999 resultados para SEA-SURFACE


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The variability of the sea surface salinity (SSS) in the Indian Ocean is studied using a 100-year control simulation of the Community Climate System Model (CCSM 2.0). The monsoon-driven seasonal SSS pattern in the Indian Ocean, marked by low salinity in the east and high salinity in the west, is captured by the model. The model overestimates runoff int the Bay of Bengal due to higher rainfall over the Himalayan-Tibetan regions which drain into the Bay of Bengal through Ganga-Brahmaputra rivers. The outflow of low-salinity water from the Bay of Bengal is to strong in the model. Consequently, the model Indian Ocean SSS is about 1 less than that seen in the climatology. The seasonal Indian Ocean salt balance obtained from the model is consistent with the analysis from climatological data sets. During summer, the large freshwater input into the Bay of Bengal and its redistribution decide the spatial pattern of salinity tendency. During winter, horizontal advection is the dominant contributor to the tendency term. The interannual variability of the SSS in the Indian Ocean is about five times larger than that in coupled model simulations of the North Atlantic Ocean. Regions of large interannual standard deviations are located near river mouths in the Bay of Bengal and in the eastern equatorial Indian Ocean. Both freshwater input into the ocean and advection of this anomalous flux are responsible for the generation of these anomalies. The model simulates 20 significant Indian Ocean Dipole (IOD) events and during IOD years large salinity anomalies appear in the equatorial Indian Ocean. The anomalies exist as two zonal bands: negative salinity anomalies to the north of the equator and positive to the south. The SSS anomalies for the years in which IOD is not present and for ENSO years are much weaker than during IOD years. Significant interannual SSS anomalies appear in the Indian Ocean only during IOD years.

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The interannual variation of surface fields over the Arabian Sea and Bay of Bengal are studied using data between 1900 and 1979. It is emphasized that the monthly mean sea surface temperature (SST) over the north Indian Ocean and monsoon rainfall are significantly affected by synoptic systems and other intraseasonal variations. To highlight the interannual signals it is important to remove the large-amplitude high-frequency noise and very low frequency long-term trends, if any. By suitable spatial and temporal averaging of the SST and the rainfall data and by removing the long-term trend from the SST data, we have been able to show that there exists a homogeneous region in the southeastern Arabian Sea over which the March�April (MA) SST anomalies are significantly correlated with the seasonal (June�September) rainfall over India. A potential of this premonsoon signal for predicting the seasonal rainfall over India is indicated. It is shown that the correlation between the SST and the seasonal monsoon rainfall goes through a change of sign from significantly positive with premonsoon SST to very small values with SST during the monsoon season and to significantly negative with SST during the post-monsoon months. For the first time, we have demonstrated that heavy or deficient rainfall years are associated with large-scale coherent changes in the SST (although perhaps of small amplitude) over the north Indian 0cean. We also indicate possible reasons for the apparent lack of persistence of the premonsoon SST anomalies.

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Plastic-coated paper is shown to possess reflectivity characteristics quite similar to those of the surface of water. This correspondence has been used with a conversion factor to model a sea surface by means of plastic-coated paper. Such a paper model is then suitably illuminated and photographed, yielding physically simulated daylight imagery of the sea surface under controlled conditions. A simple example of sinusoidal surface simulation is described.

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The convective available potential energy (CAFE) based on monthly mean sounding has been shown to be relevant to deep convection in the tropics. The variation of CAFE with SST has been found to be similar to the variation of the frequency of deep convection at one station each in the tropical Atlantic and W. Pacific oceans. This suggests a strong link between the frequency of tropical convection and CAFE. It has been shown that CAFE so derived can be interpreted as the work potential of the atmosphere above the boundary layer with ascent in the convective region and subsidence in the surrounding cloud-free region.

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The authors present the simulation of the tropical Pacific surface wind variability by a low-resolution (R15 horizontal resolution and 18 vertical levels) version of the Center for Ocean-Land-Atmosphere Interactions, Maryland, general circulation model (GCM) when forced by observed global sea surface temperature. The authors have examined the monthly mean surface winds acid precipitation simulated by the model that was integrated from January 1979 to March 1992. Analyses of the climatological annual cycle and interannual variability over the Pacific are presented. The annual means of the simulated zonal and meridional winds agree well with observations. The only appreciable difference is in the region of strong trade winds where the simulated zonal winds are about 15%-20% weaker than observed, The amplitude of the annual harmonics are weaker than observed over the intertropical convergence zone and the South Pacific convergence zone regions. The amplitudes of the interannual variation of the simulated zonal and meridional winds are close to those of the observed variation. The first few dominant empirical orthogonal functions (EOF) of the simulated, as well as the observed, monthly mean winds are found to contain a targe amount of high-frequency intraseasonal variations, While the statistical properties of the high-frequency modes, such as their amplitude and geographical locations, agree with observations, their detailed time evolution does not. When the data are subjected to a 5-month running-mean filter, the first two dominant EOFs of the simulated winds representing the low-frequency EI Nino-Southern Oscillation fluctuations compare quite well with observations. However, the location of the center of the westerly anomalies associated with the warm episodes is simulated about 15 degrees west of the observed locations. The model simulates well the progress of the westerly anomalies toward the eastern Pacific during the evolution of a warm event. The simulated equatorial wind anomalies are comparable in magnitude to the observed anomalies. An intercomparison of the simulation of the interannual variability by a few other GCMs with comparable resolution is also presented. The success in simulation of the large-scale low-frequency part of the tropical surface winds by the atmospheric GCM seems to be related to the model's ability to simulate the large-scale low-frequency part of the precipitation. Good correspondence between the simulated precipitation and the highly reflective cloud anomalies is seen in the first two EOFs of the 5-month running means. Moreover, the strong correlation found between the simulated precipitation and the simulated winds in the first two principal components indicates the primary role of model precipitation in driving the surface winds. The surface winds simulated by a linear model forced by the GCM-simulated precipitation show good resemblance to the GCM-simulated winds in the equatorial region. This result supports the recent findings that the large-scale part of the tropical surface winds is primarily linear.

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Intraseasonal variations (ISV) of sea surface temperature (SST) in the Bay of Bengal (BoB) is highest in its northwestern part. An Indian Ocean model forced by QuikSCAT winds and climatological river discharge (QR run) reproduces ISV of SST, albeit with weaker magnitude. Air-sea fluxes, in the presence of a shallow mixed layer, efficiently effect intraseasonal SST fluctuations. Warming during intraseasonal events is smaller (<1°C) for June - July period and larger (1.5° to 2°C) during September, the latter due to a thinner mixed layer. To examine the effect of salinity on ISV, the model was run by artificially increasing the salinity (NORR run) and by decreasing it (MAHA10 run). In NORR, both rainfall and river discharge were switched off and in MAHA10 the discharge by river Mahanadi was increased tenfold. The spatial pattern of ISV as well as its periodicity was similar in QR, NORR and MAHA10. The ISV was stronger in NORR and weaker in MAHA10, compared to QR. In NORR, both intraseasonal warming and cooling were higher than in QR, the former due to reduced air-sea heat loss as the mean SST was lower, and the latter due to enhanced subsurface processes resulting from weaker stratification. In MAHA10, both warming and cooling were lower than in QR, the former due to higher air-sea heat loss owing to higher mean SST, and the latter due to weak subsurface processes resulting from stronger stratification. These model experiments suggest that salinity effects are crucial in determining amplitudes of intraseasonal SST variations in the BoB.

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During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against similar to 0.25 for wind stress) and in observations (0.8 regression coefficient); similar to 60% of the heat flux variation is due do shortwave radiation and similar to 40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our similar to 100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

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The diurnal cycle is an important mode of sea surface temperature (SST) variability in tropical oceans, influencing air-sea interaction and climate variability. Upper ocean mixing mechanisms are significant at diurnal time scales controlling the intraseasonal variability (ISV) of SST. Sensitivity experiments using an Ocean General Circulation Model (OGCM) for the summer monsoon of the year 2007 show that incorporation of diurnal cycle in the model atmospheric forcings improves the SST simulation at both intraseasonal and shorter time scales in the Bay of Bengal (BoB). The increase in SST-ISV amplitudes with diurnal forcing is approximate to 0.05 degrees C in the southern bay while it is approximate to 0.02 degrees C in the northern bay. Increased intraseasonal warming with diurnal forcing results from the increase in mixed layer heat gain from insolation, due to shoaling of the daytime mixed layer. Amplified intraseasonal cooling is dominantly controlled by the strengthening of subsurface processes owing to the nocturnal deepening of mixed layer. In the southern bay, intraseasonal variability is mainly determined by the diurnal cycle in insolation, while in the northern bay, diurnal cycle in insolation and winds have comparable contributions. Temperature inversions (TI) develop in the northern bay in the absence of diurnal variability in wind stress. In the northern bay, SST-ISV amplification is not as large as that in the southern bay due to the weaker diurnal variability of mixed layer depth (MLD) limited by salinity stratification. Diurnal variability of model MLD is not sufficient to create large modifications in mixed layer heat budget and SST-ISV in the northern bay.

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The combination of remotely sensed gappy Sea surface temperature (SST) images with the missing data filling DINEOF (data interpolating empirical orthogonal functions) technique, followed by a principal component analysis of the reconstructed data, has been used to identify the time evolution and the daily scale variability of the wintertime surface signal of the Iberian Poleward Current (IPC), or Navidad, during the 1981-2010 period. An exhaustive comparison with the existing bibliography, and the vertical temperature and salinity profiles related to its extremes over the Bay of Biscay area, show that the obtained time series accurately reflect the IPC-Navidad variability. Once a time series for the evolution of the SST signal of the current over the last decades is well established, this time series is used to propose a physical mechanism in relation to the variability of the IPC-Navidad, involving both atmospheric and oceanic variables. According to the proposed mechanism, an atmospheric circulation anomaly observed in both the 500 hPa and the surface levels generates atmospheric surface level pressure, wind-stress and heat-flux anomalies. In turn, those surface level atmospheric anomalies induce mutually coherent SST and sea level anomalies over the North Atlantic area, and locally, in the Bay of Biscay area. These anomalies, both locally over the Bay of Biscay area and over the North Atlantic, are in agreement with several mechanisms that have separately been related to the variability of the IPC-Navidad, i.e. the south-westerly winds, the joint effect of baroclinicity and relief (JEBAR) effect, the topographic beta effect and a weakened North Atlantic gyre.

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ENGLISH: Isograms of sea surface temperature (OC) have been produced for 1949-1968 for the areas of the eastern Pacific Ocean in which the majority of the skipjack catch is taken. These are in the immediate coastal zone, California (35° N) to Chile (20 0 S), and the Revillagigedo and Galapagos Islands groups. Skipjack occurrence and apparent abundance (as CSDF, i.e., catch per standard days fishing, standardized in purse-seiner units) for 1951-1968 were then superimposed on the surface temperature isograms. Results show that skipjack occur at surface temperatures> 17° C but with the majority between 20°-30° C. Apparent abundance at CSDF > 1 ton/day is normally Iimited to 20°29° C water, except in two areas in certain years; from the Gulf of Tehuantepec to Cape Mala rates of 1-9 tons/day are relatively common at 29°-30° C, and off Chimbote (Peru) occasionally >9 tons/day are recorded down to 18° C. As expected there were no apparent relationships between annual thermal conditions in the coastal zone and skipjack abundance (total catch or indices of abundance) in the same or 2 subsequent years. An Appendix to the report determines the quantitative relationships between surface temperature and skipjack abundance in relatively small areal strata in Baja California waters in 1955 and 1958. Relationships generally appeared significant and opposite in these years when temperatures were respectively anomalously cold and warm. SPANISH: Se han producido isogramas de la temperatura de la superficie del mar (OC) para 1949-1968 correspondientes a las áreas del Océano Pacífico oriental en donde se obtiene la mayor parte de la captura de barrilete. Estas se encuentran ubicadas en la zona costanera inmediata, desde California (35°N) hasta Chile (200S) y en las Islas Revillagigedo y Galápagos. La ocurrencia de barrilete y su abundancia aparente (expresada como CDSP standardizada en unidades de cerqueros) para 1951-1968 fueron luego superpuestas en los isogramas de la temperatura superficial. Los resultados demuestran que el barrilete aparece en temperaturas superficiales de > 17°C pero la mayoría entre los 20°C-30°C. La abundancia aparente de la CDSP > 1 tonelada/día se limita normalmente a aguas de 20°-29°C, excepto en dos áreas en ciertos años; desde el Golfo de Tehuantepec a Cabo Mala las tasas de 1-9 toneladas/día son relativamente comunes en los 29°-30°C, y frente a Chimbote (Perú) se registran ocasionalmente> 9 toneladas/día a una temperatura tan fría como de 18°C. Como era de esperarse no existió una relación aparente entre las condiciones térmicas anuales de la zona costanera y la abundancia del barrilete (captura total o índices de abundancia) en el mismo año o en los 2 años siguientes. Un Apéndice del informe determina la relación cuantitativa entre la temperatura superficial y la abundancia del barrilete en un estrato de áreas relativamente pequeño en las aguas de Baja California en 1955 y 1968. Las relaciones generalmente aparecieron significativas y opuestas en esos años cuando las temperaturas fueron respectivamente anómalamente frías y calientes. (PDF contains 53 pages.)

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Daily sea surface temperatures have been acquired at the Hopkins Marine Station in Pacific Grove, California since January 20, 1919.This time series is one of the longest oceanographic records along the U.S. west coast. Because of its length it is well-suited for studying climate-related and oceanic variability on interannual, decadal, and interdecadal time scales. The record, however, is not homogeneous, has numerous gaps, contains possible outliers, and the observations were not always collected at the same time each day. Because of these problems we have undertaken the task of reconstructing this long and unique series. We describe the steps that were taken and the methods that were used in this reconstruction. Although the methods employed are basic, we believe that they are consistent with the quality of the data. The reconstructed record has values at every time point, original, or estimated, and has been adjusted for time-of-day variations where this information was available. Possible outliers have also been examined and replaced where their credibility could not be established. Many of the studies that have employed the Hopkins time series have not discussed the issue of data quality and how these problems were addressed. Because of growing interest in this record, it is important that a single, well-documented version be adopted, so that the results of future analyses can be directly compared. Although additional work may be done to further improve the quality of this record, it is now available via the internet. [PDF contains 48 pages]

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Data from the Mexican purse seiner fleet operating in the eastern Tropical Pacific, for the year 1985-1990, are used to show that the fraction of surface schools of yellowfin tuna Thunnus albacares associated with dolphins (Stenella attenuata and others) increases with sea surface temperature. Possible reasons for this correlation are briefly discussed.

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Data recovered from 11 popup satellite archival tags and 3 surgically implanted archival tags were used to analyze the movement patterns of juvenile northern bluefin tuna (Thunnus thynnus orientalis) in the eastern Pacific. The light sensors on archival and pop-up satellite transmitting archival tags (PSATs) provide data on the time of sunrise and sunset, allowing the calculation of an approximate geographic position of the animal. Light-based estimates of longitude are relatively robust but latitude estimates are prone to large degrees of error, particularly near the times of the equinoxes and when the tag is at low latitudes. Estimating latitude remains a problem for researchers using light-based geolocation algorithms and it has been suggested that sea surface temperature data from satellites may be a useful tool for refining latitude estimates. Tag data from bluefin tuna were subjected to a newly developed algorithm, called “PSAT Tracker,” which automatically matches sea surface temperature data from the tags with sea surface temperatures recorded by satellites. The results of this algorithm compared favorably to the estimates of latitude calculated with the lightbased algorithms and allowed for estimation of fish positions during times of the year when the lightbased algorithms failed. Three near one-year tracks produced by PSAT tracker showed that the fish range from the California−Oregon border to southern Baja California, Mexico, and that the majority of time is spent off the coast of central Baja Mexico. A seasonal movement pattern was evident; the fish spend winter and spring off central Baja California, and summer through fall is spent moving northward to Oregon and returning to Baja California.

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Previous consideration of the relationship between climate and the survival rate of Pacific salmon eggs and fry has been confined to effects of large variation in the ambient freshwater environment; e.g., stream discharge, temperature, turbidity. This analysis shows sea surface temperatures during the last year of life of maturing adult salmon are also strongly associated with the subsequent survival rate of salmon eggs and fry is fresh water, presumably through development of the future eggs or sperm. In several stocks of three species of North American salmon, the association between the "marine" climate and egg survival is stronger than, or additive to, any estimated climatic association in fresh water. This apparent and surprising link between fresh water and the distant ocean has some interesting and complex implications for management of future salmon production.