Interactions of the Indian Ocean climate with other tropical oceans

2020 ◽  
Author(s):  
Matthieu Lengaigne ◽  
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Future Climate ◽  
Future Climate Change ◽  
The Pacific ◽  
Ocean Atmosphere ◽  
The Indian Ocean ◽  
The Tropics ◽  
Modes Of Climate Variability ◽  
The Tropical Pacific

<p>Ocean-atmosphere interactions in the tropics have a profound influence on the climate system. El Niño–Southern Oscillation (ENSO), which is spawned in the tropical Pacific, is the most prominent and well-known year-to-year variation on Earth. Its reach is global, and its impacts on society and the environment are legion. Because ENSO is so strong, it can excite other modes of climate variability in the Indian Ocean by altering the general circulation of the atmosphere. However, ocean-atmosphere interactions internal to the Indian Ocean are capable of generating distinct modes of climate variability as well. Whether the Indian Ocean can feedback onto Atlantic and Pacific climate has been an on-going matter of debate. We are now beginning to realize that the tropics, as a whole, are a tightly inter-connected system, with strong feedbacks from the Indian and Atlantic Oceans onto the Pacific. These two-way interactions affect the character of ENSO and Pacific decadal variability and shed new light on the recent hiatus in global warming.</p><p>Here we review advances in our understanding of pantropical interbasins climate interactions with the Indian Ocean and their implications for both climate prediction and future climate projections. ENSO events force changes in the Indian Ocean than can feed back onto the Pacific. Along with reduced summer monsoon rainfall over the Indian subcontinent, a developing El Niño can trigger a positive Indian Ocean Dipole (IOD) in fall and an Indian Ocean Basinwide (IOB) warming in winter and spring. Both IOD and IOB can feed back onto ENSO. For example, a positive IOD can favor the onset of El Niño, and an El Niño–forced IOB can accelerate the demise of an El Niño and its transition to La Niña. These tropical interbasin linkages however vary on decadal time scales. Warming during a positive phase of Atlantic Multidecadal Variability over the past two decades has strengthened the Atlantic forcing of the Indo-Pacific, leading to an unprecedented intensification of the Pacific trade winds, cooling of the tropical Pacific, and warming of the Indian Ocean. These interactions forced from the tropical Atlantic were largely responsible for the recent hiatus in global surface warming.</p><p>Climate modeling studies to address these issues are unfortunately compromised by pronounced systematic errors in the tropics that severely suppress interactions with the Indian and Pacific Oceans. As a result, there could be considerable uncertainty in future projections of Indo-Pacific climate variability and the background conditions in which it is embedded. Projections based on the current generation of climate models suggest that Indo-Pacific mean-state changes will involve slower warming in the eastern than in the western Indian Ocean. Given the presumed strength of the Atlantic influence on the pantropics, projections of future climate change could be substantially different if systematic model errors in the Atlantic were corrected. There is hence tremendous potential for improving seasonal to decadal climate predictions and for improving projections of future climate change in the tropics though advances in our understanding of the dynamics that govern interbasin linkages.</p>

scholarly journals Indian Ocean Decadal Variability: A Review

2014 ◽  
Vol 95 (11) ◽  
pp. 1679-1703 ◽  
Author(s):  
Weiqing Han ◽  
Jérôme Vialard ◽  
Michael J. McPhaden ◽  
Tong Lee ◽  
Yukio Masumoto ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Decadal Variability ◽  
International Scientific Community ◽  
Climate Research ◽  
Physical Mechanisms ◽  
The Pacific ◽  
Climatic Impacts ◽  
The Indian Ocean ◽  
Multidecadal Climate Variability

The international scientific community has highlighted decadal and multidecadal climate variability as a priority area for climate research. The Indian Ocean rim region is home to one-third of the world's population, mostly living in developing countries that are vulnerable to climate variability and to the increasing pressure of anthropogenic climate change. Yet, while prominent decadal and multidecadal variations occur in the Indian Ocean, they have been less studied than those in the Pacific and Atlantic Oceans. This paper reviews existing literature on these Indian Ocean variations, including observational evidence, physical mechanisms, and climatic impacts. This paper also identifies major issues and challenges for future Indian Ocean research on decadal and multidecadal variability.

scholarly journals Interannual to Decadal Variability of Tropical Indian Ocean Sea Surface Temperature: Pacific Influence versus Local Internal Variability

2020 ◽  
pp. 1-50
Author(s):  
Lei Zhang ◽  
Gang Wang ◽  
Matthew Newman ◽  
Weiqing Han
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Tropical Indian Ocean ◽  
Tropical Pacific ◽  
Sea Surface ◽  
External Influence ◽  
Sst Variability ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Tropical Pacific

AbstractThe Indian Ocean has received increasing attention for its large impacts on regional and global climate. However, sea surface temperature (SST) variability arising from Indian Ocean internal processes has not been well understood particularly on decadal and longer timescales, and the external influence from the Tropical Pacific has not been quantified. This paper analyzes the interannual-to-decadal SST variability in the Tropical Indian Ocean in observations and explores the external influence from the Pacific versus internal processes within the Indian Ocean using a Linear Inverse Model (LIM). Coupling between Indian Ocean and tropical Pacific SST anomalies (SSTAs) is assessed both within the LIM dynamical operator and the unpredictable stochastic noise that forces the system. Results show that the observed Indian Ocean Basin (IOB)-wide SSTA pattern is largely a response to the Pacific ENSO forcing, although it in turn has a damping effect on ENSO especially on annual and decadal timescales. On the other hand, the Indian Ocean Dipole (IOD) is an Indian Ocean internal mode that can actively affect ENSO; ENSO also has a returning effect on the IOD, which is rather weak on decadal timescale. The third mode is partly associated with the Subtropical Indian Ocean Dipole (SIOD), and it is primarily generated by Indian Ocean internal processes, although a small component of it is coupled with ENSO. Overall, the amplitude of Indian Ocean internally generated SST variability is comparable to that forced by ENSO, and the Indian Ocean tends to actively influence the tropical Pacific. These results suggest that the Indian-Pacific Ocean interaction is a two-way process.

Predictability of Indian Ocean Dipole (IOD)

2016 ◽  
Author(s):  
Jing-Jia Luo
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
The West ◽  
The North ◽  
The Pacific ◽  
Westerly Winds ◽  
Ocean Atmosphere ◽  
The Indian Ocean

This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article. The tropical Indian Ocean is unique in several aspects. Unlike the Pacific and the Atlantic Oceans, the Indian Ocean is bounded to the north by a large landmass, the Eurasian continent. The large thermal heat contrast between the ocean in the south and the land in the north induces the world’s strongest monsoon systems in South and East Asia, in response to the seasonal migration of solar radiation. The strong and seasonally reversing surface winds generate large seasonal variations in ocean currents and basin-wide meridional heat transport across the equator. In contrast to the tropical Pacific and the Atlantic, where easterly trade winds prevail throughout the year, westerly winds (albeit with a relatively weak magnitude) blow along the equatorial Indian Ocean, particularly during the boreal spring and autumn seasons, generating the semi-annual Yoshida-Wyrtki eastward equatorial ocean currents. As a consequence of the lack of equatorial upwelling, the tropical Indian Ocean occupies the largest portion of the warm water pool (with Sea Surface Temperature [SST] being greater than 28 °C) on Earth. The massive warm water provides a huge potential energy available for deep convections that significantly affect the weather-climate over the globe. It is therefore of vital importance to discover and understand climate variabilities in the Indian Ocean and to further develop a capability to correctly predict the seasonal departures of the warm waters and their global teleconnections. The Indian Ocean Dipole (IOD) is the one of the recently discovered climate variables in the tropical Indian Ocean. During the development of the super El Niño in 1997, the climatological zonal SST gradient along the equator was much reduced (with strong cold SST anomalies in the east and warm anomalies in the west). The surface westerly winds switched to easterlies, and the ocean thermocline became shallow in the east and deep in the west. These features are reminiscent of what are observed during El Niño years in the Pacific, representing a typical coupled process between the ocean and the atmosphere. The IOD event in 1997 contributed significantly to floods in eastern Africa and severe droughts and bushfires in Indonesia and southeastern Australia. Since the discovery of the 1997 IOD event, extensive efforts have been made to lead the rapid progress in understanding the air-sea coupled climate variabilities in the Indian Ocean; and many approaches, including simple statistical models and comprehensive ocean-atmosphere coupled models, have been developed to simulate and predict the Indian Ocean climate. Essential to the discussion are the ocean-atmosphere dynamics underpinning the seasonal predictability of the IOD, critical factors that limit the IOD predictability (inter-comparison with El Niño-Southern Oscillation [ENSO]), observations and initialization approaches that provide realistic initial conditions for IOD predictions, models and approaches that have been developed to simulate and predict the IOD, the influence of global warming on the IOD predictability, impacts of IOD-ENSO interactions on the IOD predictability, and the current status and perspectives of the IOD prediction at seasonal to multi-annual timescales.

scholarly journals Kyllinga nemoralis (white kyllinga).

2020 ◽  
Author(s):  
Eduardo Ventosa-Febles
Keyword(s):  
Invasive Species ◽  
Indian Ocean ◽  
Positive Reaction ◽  
Related Species ◽  
Grass Species ◽  
Old World ◽  
The Pacific ◽  
The Indian Ocean ◽  
Tropical Climates ◽  
The Tropics

Abstract Kyllingia nemoralis is a perennial sedge native to the tropical Old World that has been introduced elsewhere in Oceania, the Indian Ocean and the Americas. Several species of Cyperaceae are listed as highly invasive worldwide. Sedges of the genus Kyllinga are recognized for their invasive tendencies in tropical climates. K. nemoralis exhibits characteristics common to the success of an invasive species, such as asexual spreading, positive reaction to human-caused disturbance, early and consistent reproduction and small seeds. In the tropics, it can be competitive with grass species and is sometimes aggressive in lawns, turf and pasture. A related species K. polyphylla, is a major weed of improved pastures, but can be suppressed by competition from vigorous, well managed grasses. K. nemoralis is listed as invasive in a number of islands in the Pacific and Indian Oceans.

A new marine Dryosphaera (Ascomycotina) from the tropics

1993 ◽  
Vol 71 (7) ◽  
pp. 992-995
Author(s):  
Jan Kohlmeyer ◽  
Brigitte Volkmann-Kohlmeyer
Keyword(s):  
New Species ◽  
Indian Ocean ◽  
Type Species ◽  
Marine Fungi ◽  
Sandy Beaches ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Pacific Ocean ◽  
The Caribbean ◽  
The Tropics

The marine ascomycete Dryosphaera tropicalis Kohlm. & Volkm.-Kohlm., sp.nov., is described from the Caribbean (Tobago), the Indian Ocean (Sri Lanka, Thailand), and the Pacific Ocean (Hawaiian Islands: Hawaii, Kauai, Maui, and Molokai). The new species occurs on intertidal and supratidal wood on sandy beaches. It is compared with the type species, Dryosphaera navigans from temperate waters, and differs mainly by ascospore dimensions and appendages. Key words: arenicolous fungi, ascomycetes, Dryosphaera, marine fungi, tropics.

scholarly journals PENGARUH PROPAGASI MADDEN JULIAN OSCILLATION (MJO) DI BENUA MARITIM INDONESIA (BMI) TERHADAP SIKLUS DIURNAL DINAMIKA ATMOSFER DAN CURAH HUJAN DI PROVINSI LAMPUNG TAHUN 2018

2021 ◽  
Vol 22 (2) ◽  
pp. 71-84
Author(s):  
Sindy Maharani ◽  
Hasti Amrih Rejeki
Keyword(s):  
Indian Ocean ◽  
Diurnal Cycle ◽  
Time Lag ◽  
Early Morning ◽  
Madden Julian Oscillation ◽  
Phase 3 ◽  
Diurnal Cycles ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Tropics

Intisari Madden Julian Oscillation (MJO) merupakan osilasi gelombang submusiman di wilayah tropis yang berpropagasi ke arah timur dari Samudera Hindia melewati Benua Maritim Indonesia (BMI) hingga Samudera Pasifik. Propagasi MJO dapat meningkatkan konvektivitas dan curah hujan pada wilayah yang dilewatinya. Lampung merupakan salah satu wilayah di BMI bagian barat yang berbatasan dengan Samudera Hindia sebagai tempat awal kemunculan MJO. Posisi Lampung tersebut menyebabkan perbedaan insolasi antara daratan dan lautan secara diurnal sehingga siklus diurnal ikut berperan dalam pembentukan cuaca. Oleh karena itu penelitian ini bertujuan untuk mengetahui pengaruh propagasi MJO dari Fase 3-5 pada tahun 2018 terhadap siklus diurnal dinamika atmosfer dan curah hujan di Lampung. Siklus diurnal dianalisis dengan membagi empat periode waktu yaitu dini hari (00.00-06.00 LT), pagi hari (06.00-12.00 LT), siang hari (12.00-18.00 LT) dan malam hari (18.00-00.00 LT). Berdasarkan rata-rata komposit data Reanalysis ECMWF, GSMaP, dan curah hujan observasi didapatkan bahwa selama penjalarannya MJO menguat ketika Fase 3-4 dan melemah ketika Fase 5. Secara diurnal konvektivitas yang kuat dan curah hujan tinggi terjadi di perairan pada dini hari hingga pagi hari, di daerah pesisir pada siang hari, dan di daratan pada malam hari yang meningkat dari Fase 3-4 dan melemah pada Fase 5. Hujan menjalar dari Lampung bagian barat menuju Lampung bagian tengah dengan jeda waktu selama 2-5 jam ketika Fase 3, 4-7 jam ketika Fase 4, dan 1-2 jam ketika Fase 5. Pada Fase 3-5 hujan terjadi di Lampung bagian timur dengan perbedaan waktu 1-3 jam dari Lampung bagian tengah.   Abstract Madden Julian oscillation (MJO) is a sub-seasonal wave oscillation in the tropics that propagates eastward from the Indian Ocean through the Indonesian Maritime Continent (IMC) until the Pacific Ocean. MJO propagation can increase convective and rainfall in the regions it passes. Lampung is one of the regions in the western IMC which near the Indian Ocean for the MJO first appeared. The Lampung position causes different insolation between land and sea diurnally, so the diurnal cycles play an important role in weather formation. Therefore, this study aims to determine the effect of MJO propagation phases 3-5 in 2018 on the diurnal cycle of atmospheric dynamics and rainfall in Lampung. The diurnal cycle was analyzed by dividing four periods of time, in the early morning (00-06 LT), morning (06-12 LT), afternoon (12-18 LT), and night (18-00 LT). Based on the average composite of ECMWF, GSMaP, and precipitation observations data were obtained that propagation MJO strengthens during phase 3-4 and weakens during phase 5. Diurnal strong convective and high rainfall occur in the oceans from early morning to morning, in coastal during the day, and on land at night which increases from phase 3-4 and weakens in phase 5. Rain propagates from western Lampung to central Lampung with a time lag of 2-5 hours during phase 3, 4-7 hours when phases 4, and 1 -2 hours during phase 5. In the 3-5 phase, rain occurs in eastern Lampung with a time difference of 1-3 hours from central Lampung.  

scholarly journals Research Gap Analysis of Remote Sensing Application in Fisheries: Prospects for Achieving the Sustainable Development Goals

2021 ◽  
Vol 13 (5) ◽  
pp. 1013
Author(s):  
Kuo-Wei Yen ◽  
Chia-Hsiang Chen
Keyword(s):  
Sustainable Development ◽  
Indian Ocean ◽  
Atlantic Ocean ◽  
The Sustainable Development ◽  
The North ◽  
The Pacific ◽  
Development Goals ◽  
The Indian Ocean ◽  
The Pacific Ocean ◽  
Research Hotspots

Remote sensing (RS) technology, which can facilitate the sustainable management and development of fisheries, is easily accessible and exhibits high performance. It only requires the collection of sufficient information, establishment of databases and input of human and capital resources for analysis. However, many countries are unable to effectively ensure the sustainable development of marine fisheries due to technological limitations. The main challenge is the gap in the conditions for sustainable development between developed and developing countries. Therefore, this study applied the Web of Science database and geographic information systems to analyze the gaps in fisheries science in various countries over the past 10 years. Most studies have been conducted in the offshore marine areas of the northeastern United States of America. In addition, all research hotspots were located in the Northern Hemisphere, indicating a lack of relevant studies from the Southern Hemisphere. This study also found that research hotspots of satellite RS applications in fisheries were mainly conducted in (1) the northeastern sea area in the United States, (2) the high seas area of the North Atlantic Ocean, (3) the surrounding sea areas of France, Spain and Portugal, (4) the surrounding areas of the Indian Ocean and (5) the East China Sea, Yellow Sea and Bohai Bay sea areas to the north of Taiwan. A comparison of publications examining the three major oceans indicated that the Atlantic Ocean was the most extensively studied in terms of RS applications in fisheries, followed by the Indian Ocean, while the Pacific Ocean was less studied than the aforementioned two regions. In addition, all research hotspots were located in the Northern Hemisphere, indicating a lack of relevant studies from the Southern Hemisphere. The Atlantic Ocean and the Indian Ocean have been the subjects of many local in-depth studies; in the Pacific Ocean, the coastal areas have been abundantly investigated, while offshore local areas have only been sporadically addressed. Collaboration and partnership constitute an efficient approach for transferring skills and technology across countries. For the achievement of the sustainable development goals (SDGs) by 2030, research networks can be expanded to mitigate the research gaps and improve the sustainability of marine fisheries resources.

scholarly journals Sources of Tropical Subseasonal Skill in the CFSv2

2020 ◽  
Vol 148 (4) ◽  
pp. 1553-1565 ◽  
Author(s):  
Carl J. Schreck ◽  
Matthew A. Janiga ◽  
Stephen Baxter
Keyword(s):  
Indian Ocean ◽  
Low Frequency ◽  
Equatorial Pacific ◽  
Convectively Coupled Equatorial Waves ◽  
Subseasonal Variability ◽  
The Pacific ◽  
Fourier Filtering ◽  
The Indian Ocean ◽  
Rainfall Anomalies ◽  
Combined Data

Abstract This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.

Sign in / Sign up

Export Citation Format

Share Document