查詢紙本館藏   畢業系所 遙測科技碩士學位學程
論文名稱 衛星觀測季風對海表溫度、葉綠素 a 和 Ekman 動力學變異的影響及其與 IOD 和 ENSO之相關分析-小巽他群島南部海岸
(The effects of Monsoon on Sea Surface Temperature, Chlorophyll-a, and Ekman dynamics variability and its connection to IOD and ENSO based on satellite observations off the southern coast of Lesser Sunda Islands)
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摘要(中) 印度尼西亞海域的海表面參數受到亞洲-澳大利亞季風 (Asian-Australian Monsoon, AAM) 風、印度洋偶極子 (Indian Ocean Dipole, IOD) 和厄爾尼諾-南方濤動 (El Nino-Southern Oscillation, ENSO) 的強烈影響,特別是在小巽他群島 (Lesser Sunda Islands, LSI) 南部海岸。本研究因此應用衛星觀測資料檢驗AAM 風對海洋表面參數變化的效應,以及AAM對 IOD 和 ENSO 的影響。此外,本文還定義埃克曼動力學的空間和時間變化,包括埃克曼質量傳遞 (Ekman Mass Transport, EMT) 和埃克曼泵送速度 (Ekman Pumping Velocity, EPV),以及海面溫度 (sea surface temperature, SST) 與風之間的關聯。基於衛星觀測資料、現地量測數據和再分析數解析LSI中湧升流的有利特徵。分析結果顯示,2009年厄爾尼諾(El Nino)期間葉綠素-a(-0.5 mg m-3)和SST(+1.5°C)有明顯的異相變化情形,這與負風應力和EMT異常相吻合;相反地,在 2007 年拉尼娜(La Nina)期間則有SST (-0.5 °C) 和葉綠素-a (+0.5 mg m−3) 的異相變化。根據 浮標(Argo float) 的觀測數據,東南季風季節的混合層深度較西北季風季節期間淺。同時再分析數據也顯示爪哇島南部海岸的上升流強度明顯高於其他週邊區域。此外,本研究亦發現 LSI 南部海岸的四個不同區域具有獨特的生成機制,可調節這四個領域內的 SST 差異。
摘要(英) Indonesian seas are significantly affected by the Asian-Australian Monsoon (AAM) winds, the Indian Ocean Dipole (IOD), and the El Nino-Southern Oscillation (ENSO), particularly along the southern coast of Lesser Sunda Islands (LSI). This study investigates the impact of the AAM winds on ocean surface conditions and elucidates the influence of IOD and ENSO within the LSI. In addition, the spatial and temporal variability of Ekman dynamics, which includes of Ekman Mass Transport (EMT) and Ekman Pumping Velocity (EPV), will also be defined, as well as the association between sea surface temperature (SST) and wind in the LSI. Remotely sensed data, in-situ observation data, and reanalysis data are used to understand the favorable features for upwelling in the LSI. The results indicate that negative chlorophyll-a (-0.5 mg m-3) and positive SST (1.5°C) anomalies occurred during the 2009 El Nino, which coincides with negative wind stress and EMT anomalies. Conversely, negative SST (-0.5 °C) and positive chlorophyll-a (0.5 mg m−3) anomalies occurred during the 2007 La Nina. Based on the Argo float data, the mixed layer depth during the southeast monsoon season is shallower than during the northwest monsoon season. Furthermore, according to the reanalysis data, the author found that the upwelling strength in the southern coast of Java (Box 1) is stronger than in Boxes 2, 3, and 4. Additionally, the author found that four different regions in the southern coast of LSI have a distinctive generated mechanism that regulates SST variance within these four areas.
關鍵字(中) ★ ENSO
★ IOD
★ 上升流
★ 埃克曼動力學
關鍵字(英) ★ ENSO
★ IOD
★ upwelling
★ Ekman dynamics
論文目次 摘要 i
Abstract ii
Acknowledgement iii
Table of Contents iv
List of Figures vi
List of Tables vii
CHAPTER I INTRODUCTION 1
1.1. Background 1
1.2. Research Problem and Objective 2
1.3. Thesis Outline 4
CHAPTER II LITERATURE REVIEW 5
2.1 Upwelling 5
2.2. Chlorophyll-a (chl-a) 6
2.2.1 Definition and the importance of chl-a 6
2.2.2 The Aqua MODIS chl-a product 7
2.3 Sea Surface Temperature (SST) 7
2.3.1 Remote sensing of SST 7
2.3.2 The Aqua MODIS SST product 9
2.4 Wind 10
2.4.1 The influence of the wind on the ocean 10
2.4.2 Copernicus Marine Service wind product 12
2.5 El Nino Southern Oscillation (ENSO) 13
2.6 Indian Ocean Dipole (IOD) 15
CHAPTER III Study Area and Methods 16
3.1. Study Area 16
3.2. Dataset 17
3.3. Methods 18
3.3.1 Workflow 18
3.3.2 Wind stress, EMT, and EPV calculation 19
3.3.3 ONI and DMI 20
3.3.4 Reanalysis data processing 21
3.3.5 Relationship between SST, Ekman dynamics, and IOD and ENSO 22
CHAPTER IV Results and Discussion 24
4.1. Result 24
4.1.1 Spatio-temporal variation of chl-a 24
4.1.2 Spatio-temporal variation of SST 25
4.1.3 Spatio-temporal variation of wind stress 26
4.1.4 The four distinct area with different relationship between SST and wind 27
4.1.5 Spatio-temporal variation of EMT 28
4.1.6 Spatio-temporal variation of EPV 29
4.1.7 The effect of the 2009 El Nino and 2007 La Nina 34
4.1.8 The effect of the 2008 positive IOD and 2016 negative IOD 36
4.1.9 The effect of the 2015 positive IOD coincides with El Nino and 2010 negative IOD coincides with La Nina 38
4.1.10 The variation of mixed layer depth 40
4.2. Discussion 42
CHAPTER V Conclusions 44
References 46
參考文獻 [1] McGregor, H.V.; Dima, M.; Fischer, H.W.; Mulitza, S. Rapid 20th-century increase in coastal upwelling off Northwest Africa. Science 2007, 315, 637–639.
[2] Baars, M. A; A. B. Sutomo; S. S. Oostherhuis; and O. H. Arinardi. 1990. "Zooplankton Abundance in the Eastern Banda Sea and Northern Arafura during and after the Upwelling Session August 1984 and February 1985." Netherland Journal of Sea. Research 25 (4): 527-543.
[3] Sachoemar, S.I.; Yanagi, T.; Hendiarti, N.; Sadly, M.; Meliani, F. Seasonal Variability of Sea Surface Cholophyll-a and Abundance of Pelagic Fish in Lampung Bay, Southern Coastal Area of Sumatra, Indonesia. Coast. Mar. Sci. 2010, 34, 82–90.
[4] Purba; Noir P.; and Alexander M. A. Khan. “Upwelling session in Indonesia waters.” (2019). World News of Natural Sciences, 25, 72-83.
[5] Wyrtki, K. Physical oceanography of the southeast asian waters. Scientific results of marine investigation of the south China sea and the gulf of Thailand 1959–1961. Phys. Oceanogr. Southeast Asian Waters Naga Rep. 1961, 2, 195.
[6] Pramuwardani, I.; Sopaheluwakan, A. Indonesian rainfall variability during Western North Pacific and Australian monsoon phase related to convectively coupled equatorial waves. Arab. J. Geosci. 2018, 11, 673.
[7] Griffiths, M.L.; Drysdale, R.N.; Gagan, M.K.; Zhao, J.-X.; Ayliffe, L.K.; Hellstrom, J.C.; Hantoro, W.S.; Frisia, S.; Feng, Y.-X.; Cartwright, I.; et al. Increasing Australian-Indonesian Monsoon Rainfall Linked to Early Holocene Sea-level Rise. Nat. Geosci. 2009, 2, 636–639.
[8] Jin, F.-F. An equatorial ocean recharge paradigm for ENSO. Part I Concept. Model J. Atmos. Sci. 1997, 54, 811–829.
[9] Lau, N.-C.; Nath, M.J. The role of the “atmospheric bridge” in linking tropical Pacific ENSO events to extratropical SST anomalies. J. Clim. 1996, 9, 2036–2057.
[10] Trenberth, K.E.; Branstator, G.W.; Karoly, D.; Kumar, A.; Lau, N.-C.; Ropelewski, C. Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res. 1998, 103, 14291–14324.
[11] Wei, X.; Liao, X.; Zhan, H.; Liu, H. Estimates of potential new production in the Java-Sumatra upwelling system. Chin. J. Oceanol. Limnol. 2012, 30, 1063–1067.
[12] Lumban-Gaol, J.; Leben, R.R.; Vignudelli, S.; Mahapatra, K.; Okada, Y.; Nababan, B.; Mei-Ling, M.; Amri, K.; Arhatin, R.E.; Syahdan, M. Variability of satellite-derived sea surface height anomaly, and its relationship with Bigeye tuna (Thunnus obesus) catch in the Eastern Indian Ocean. Eur. J. Remote Sens. 2015, 48, 465–477.
[13] Hood, R.R.; Beckley, L.E.; Wiggert, J.D. Biogeochemical and ecological impacts of boundary currents in the Indian Ocean. Prog. Oceanogr. 2017, 156, 290–325.
[14] Ningsih, N.S.; Rakhmaputeri, N.; Harto, A.B. Upwelling Variability along the Southern Coast of Bali and in Nusa Tenggara. Ocean Sci. J. 2013, 48, 49–57.
[15] Susanto, R.D.; Gordon, A.L.; Zheng, Q. Upwelling along the coasts of Java and Sumatra and its relation to ENSO. Geophys. Res. Lett. 2001, 28, 1599–1602.
[16] Setiawan, R.Y.; Wirasatriya, A.; Hernawan, U.; Leung, S.; Iskandar, I. Spatio-temporal variability of surface chlorophyll-a in the Halmahera Sea and its relation to ENSO and the Indian Ocean Dipole. International Journal of Remote Sensing 2020, 41:1, 284-299. https://doi.org/10.1080/01431161.2019.1641244.
[17] Wirasatriya, A.; Setiawan, R.Y.; Subardjo, P. The Effect of ENSO on the Variability of Chlorophyll-a and Sea Surface Temperature in the Maluku Sea. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2017, 10, 5513–5518.
[18] Setiawan, R.Y.; Setyobudi, E.; Wirasatriya, A.; Muttaqin, A.S.; Maslukah, L. The Influence of Seasonal and Interannual Variability on Surface Chlorophyll-a Off the Western Lesser Sunda Islands. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2019, Volume 12, no. 11, pp. 4191-4197. https://doi.org/10.1109/JSTARS.2019.2948385.
[19] Chen, G.; Han, W.; Li, Y.; Wang, D. Interannual Variability of Equatorial Eastern Indian Ocean Upwelling: Local versus Remote Forcing. J. Phys. Oceanogr. 2016, 46, 789–807.
[20] Sari, Q.W.; Utari, P.A.; Setiabudidaya, D.; Yustian, I.; Siswanto, E.; Iskandar, I. Surface chlorophyll-a variations in the Southeastern Tropical Indian Ocean during various types of the positive Indian Ocean Dipole events. Int. J. Remote Sens. 2020, 41, 171–184.
[21] Iskandar, I.; Rao, S.A.; Tozuka, T. Chlorophyll-a Bloom along the Southern Coasts of Java and Sumatra during 2006. Int. J. Remote Sens. 2009, 30, 663–671. https://doi.org/10.1080/01431160802372309.
[22] Veron, J.; Devantier, L.M.; Turak, E.; Green, A.L.; Kininmonth, S.; Stafford-Smith, M.; Peterson, N. Delineating the Coral Triangle. Galaxea J. Coral Reef Stud. 2009, 11, 91–100.
[23] Allen, G.R.; Erdmann, M.V. Reef Fishes of the East Indies. In Tropical Reef Research; Tropical Reef Research: Perth, Australia, 2007; Volume I–III, pp. 1–1260.
[24] Suman, A.; Irianto, H.E.; Satria, F.; Amri, K. Potential and utilization rate of fish resources in the Indonesian state fisheries management area (WPP NKRI) year 2015 as well as its management. Indones. Fish. Policy J. 2016, 8, 97–110.
[25] Oktavia, P.; Salim, W.; Perdanahardja, G. Reinventing papadak/hoholok as a traditional management system of marine resources in Rote Ndao, Indonesia. Ocean Coast Manag. 2018, 161, 37–49.
[26] Hidayat, R.; Zainuddin, M.; Putri, A.R.S. Safruddin, Skipjack tuna (Katsuwonus pelamis) catches in relation to chlorophyll-a front in bone gulf during the southeast monsoon. AACL Bioflux 2019, 12, 209–218.
[27] Syamsuddin, M.; Najamuddin, A.S. Development Analysis of Skipjack Tuna (Katsuwonus pelamis Linneus) Sustainable in Kupang, East Nusa Tenggara Province. Master’s Thesis, Hasanudin University, Makassar, Indonesia, 2009.
[28] Wijaya, A. Oceanographic phenomenon in the Savu sea to determine the potential of high economic pelagic fish resources. Proceed. XVI Annu. Sci. Meet. Indones. Geogr. Assoc. 2013, 1, 253–259.
[29] Anderson, D.M; Prell, W.L (1993). A 300 KYR record of upwelling off Oman during the late quaternary: evidence of the Asian southwest monsoon". Paleoceanography. 8 (2): 193–208. https://doi.org/10.1029/93PA00256.
[30] Sarhan, T; Lafuente, JG; Vargas, M; Vargas, JM; Plaza, F (1999). "Upwelling mechanisms in the northwestern Alboran Sea". Journal of Marine Systems. 23 (4): 317–331. https://doi.org/10.1016/s0924-7963(99)00068-8.
[31] Bakun, A (1990). Global climate change and intensification of coastal ocean upwelling. Science. 247 (4939): 198–201. https://doi.org/10.1126/science.247.4939.198.
[32] Qamal Taufikurahman and Rahmat Hidayat. 2017. IOP Conf. Ser.: Earth Environ. Sci. 54 012075
[33] Setyohadi, D.; Zakiyah, U.; Sambah, A.B.; Wijaya, A. Upwelling Impact on Sardinella lemuru during the Indian Ocean Dipole in the Bali Strait, Indonesia. Fishes 2021, 6, 8. https://doi.org/10.3390/fishes6010008.
[34] Lalli, C.M., Parsons, T.R. (1997) Biological Oceanography: An Introduction. Oxford: Elsevier Publications. ISBN 0-7506-3384-0.
[35] Brodeur, RD; Ware, DM (2007). "Long-term variability in zooplankton biomass in the subarctic Pacific ocean". Fisheries Oceanography. 1 (1): 32–38. https://doi.org/10.1111/j.1365-2419.1992.tb00023.x.
[36] Racault, M.-F.; Sathyendranath, S.; Brewin, R.J.W.; Raitsos, D.E.; Jackson, T.; Platt, T. Impact of El Niño Variability on Oceanic Phytoplankton. Front. Mar. Sci. 2017, 4, 133.
[37] Spyrakos, E.; Vilas, L.G.; Palenzuela, J.M.T.; Barton, E.D. Remote sensing chlorophyll a of optically complex waters (rias Baixas, NW Spain): Application of a regionally specific chlorophyll a algorithm for MERIS full resolution data during an upwelling cycle. Remote Sens. Environ. 2011, 115, 2471–2485.
[38] Nieto, K.; Mélin, F. Variability of chlorophyll-a concentration in the Gulf of Guinea and its relation to physical oceanographic variables. Prog. Oceanogr. 2017, 151, 97–115.
[39] Pinochet, A.; Garcés-Vargas, J.; Lara, C.; Olguin, F. Seasonal Variability of Upwelling off Central-Southern Chile. Remote Sens. 2019, 11, 1737.
[40] Xu, T.; Wei, Z.; Li, S.; Susanto, R.D.; Radiarta, N.; Yuan, C.; Setiawan, A.; Kuswardani, A.; Agustiadi, T.; Trenggono, M. Satellite-Observed Multi-Scale Variability of Sea Surface Chlorophyll-a Concentration along the South Coast of the Sumatra-Java Islands. Remote Sens. 2021, 13, 2817. https://doi.org/10.3390/rs13142817.
[41] O′Reilly, J.E.; Maritorena, S.; Mitchell, B. G.; Siegel, D. A.; Carder, K. L.; Garver, S. A.; Kahru, M.; and McClain, C. R. (1998). Ocean color chlorophyll algorithms for SeaWiFS, Journal of Geophysical Research 103, 24937-24953, https://doi.org/10.1029/98JC02160.
[42] Hu, C.; Lee, Z.; and Franz, B. (2012). Chlorophyll-a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference. Journal of Geophysical Research, 117(C1). https://doi.org/10.1029/2011jc007395.
[43] Zhang, C. Y.; C. M. Hu; S. L. Shang; F. E. Muller-Karger; Y. Li; M. H. Dai; B. Q. Huang; X. R. Ning; and H. S. Hong. 2006. “Bridging between SeaWiFS and MODIS for Continuity of Chlorophyll-a Concentration Assessments off Southeastern China.” Remote Sensing Environment 102: 250–263. https://doi.org/10.1016/j.rse.2006.02.015.
[44] Kahru, M.; Kudela, R.M.; Anderson, C.R.; Manzano-Sarabia, M.; Mitchell, B.G. Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current. Remote Sens. 2014, 6, 8524-8540. https://doi.org/10.3390/rs6098524.
[45] López García; M.J. SST Comparison of AVHRR and MODIS Time Series in the Western Mediterranean Sea. Remote Sens. 2020, 12, 2241. https://doi.org/10.3390/rs12142241.
[46] Donlon, C.J.; The GHRSST Science Team. The Recommended GHRSST-PP Data Processing Specification; Technical Report v1 revision 1.6; GHRSST: Exeter, UK, 2005.
[47] Rayner, N.A.; Brohan, P.; Parker, D.E.; Folland, C.K.; Kenndy, J.J.; Vanicek, M.; Ansell, T.J.; Tett, S.F.B. Improved analysis of changes and uncertainties in sea surface temperature measured in situ since the mid-ninteenth century: The HadSST2 dataset. J. Clim. 2006, 19, 446–469.
[48] Minnett, P.J.; Azcárate, A.A.; Chin, T.M.; Corlett, G.K.; Gentemann, C.L.; Karagali, I.; Li, X.; Marsouin, A.; Marullo, S.; Maturi, E.; et al. Half a century of satellite remote sensing of sea-surface temperature. Remote Sens. Environ. 2019, 233, 111366.
[49] Donlon, C.; Rayner, N.; Robinson, I.; Poulter, D.; Casey, K.; Vazquez-Cuervo, J.; Armstrong, E.; Bingham, A.; Arino, O.; Gentemann, C.; et al. The global ocean data assimilation experiment high-resolution sea surface temperature pilot project. Bull. Am. Meteorol. Soc. 2007, 88, 1197–1213.
[50] Maturi, E.; Harris, A.; Mittaz, J.; Sapper, J.; Wick, G.; Zhu, X.; Dash, P.; Koner, P. A New High-Resolution Sea Surface Temperature Blended Analysis. Bull. Am. Meteorol. Soc. 2017, 98, 1015–1026.
[51] Hosoda, K. A review of satellite-based microwave observations of sea surface temperatures. J. Oceanogr. 2010, 66, 439–473.
[52] Emery, W.J.; Castro, S.; Wick, G.A.; Schlüssel, P.; Donlon, C. Estimating Sea Surface Temperature from Infrared Satellite and In Situ Temperature Data. Bull. Am. Meteorol. Soc. 2001, 82, 2773–2785.
[53] McClain, E.P.; Pichel, W.G.; Walton, C.C. Comparative performance of AVHRR-based multichannel sea surface temperatures. J. Geophys. Res. Space Phys. 1985, 90, 11587.
[54] Casey, K.S.; Brandon, T.B.; Cornillon, P.; Evans, R. The Past, Present, and Future of the AVHRR Pathfinder SST Program. In Oceanography from Space; Springer Science and Business Media LLC: New York, NY, USA, 2010; pp. 273–287.
[55] Minnett, P.; Evans, R.; Kearns, E.; Brown, O. Sea-surface temperature measured by the Moderate Resolution Imaging Spectroradiometer (MODIS). In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toronto, ON, Canada, 24–28 June 2002; Volume 2, pp. 1177–1179.
[56] OBPG. MODIS Terra Level 3 SST Thermal IR Monthly 4km Nighttime v2014.0. Ver. 2014.0. PO.DAAC, CA, USA. 2015. Available online: https://doi.org/10.5067/MODST-MO4N4 (accessed on 25 February 2021).
[57] Barton, I., and A. Pearce. 2006. “Validation of GLI and Other Satellite-Derived Sea Surface Temperatures Using Data from the Rottnest Island Ferry, Western Australia.” Journal of Oceanography 62: 303–310.
[58] Hosoda, K.; H. Murakami; F. Sakaida; and H. Kawamura. 2007. “Algorithm and Validation of Sea Surface Temperature Observation Using MODIS Sensors Abroad Terra and Aqua in the Western North Pacific.” Journal of Oceanography 63: 267–280.
[59] Williams, G. N.; A. I. Dogliotti; P. Zaidman; M. Solis; M. A. Narvarte; R. C. Gonzalez; J. L. Estevez; and D. A. Gagliardini. 2013. “Assessment of Remotely-Sensed Sea-Surface Temperature and Chlorophyll-a Concentration in San Matías Gulf (Patagonia, Argentina). Continental Shelf Research 52: 159–171. doi:10.1016/j.csr.2012.08.014.
[60] Gordon, A.L. Oceanography of the Indonesian seas and their throughflow. Oceanography 2005, 18, 15–27. https://doi.org/10.5670/oceanog.2005.01.
[61] Chang, C.-P.; Wang, Z.; McBride, J.; Liu, C.-H. Annual Cycle of Southeast Asia-Maritime Continent Rainfall and the Asymmetric Monsoon Transition. J. Clim. 2005, 18, 287–301. https://doi.org/10.1175/JCLI-3257.1.
[62] Setiawan, R.Y.; Habibi, A. Satellite detection of summer chlorophyll-a bloom in the gulf of tomini. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens 2011, 4, 944–948. https://doi.org/10.1109/JSTARS.2011.2163926.
[63] Wirasatriya, A.; Setiawan, J.D.; Sugianto, D.N.; Rosyadi, I.A.; Haryadi, H.; Winarso, G.; Setiawan, R.Y.; Susanto, R.D.; Ekman dynamics variability along the southern coast of Java revealed by satellite data. International Journal of Remote Sensing 2020, 41:21, 8475-8496, https://doi.org/10.1080/01431161.2020.1797215.
[64] Utama, F.G.; Atmadipoera, A.S.; Purba, M.; Sudjono, E.H.; Zuraida, R. Analysis of upwelling event in Southern Makassar Strait. IOP Conf. Ser. Earth Environ. Sci. 2017, 54, 12085.
[65] Varella, R.; F. Santos; M. Gómez-Gesteira; I. Álvarez; X. Costoya; and J. M. Días. 2016. “Influence of Coastal Upwelling on SST Trends along the South Coast of Java.” PLoS ONE 11 (9): e0162122.
[66] Kok, P. H.; M. F. M. Mohd Akhir; F. Tangang; and M. L. Husain. 2017. “Spatiotemporal Trends in the Southwest Monsoon Wind-driven Upwelling in the Southwestern Part of the South China Sea.” PLoS ONE 12 (2): e0171979.
[67] Setiawan, R.Y.; Kawamura, H. Summertime Phytoplankton Bloom in the South Sulawesi Sea. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2011, 4, 241–244. https://doi.org/10.1109/JSTARS.2010.2094604.
[68] Setiawan, R. Y.; and H. Kawamura. Satellite Detection of Summer Chlorophyll-a Bloom in the Gulf of Tomini. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2011, Volume 4 (4), 944–948. https://doi.org/10.1109/JSTARS.2011.2163926.
[69] KNMI. Global Ocean Daily Gridded Reprocessed L3 Sea Surface Winds from Scatterometer. CMEMS. 1992. Available online: https://doi.org/10.48670/moi-00183 (accessed on 25 February 2021).
[70] Verhoef, A.; Stoffelen, A. ASCAT Coastal Winds Validation Report”, v1.5, May Technical Note SAF/OSI/CDOP/KNMI/TEC/RP/176; 2013. Available online: http://projects.knmi.nl/scatterometer/publications/pdf/ASCAT_validation_coa.pdf (accessed on 25 February 2021).
[71] Gordon, A.; Fine, R. Pathways of water between the Pacific and Indian oceans in the Indonesian seas. Nature 379, 146–149 (1996). https://doi.org/10.1038/379146a0.
[72] Neelin, J.D.; Battisti, D.S.; Hirst, A.C.; Jin, F.F.; Wakata, Y.; Yamagata, T.; Zebiak, S.E. ENSO theory. J. Geophys. Res. Oceans 1998, 103, 14262–14290.
[73] Rasmusson, E.M.; Carpenter, T.H. Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Weather Rev. 1982, 110, 354–384.
[74] Wang, B., 1995: Interdecadal changes in El Niño onset in the last four decades. J. Climate, 8, 267–285.
[75] Neelin, J. D., 1991: The slow sea surface temperature mode and the fast-wave limit: Analytic theory for tropical interannual oscillations and experiments in a hybrid coupled model. J. Atmos. Sci., 48, 584–606.
[76] Schopf, P. S.; and M. J. Suarez, 1988: Vacillations in a coupled ocean–atmosphere model. J. Atmos. Sci., 45, 549–566.
[77] Trenberth, Kevin E.; and David P. Stepaniak. " Indices of El Niño Evolution", Journal of Climate 14, 8 (2001): 1697-1701, accessed Apr 12, 2022, https://doi.org/10.1175/1520-0442(2001)014<1697: LIOENO>2.0.CO;2.
[78] Climate Prediction Center (2005-12-19). "Frequently Asked Questions about El Niño and La Niña". National Centers for Environmental Prediction. Archived from the original on 2009-08-27. Retrieved 2009-07-17.
[79] Maisyarah, S; A. Wirasatriya; J. Marwoto; P. Subardjo; and I. B. Prasetyawan. 2019. "The Effect of the ENSO on the Variability of SST and Chlorophyll-a in the SouthiChina Sea." IOP Conference Series: Earth and Environment Science 246 (2019): 012027. doi:10.1088/1755-1315/246/1/012027.
[80] Dewi, Y. W.; A. Wirasatriya; D. N. Sugianto; M. Helmi; J. Marwoto; and L. Maslukah. 2020. "Effect of ENSO and IOD on the Variability of Sea Surface Temperature (SST) in Java Sea." IOP Conference Series: Earth and Environmental Science 530 (2020): 012007. doi:10.1088/1755-1315/530/1/ 012007.
[81] Saji, N.H.; Goswami, B.N.; Vinayachandran, P.N.; Yamagata, T. A dipole mode in the tropical Indian Ocean. Nature 1999, 401, 360–363.
[82] Webster, P. J.; A. Moore; J. P. Loschnigg; and R. R. Leben. 1999. “Coupled Ocean-Atmosphere Dynamics in the Indian Ocean during 1997–98.” Nature 401 (6751): 356–360. doi:10.1038/43848.
[83] Abram, N.J.; Wright, N.M.; Ellis, B.; Dixon, B.C.; Wurtzel, J.B.; England, M.H.; Ummenhofer, C.C.; Philibosian, B.; Cahyarini, S.Y.; Yu, T.L.; et al. Coupling of Indo-Pacific climate variability over the last millennium. Nature 2020, 579, 385–392.
[84] Cai, W.; Yang, K.; Wu, L.; Huang, G.; Santoso, A.; Benjamin, N.; Wang, G.; Yamagata, T. Opposite response of strong and moderate positive Indian Ocean Dipole to global warming. Nat. Clim. Chang. 2020, 11, 1–6.
[85] Ashok, K.; Guan, Z.; Yamagata, T. Impact of the Indian Ocean dipole on the relationship between the Indian monsoon rainfall and ENSO. Geophys. Res. Lett. 2001, 28, 4499–4502.
[86] Hashizume, M.; Chaves, L.F.; Minakawa, N. Indian Ocean Dipole drives malaria resurgence in East African highlands. Sci. Rep. 2012, 2, 1–6.
[87] Chaves, L.F.; Satake, A.; Hashizume, M.; Minakawa, N. Indian Ocean dipole and rainfall drive a Moran effect in East Africa malaria transmission. J. Infect. Dis. 2012, 205, 1885–1891.
[88] Cai, W.; Cowan, T.; Raupach, M. Positive Indian Ocean Dipole events precondition southeast Australia bushfires. Geophys. Res. Lett. 2009, 36, 1–6.
[89] Manatsa, D.; Chingombe, W.; Matarira, C.H. The impact of the positive Indian Ocean dipole on Zimbabwe droughts. Int. J. Clim. 2008, 28, 2011–2029.
[90] Iskandar. I; Lestari D.O.; Utari P.A.; Supardi; Rozirwan; Khakim M. Y. N.; Poerwono P., and Setiabudidaya D. Evolution and impact of the 2016 negative Indian Ocean Dipole. 2018. J. Phys.: Conf. Ser. 985 012017.
[91] Lumban-Gaol, J.; Siswanto, E.; Mahapatra, K.; Natih, N.M.N.; Nurjaya, IW.; Hartanto, M.T.; Maulana, E.; Adrianto, L.; Rachman, H.A.; Osawa, T.; et al. Impact of the Strong Downwelling (Upwelling) on Small Pelagic Fish Production during the 2016 (2019) Negative (Positive) Indian Ocean Dipole Events in the Eastern Indian Ocean off Java. Climate 2021, 9, 29. https://doi.org/10.3390/cli9020029.
[92] Maarif MS. Declaration of Savu Sea Marine National Parkmand the achievement of 10 million hectares of marine protected-656 marea in Indonesia. 2009. Available online: http://surajis.multiply.com/journal/item/75 (accessed on 25 February 2021).
[93] de Boyer Montégut, C.; Madec, G.; Fischer, A.S.; Lazar, A.; Iudicone, D. Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology. J. Geophys. Res. 2004, 109, C12003.
[94] WAMDI group. The WAM Model: A Third Generation Ocean Wave Prediction Model. Journal of Physical Oceanography 1988, 1: 1775–1810. https://doi.org/10.1175/1520-0485(1988)018<1775:TWMTGO>2.0.CO;2.
[95] Wang, -J.-J.; Tang, D.L. Phytoplankton Patchiness during Spring Intermonsoon in Western Coast of South China Sea. Deep Sea Res. II 2014, 101: 120–128. https://doi.org/10.1016/j.dsr2.2013.09.020.
[96] Stewart, R. H. Introduction to Physical Oceanography. Texas A & M University: Texas, USA, 2008.
[97] Fernandez, E.; Lellouche, J.M. Product User Manual for the Global Ocean Reanalysis Products GLOBAL-REANALYSIS-PHY-001-030; Marine Copernicus EU: Toulouse, France, 2018.
[98] UNESCO. Tenth Report of the Joint Panel on Oceanographic Tables and Standards; UNESCO Technical Papers in Marine Science: Paris, France, 1981; p. 25.
[99] Draper, N.R.; Smith, H. Applied Regression Analysis; John Wiley & Sons: New York, NY, USA, 1998.
[100] Hao, Q.; Chai, F.; Xiu, P.; Bai, Y.; Chen, J.; Liu, C.; Le, F.; Zhou, F. Spatial and temporal variation in chlorophyll a concentration in the Eastern China Seas based on a locally modified satellite dataset. Estuar. Coast Shelf Sci. 2019, 220, 220–231.
[101] Manzer, C.R.; Connolly, T.P.; McPhee-Shaw, E.; Smith, G.J. Physical factors influencing phytoplankton abundance in southern Monterey Bay. Continent. Shelf Res. 2019, 180, 1–13.
[102] Sartimbul, A.; Nakata, H.; Rohadi, E.; Yusuf, B.; Kadarisman, H.P. Variations in chlorophyll-a concentration and the impact on Sardinella lemuru catches in Bali Strait, Indonesia. Prog. Oceanogr. 2010, 87, 168–174.
指導教授 林唐煌(Lin, Tang-Huang) 審核日期 2022-6-22
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