Literatura académica sobre el tema "Salinity – Indian Ocean"

Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros

Elija tipo de fuente:

Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Salinity – Indian Ocean".

Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.

También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.

Artículos de revistas sobre el tema "Salinity – Indian Ocean"

1

Hu, Shijian, Ying Zhang, Ming Feng, Yan Du, Janet Sprintall, Fan Wang, Dunxin Hu, Qiang Xie y Fei Chai. "Interannual to Decadal Variability of Upper-Ocean Salinity in the Southern Indian Ocean and the Role of the Indonesian Throughflow". Journal of Climate 32, n.º 19 (29 de agosto de 2019): 6403–21. http://dx.doi.org/10.1175/jcli-d-19-0056.1.

Texto completo
Resumen
Abstract Variability of oceanic salinity, an indicator of the global hydrological cycle, plays an important role in the basin-scale ocean circulation. In this study, interannual to decadal variability of salinity in the upper layer of the Indian Ocean is investigated using Argo observations since 2004 and data assimilating model outputs (1992–2015). The southeastern Indian Ocean shows the strongest interannual to decadal variability of upper-ocean salinity in the Indian Ocean. Westward propagation of salinity anomalies along isopycnal surfaces is detected in the southern Indian Ocean and attributed to zonal salinity advection anomalies associated with the Indonesian Throughflow and the South Equatorial Current. Composite and salinity budget analyses show that horizontal advection is a major contributor to the interannual to decadal salinity variability of the southern Indian Ocean, and the local air–sea freshwater flux plays a secondary role. The Pacific decadal oscillation (PDO) and El Niño–Southern Oscillation (ENSO) modulate the salinity variability in the southeastern Indian Ocean, with low salinity anomalies occurring during the negative phases of the PDO and ENSO and high salinity anomalies during their positive phases. The Indonesian Throughflow plays an essential role in transmitting the PDO- and ENSO-related salinity signals into the Indian Ocean. A statistical model is proposed based on the PDO index, which successfully predicts the southeastern Indian Ocean salinity variability with a lead time of 10 months.
Los estilos APA, Harvard, Vancouver, ISO, etc.
2

Kido, Shoichiro y Tomoki Tozuka. "Salinity Variability Associated with the Positive Indian Ocean Dipole and Its Impact on the Upper Ocean Temperature". Journal of Climate 30, n.º 19 (1 de septiembre de 2017): 7885–907. http://dx.doi.org/10.1175/jcli-d-17-0133.1.

Texto completo
Resumen
Abstract Both surface and subsurface salinity variability associated with positive Indian Ocean dipole (pIOD) events and its impacts on the sea surface temperature (SST) evolution are investigated through analysis of observational/reanalysis data and sensitivity experiments with a one-dimensional mixed layer model. During the pIOD, negative (positive) sea surface salinity (SSS) anomalies appear in the central-eastern equatorial Indian Ocean (southeastern tropical Indian Ocean). In addition to these SSS anomalies, positive (negative) salinity anomalies are found near the pycnocline in the eastern equatorial Indian Ocean (southern tropical Indian Ocean). A salinity balance analysis shows that these subsurface salinity anomalies are mainly generated by zonal and vertical salt advection anomalies induced by anomalous currents associated with the pIOD. These salinity anomalies stabilize (destabilize) the upper ocean stratification in the central-eastern equatorial (southeastern tropical) Indian Ocean. By decomposing observed densities into contribution from temperature and salinity anomalies, it is shown that the contribution from anomalous salinity stratification is comparable to that from anomalous thermal stratification. Furthermore, impacts of these salinity anomalies on the SST evolution are quantified for the first time using a one-dimensional mixed layer model. Since enhanced salinity stratification in the central-eastern equatorial Indian Ocean suppresses vertical mixing, significant warming of about 0.3°–0.5°C occurs. On the other hand, stronger vertical mixing associated with reduced salinity stratification results in significant SST cooling of about 0.2°–0.5°C in the southeastern tropical Indian Ocean. These results suggest that variations in salinity may potentially play a crucial role in the evolution of the pIOD.
Los estilos APA, Harvard, Vancouver, ISO, etc.
3

Han, Weiqing y Julian P. McCreary. "Modeling salinity distributions in the Indian Ocean". Journal of Geophysical Research: Oceans 106, n.º C1 (15 de enero de 2001): 859–77. http://dx.doi.org/10.1029/2000jc000316.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
4

Iskandar, Mochamad Riza y Dewi Surinati. "DECADAL MIXED LAYER SALINITY IN THE SOUTHEASTERN INDIAN OCEAN". Marine Research in Indonesia 44, n.º 2 (28 de diciembre de 2019): 72–81. http://dx.doi.org/10.14203/mri.v44i2.546.

Texto completo
Resumen
The decadal of mixed layer salinity budget in the southeastern Indian Ocean (SETIO) is evaluated by using monthly gridded reanalysis ocean dataset (Estimated State of Global Ocean for Climate Research (ESTOC)) from January 1960 to December 2014. The evaluation of salinity budget through the examination of atmospheric flux, surface advection, Ekman advection and entrainment terms. The mixed layer salinity (MLS) in the outflow of the ITF shows decadal cycle. The decadal MLS tendency follows the Ekman advection term. The other processes such as atmospheric surface flux, surface advection and entrainment terms are counterbalanced and small correlates to the salinity tendency.
Los estilos APA, Harvard, Vancouver, ISO, etc.
5

Yuhong, Zhang, Du Yan, Zheng Shaojun, Yang Yali y Cheng Xuhua. "Impact of Indian Ocean Dipole on the salinity budget in the equatorial Indian Ocean". Journal of Geophysical Research: Oceans 118, n.º 10 (octubre de 2013): 4911–23. http://dx.doi.org/10.1002/jgrc.20392.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
6

Jensen, Tommy G. "Wind-Driven Response of the Northern Indian Ocean to Climate Extremes*". Journal of Climate 20, n.º 13 (1 de julio de 2007): 2978–93. http://dx.doi.org/10.1175/jcli4150.1.

Texto completo
Resumen
Abstract Composites of Florida State University winds (1970–99) for four different climate scenarios are used to force an Indian Ocean model. In addition to the mean climatology, the cases include La Niña, El Niño, and the Indian Ocean dipole (IOD). The differences in upper-ocean water mass exchanges between the Arabian Sea and the Bay of Bengal are investigated and show that, during El Niño and IOD years, the average clockwise Indian Ocean circulation is intensified, while it is weakened during La Niña years. As a consequence, high-salinity water export from the Arabian Sea into the Bay of Bengal is enhanced during El Niño and IOD years, while transport of low-salinity waters from the Bay of Bengal into the Arabian Sea is enhanced during La Niña years. This provides a venue for interannual salinity variations in the northern Indian Ocean.
Los estilos APA, Harvard, Vancouver, ISO, etc.
7

Zhang, Zheen, Thomas Pohlmann y Xueen Chen. "Correlation between subsurface salinity anomalies in the Bay of Bengal and the Indian Ocean Dipole and governing mechanisms". Ocean Science 17, n.º 1 (3 de marzo de 2021): 393–409. http://dx.doi.org/10.5194/os-17-393-2021.

Texto completo
Resumen
Abstract. Lead–lag correlations between the subsurface temperature and salinity anomalies in the Bay of Bengal (BoB) and the Indian Ocean Dipole (IOD) are revealed in model results, ocean synthesis, and observations. Mechanisms for such correlations are further investigated using the Hamburg Shelf Ocean Model (HAMSOM), mainly relating to the salinity variability. It is found that the subsurface salinity anomaly of the BoB positively correlates to the IOD, with a lag of 3 months on average, while the subsurface temperature anomaly correlates negatively. The model results suggest the remote forcing from the equatorial Indian Ocean dominates the interannual subsurface salinity variability in the BoB. The coastal Kelvin waves carry signals of positive (negative) salinity anomalies from the eastern equatorial Indian Ocean and propagate counterclockwise along the coasts of the BoB during positive (negative) IOD events. Subsequently, westward Rossby waves propagate these signals to the basin at a relatively slow speed, which causes a considerable delay of the subsurface salinity anomalies in the correlation. By analyzing the salinity budget of the BoB, it is found that diffusion dominates the salinity changes near the surface, while advection dominates the subsurface; the vertical advection of salinity contributes positively to this correlation, while the horizontal advection contributes negatively. These results suggest that the IOD plays a crucial role in the interannual subsurface salinity variability in the BoB.
Los estilos APA, Harvard, Vancouver, ISO, etc.
8

Sonzogni, Corinne, Edouard Bard, Frauke Rostek, Denis Dollfus, Antoni Rosell-Melé y Geoffrey Eglinton. "Temperature and Salinity Effects on Alkenone Ratios Measured in Surface Sediments from the Indian Ocean". Quaternary Research 47, n.º 3 (mayo de 1997): 344–55. http://dx.doi.org/10.1006/qres.1997.1885.

Texto completo
Resumen
We compare alkenone unsaturation ratios measured on recent sediments from the Indian Ocean (20°N–45°S) with modern sea oceanographic parameters. For each of the core sites we estimated average seasonal cycles of sea surface temperature (SST) and salinity, which we then weighted with the seasonal productivity cycle derived from chlorophyll satellite imagery. The unsaturation index (U37K′) ranges from 0.2 to 1 and correlates with water temperature but not with salinity. TheU37K′versus SST relationship for Indian Ocean sediments (U37K′= 0.033 SST + 0.05) is similar to what has been observed for core tops from the Pacific and Atlantic oceans and the Black Sea. A global compilation for core tops givesU37K′= 0.031 T + 0.084 (R= 0.98), which is close to a previously reported calibration based on particulate organic matter from the water column. For temperatures between 24° and 29°C, however, the slope seems to decrease to about 0.02U37K′unit/°C. For Indian Ocean core tops, the ratios of total C37alkenones/total C38alkenones and the slope of theU37K′-SST relationship are similar to those previously observed for cultures ofEmiliania huxleyibut different from those previously published forGephyrocapsa oceanica.EitherE. huxleyiis a major producer of alkenones in the Indian Ocean or strains ofG. oceanicaliving in the northern Indian Ocean behave differently from the one cultured. In contrast with coccolithophorid assemblages, the ratios of C37alkenones to total C38alkenones lack clear geographic pattern in the Indian Ocean.
Los estilos APA, Harvard, Vancouver, ISO, etc.
9

Sharma, Rashmi, Neeraj Agarwal, Imran M. Momin, Sujit Basu y Vijay K. Agarwal. "Simulated Sea Surface Salinity Variability in the Tropical Indian Ocean". Journal of Climate 23, n.º 24 (15 de diciembre de 2010): 6542–54. http://dx.doi.org/10.1175/2010jcli3721.1.

Texto completo
Resumen
Abstract A long-period (15 yr) simulation of sea surface salinity (SSS) obtained from a hindcast run of an ocean general circulation model (OGCM) forced by the NCEP–NCAR daily reanalysis product is analyzed in the tropical Indian Ocean (TIO). The objective of the study is twofold: assess the capability of the model to provide realistic simulations of SSS and characterize the SSS variability in view of upcoming satellite salinity missions. Model fields are evaluated in terms of mean, standard deviation, and characteristic temporal scales of SSS variability. Results show that the standard deviations range from 0.2 to 1.5 psu, with larger values in regions with strong seasonal transitions of surface currents (south of India) and along the coast in the Bay of Bengal (strong Kelvin-wave-induced currents). Comparison of simulated SSS with collocated SSS measurements from the National Oceanographic Data Center and Argo floats resulted in a high correlation of 0.85 and a root-mean-square error (RMSE) of 0.4 psu. The correlations are quite high (>0.75) up to a depth of 300 m. Daily simulations of SSS compare well with a Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy in the eastern equatorial Indian Ocean (1.5°S, 90°E) with an RMSE of 0.3 psu and a correlation better than 0.6. Model SSS compares well with observations at all time scales (intraseasonal, seasonal, and interannual). The decorrelation scales computed from model and buoy SSS suggest that the proposed 10-day sampling of future salinity sensors would be able to resolve much of the salinity variability at time scales longer than intraseasonal. This inference is significant in view of satellite salinity sensors, such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius.
Los estilos APA, Harvard, Vancouver, ISO, etc.
10

Nagura, Motoki y Shinya Kouketsu. "Spiciness Anomalies in the Upper South Indian Ocean". Journal of Physical Oceanography 48, n.º 9 (septiembre de 2018): 2081–101. http://dx.doi.org/10.1175/jpo-d-18-0050.1.

Texto completo
Resumen
AbstractThis study investigates an isopycnal temperature/salinity T/S, or spiciness, anomaly in the upper south Indian Ocean for the period from 2004 to 2015 using observations and reanalyses. Spiciness anomalies at about 15°S on 24–26σθ are focused on, whose standard deviation is about 0.1 psu in salinity and 0.25°C in temperature, and they have a contribution to isobaric temperature variability comparable to thermocline heave. A plausible generation region of these anomalies is the southeastern Indian Ocean, where the 25σθ surface outcrops in southern winter, and the anticyclonic subtropical gyre advects subducted water equatorward. Unlike the Pacific and Atlantic, spiciness anomalies in the upper south Indian Ocean are not T/S changes in mode water, and meridional variations in SST and sea surface salinity in their generation region are not density compensating. It is possible that this peculiarity is owing to freshwater originating from the Indonesian Seas. The production of spiciness anomalies is estimated from surface heat and freshwater fluxes and the surface T/S relationship in the outcrop region, based on several assumptions including the dominance of surface fluxes in the surface T/S budget and effective mixed layer depth proposed by Deser et al. The result agrees well with isopycnal salinity anomalies at the outcrop line, which indicates that spiciness anomalies are generated by local surface fluxes. It is suggested that the Ningaloo Niño and El Niño–Southern Oscillation lead to interannual variability in surface heat flux in the southeastern Indian Ocean and contribute to the generation of spiciness anomalies.
Los estilos APA, Harvard, Vancouver, ISO, etc.
Más fuentes

Tesis sobre el tema "Salinity – Indian Ocean"

1

Han, Weiqing. "Influence of Salinity on Dynamics, Thermodynamics and Mixed-Layer Physics in the Indian Ocean". NSUWorks, 1999. http://nsuworks.nova.edu/occ_stuetd/62.

Texto completo
Resumen
A nonlinear, 4½-layer model with active thermodynamics and mixed-layer physics is used to examine salinity effects due to various forcings in the Indian Ocean. Theses forcings include: evaporation (ε) and precipitation (Ρ), river runoff in the Bay of Bengal, the Indonesian Throughflow, and the influx of salty waters from the Persian Gulf and the Red Sea. Solutions with P - ε forcing produce salinity patterns that agree qualitatively with the observations in the upper three layers. Quantitatively, however, salinity values tend to be higher than the observations in most of the basin. In regions where precipitation is strong (P - ε » 0), a thin surface mixed layer (layer 1), and thus a thicker seasonal thermocline (layer 2, a barrier layer), are formed due to decreased entrainment. In these regions, surface currents generally strengthen, T2 warms considerably and SST increases somewhat, resulting in temperature inversions at some locations of the southern Bay and the eastern equatorial ocean. Somewhat surprisingly, P - ε also causes large temperature changes in layer 3 (thermocline) and thickness changes in layers 3 and 4 (intermediate water). The Bay-of-Bengal river runoff improves salinity values significantly in the upper three layers, especially within the Bay and alongC the west coast of India. During the Southwest onsoon (SWM), coastal Kelvin waves driven by the Ganges-Brahmaputra river inflow suppress upwelling along the northeast coast of India, increasing SST by 1°C. During the Northeast Monsoon (NEM), fresh water from the rivers is carried southward by the East India Coastal Current (EICC), raising sea level and thus strengthening the EICGby 10 cm/s. This fresh water can flow directly through the India-Sri Lanka separation in the surface mixed layer, generating a strong salinity gradient along the west Indian coast during winter. The river water decreases entrainment around the perimeter of the Bay during winter, thereby producing a thin surface mixed layer, increasing T2 , and resulting in temperature inversions in the northwestern Bay. Like P - ε, the rivers cause significant thickness and temperature anomalies in layer 3. The Indonesian Throughflow improves salinities in all four layers of the model, especially in the southern tropical ocean. Consistent with previous studies, most of the Throughflow water flows out of the Indian Ocean along the western boundary and near Madagascar. A significant amount of water, however, is advected northward into the Somali basin and subsequently carried eastward into the ocean interior and northward into the Arabian Sea. The Throughflow increases SST primarily along the west Australian coast but warms the thermocline (layer 3) throughout the Indian Ocean, especially in the southern tropical ocean. As a consequence, sea level is raised in the entire basin. Warmer and saltier Persian-Gulf water (PGW) enters the Indian Ocean in layer 3, warming the northern Arabian Sea by 0.2-2°C and increasing the salinity by 0.1-0.6 psu through horizontal mixing. It increases sea-surface salinity (SSS) in a broad region of the Arabian Sea by 0.1- 0.2 psu because entrainment and, to a less extent, coastal upwelling bring PGW into the surface mixed layer, where it spreads over a large region due to advection. High-salinity and high-temperature Red-Sea water (RSW) warms layer-4 (upper intermediate layer) and increases its salinity by a significant amount in most region of the Indian Ocean, especially in the Somali Basin, the interior Arabian Sea, and the central and western equatorial ocean.
Los estilos APA, Harvard, Vancouver, ISO, etc.
2

Valiya, Parambil Akhil. "Apport des données spatiales pour la modélisation numérique de la couche de mélange du Golfe du Bengale". Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30333/document.

Texto completo
Resumen
Le Golfe du Bengale (GdB), dans l'océan indien Nord, est sous l'influence d'intenses vents de mousson, qui se renversent saisonnièrement. Les fortes pluies et les apports fluviaux associés à la mousson de Sud-Ouest font du GdB l'une des régions les moins salées des océans tropicaux. La forte stratification haline proche de la surface qui en découle contribue à limiter le mélange vertical, ce qui maintient des températures de surface élevées et favorise la convection atmosphérique et les pluies. Cette stratification en sel a ainsi des implications profondes sur les échanges air-mer et sur le climat des pays riverains. L'objectif de ma thèse est d'améliorer la description de la variabilité de la salinité de surface (SSS) du GdB, et de comprendre ses mécanismes aux échelles de temps saisonnières à interannuelles. Les climatologies existantes ont permis de mettre en évidence un cycle saisonnier marqué de la SSS, avec un dessalement intense de la partie Nord du bassin pendant l'automne, suivi par une expansion de ces eaux dessalées le long du bord Ouest du bassin. Cette langue dessalée s'érode finalement pendant l'hiver, pour revenir à son extension minimale au printemps. Cependant, la rareté des observations in-situ de SSS ne permet d'observer les fluctuations interannuelles autour de ce cycle saisonnier que de manière parcellaire dans le GdB. Le développement récent de la télédétection spatiale de la SSS (missions SMOS et AQUARIUS) a ouvert de nouvelles opportunités à cet égard. Cette technologie reste toutefois délicate dans le cas d'un bassin de petite taille tel que le GdB, du fait des contaminations éventuelles du signal de SSS par les interférences radio et par les sources d'origine continentale. Une validation systématique des produits satellites par comparaison à un jeu de données in-situ exhaustif montre qu'Aquarius capture de façon réaliste les évolutions saisonnières et interannuelles de la SSS partout dans le GdB. A l'inverse, SMOS ne parvient pas à restituer une salinité meilleure que les climatologies existantes
Located in the Northern Indian Ocean, the Bay of Bengal (BoB) is forced by intense seasonally reversing monsoon winds. Heavy rainfall and strong river runoffs associated with the southwest monsoon makes the bay one of the freshest regions in the tropical ocean. This surface fresh water flux induces strong near surface salinity stratification, which reduces vertical mixing and maintains high sea surface temperatures and deep atmospheric convection and rainfall. This intense near surface haline stratification has therefore profound implications on the air-sea exchanges, and on the climate of the neighboring countries. The goal of my thesis is to improve the description of the Sea surface salinity (SSS) variability in the BoB and to understand the oceanic and atmospheric processes driving this variability at seasonal and interannual timescales. Existing climatologies reveal a marked seasonal cycle of SSS with an intense freshening of the northern part of the basin during fall that subsequently spreads along the western boundary. This fresh pool finally erodes during winter, to reach its minimal extent in spring. The paucity of in-situ SSS observations however prevented to monitor the interannual fluctuations around this seasonal picture with a good spatial coverage. The recent development of SSS remote-sensing capabilities (with SMOS and AQUARIUS satellites) may help with that regard. However this is particularly challenging for a small semi-enclosed basin such as the Bay of Bengal, because of the potential contamination of the SSS signal by radio frequency interferences and land effects in the near coastal environment. A thorough validation of these satellite products to an exhaustive gridded in-situ dataset shows that Aquarius reasonably captures the large-scale observed seasonal and interannual SSS evolution everywhere in the BoB while SMOS does not perform better than existing climatologies, advocating for improvements of its SSS retrieval algorithm there
Los estilos APA, Harvard, Vancouver, ISO, etc.
3

Boyer, Montégut Clément de. "Couche mélangée océanique et bilan thermohalin de surface dans l'Océan Indien Nord". Paris 6, 2005. https://tel.archives-ouvertes.fr/tel-00011449.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
4

Parampil, Sindu Raj. "Observed Subseasonal Variability Of Temperarture And Salinity In The Tropical Indian Ocean". Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2040.

Texto completo
Resumen
Subseasonal variability of tropical Indian Ocean sea surface temperature is thought to influence the active-break cycle of the Asian monsoon. There are several open questions related to the role of surface fluxes, large-scale ocean circulation and subsurface ocean processes in the subseasonal variability of upper ocean temperature. We present a unified study of the subseasonal (2-90 day) variability of surface heat flux and upper ocean temperature and salinity throughout the tropical Indian Ocean in all seasons. We focus on the relation between surface fluxes and ocean response using a new satellitebased daily heat flux. The role of ocean processes (advection, entrainment and mixing) in determining SST variability is diagnosed from the daily satellite SST. Before the onset of the summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30-32oC. Climatological mean mixed layer depth in spring (March-May) is 10-20 m, and net surface heat flux (Qnet) is 80-100 Wm 2 into the ocean. It has been suggested that observed spring SST warming is small mainly due to (a) penetrative flux of solar radiation through the base of the mixed layer (Qpen), (b) advective cooling by upper ocean currents and (c) entrainment of sub-mixed layer cool water. We estimate the role of the first two processes in SST evolution from a two-week ARMEX experiment in April-May 2005 in the the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling. The cooling occurs although the ocean gains heat at the surface - Qnet is about 105 Wm 2 in the warming phase, and 25 Wm 2 in the cooling phase; penetrative loss Qpen, is 80 Wm 2 and 70 Wm 2. In the warming phase, SST rises mainly due to heat absorbed within the mixed layer, i.e. Qnet minus Qpen; Qpen, reduces the rate of SST warming by a factor of three. In the second phase, SST cools rapidly because (a) Qpen, is larger than Qnet, and (b) advective cooling is _85 Wm 2. A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal time scale. Buoy and satellite data suggest that a typical premonsoon intraseasonal SST cooling event occurs under clear skies and weak winds, when the ocean is gaining heat. In this respect, premonsoon SST cooling in the north Indian ocean is different from that due to MJO or monsoon ISO. As a follow-up to ARMEX, we use a short dataset from a field campaign in the premonsoon north Bay of Bengal to study diurnal variability of SST. In addition to the standard meteorological and hydrographic parameters measured from shipborne instruments and buoy sensors, we obtained a two-hourly record of subsurface sunlight profiles. Heat fluxes are seen to drive the SST warming during the day while both advection and entrainment/mixing are important during the night. The simple heat balance based on heat flux shows that it drives the diurnal cycle of SST, though ocean processes contribute towards night time cooling; this has been confirmed using the Price-Weller-Pinkel mixing model forced by heat flux and wind stress. A similar analysis for mixed layer salinity revealed that the salt balance in the region is dominated by advection rather than freshwater flux or entrainment/mixing. Buoy and satellite data show pronounced subseasonal oscillations of sea surface temperature (SST) in the summertime north Indian Ocean. The SST oscillations are forced mainly by surface heat flux associated with the active-break cycle of the south Asian summer monsoon. The input of freshwater (FW) from summer rain and rivers to the Bay is large, but not much is known about subseasonal salinity variability. We use 2002-2007 observations from Argo floats with 5-day repeat cycle to study the subseasonal response of temperature and salinity to surface heat and freshwater flux in the central Bay of Bengal and central Arabian Sea. Estimates of surface heat and freshwater flux are based on daily satellite data sampled along the float trajectory. We find that intraseasonal variability (ISV) of mixed layer temperature is mainly a response to net surface heat flux minus penetrative radiation during the summer monsoon season. In winter and spring, however, temperature variability appears to be mainly due to ocean processes rather than local heat flux. Variability of mixed layer freshwater content is generally independent of local surface flux (precipitation minus evaporation) in all seasons. There are occasions when intense monsoon rainfall leads to local freshening, but these are rare. The large subseasonal fluctuations observed in FW appear to be due to advection, suggesting that freshwater from rivers and rain moves in eddies or filaments. We have developed a new daily satellite-based heat flux dataset for the tropical Indian Ocean (30oE 120oE; 30oS 30oN); satellite data include surface air temperature and relative humidity from the Atmospheric Infrared Sounder (AIRS). On the seasonal scale (> 90 days) the flux compares reasonably well with climatologies and other daily data. On the subseasonal scale, our flux product has realistic behaviour relative to buoy data at validation sites. An important result is that ocean processes (advection, entrainment/detrainment, mixing at the base of the mixed layer) cool the tropical Indian Ocean SST by 8oC over the year. The largest contribution of ocean processes (_20oC SST cooling over the year) is in the western equatorial Indian Ocean. Ocean processes generally cool the upper ocean in all seasons and all regions, except in boreal winter, when they warm the north Indian Ocean. This is likely due to entrainment of warm sub-mixed layer water in regions of inversions. On subseasonal (2-90 days) scales, the contribution of air temperature and humidity to latent heat flux is roughly equal to the contribution from wind speed variability: Another interesting finding is that the contribution of air temperature and humidity increases away from the equator. One of the most important contributions of this thesis is the demonstration that tropical Indian Ocean SST has a coherent response to intraseasonal changes in heat flux associated with organised convection in the summer hemisphere. SST responds to flux in (i) the northeast Indian Ocean during May-October and (ii) the 15oS-5oN region during November-April. In the winter hemisphere and in regions with no organised convection, it is ocean processes and not fluxes which drive the subseasonal changes in SST. This result suggests that SST ISV feeds back to organise and sustain organised convection in the tropical atmosphere.
Los estilos APA, Harvard, Vancouver, ISO, etc.

Libros sobre el tema "Salinity – Indian Ocean"

1

United States. National Oceanic and Atmospheric Administration., ed. World Ocean Atlas 1998, Volume 6: Salinity Of The Indian Ocean... NOAA Atlas NESDIS 32... U.S. Department Of Commerce... December 1998. [S.l: s.n., 1999.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.

Actas de conferencias sobre el tema "Salinity – Indian Ocean"

1

Khan, Sartaj, Shengchun Piao, Yang Song, Shazia Khan, Bingchen Xu y Zeeshan Babar. "Seasonal Evolution of Sea Surface Salinity in the Northwestern Indian Ocean: Argo Data Study". En 2021 OES China Ocean Acoustics (COA). IEEE, 2021. http://dx.doi.org/10.1109/coa50123.2021.9519918.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
2

Grunseich, Gary y Subrahmanyam Bulusu. "Validation of SMOS salinity data and its applications the to Indian Ocean climatic events". En OCEANS 2011. IEEE, 2011. http://dx.doi.org/10.23919/oceans.2011.6106963.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
3

Subrahmanyam, B., V. S. N. Murty y J. J. O'Brien. "New sea surface salinity product in the tropical Indian Ocean estimated from Outgoing Longwave Radiation". En Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492). IEEE, 2003. http://dx.doi.org/10.1109/oceans.2003.178166.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
4

Momin, Imranali M., Ashis K. Mitra, D. K. Mahapatra y E. N. Rajagopal. "A review of recent evaluation of satellite estimates sea surface salinity in the tropical Indian Ocean". En SPIE Asia-Pacific Remote Sensing, editado por Tiruvalam N. Krishnamurti y Madhavan N. Rajeevan. SPIE, 2016. http://dx.doi.org/10.1117/12.2223571.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
5

Yueh, Simon, Wenqing Tang, Alexander Fore, Julian Chaubell Akiko Hayashi, Gary Lagerloef, Thomas Jackson y Rajat Bindlish. "Aquarius salinity and wind retrieval using the CAP algorithm and application to water cycle observation in the Indian Ocean and subcontinent". En IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723146.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
6

Sadrinasab, Masoud y Karim Kenarkoohi. "A Three-Dimensional Numerical Modelling Study of the Sound Velocity Profiles in the Persian Gulf". En ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57062.

Texto completo
Resumen
The Persian Gulf connects to the Indian Ocean via the Strait of Hormuz. In this study, a three-dimensional hydrodynamic model (COHERENS) is employed in a fully prognostic mode to derive sound velocity profiles in the Persian Gulf, an evaporation-driven inverse estuary that is governed by import of surface water from the adjacent ocean and export of saline bottom gulf water through the Strait of Hormuz. During spring and summer, a cyclonic overturning circulation establishes along the full length of the Gulf. During autumn and winter, this circulation breaks up into mesoscale eddies, laterally stirring most of the Gulf’s surface waters. Output of the model shows that sound velocity in the Persian Gulf depends mainly on the temperature in the surface layer whereas the bottom layer as well as the southern part of the Gulf depends on temperature and salinity. Maximum sound velocity occurs during summer in the Persian Gulf which decreases gradually moving from Strait of Hormuz to the north western part of the Gulf. A gradual decrease in sound velocity profiles with depth was commonly observed almost at all stations in the Gulf. However, an exception occurred in Strait of Hormuz during winter. The results of the model are very close to previous observations.
Los estilos APA, Harvard, Vancouver, ISO, etc.
Ofrecemos descuentos en todos los planes premium para autores cuyas obras están incluidas en selecciones literarias temáticas. ¡Contáctenos para obtener un código promocional único!

Pasar a la bibliografía