53 resultados para Equatorial Indian Ocean Oscillation (EQUINOO)


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Intraseasonal time-scales play an important role in tropical variability. Two modes that contribute significantly to tropical intraseasonal variability (ISV) are the eastward-propagating MaddenJulian Oscillation (MJO), and westward-moving moist equatorial Rossby waves. This note reports on a correspondence between the longitudinal gradient of mean tropical precipitable water (PW), and the geographical regions of genesis, and convective activity, of both these large-scale tropical systems. Our finding is based on an analysis of PW from the MERRA reanalysis product. The data indicate that the mean tropical PW has a dominant wavenumber two (three) structure in longitude in the Northern (Southern) Hemisphere. Departures from a longitudinally homogeneous state are attributed to the influence of subtropical anticyclones, and are accentuated by monsoonal regions of both hemispheres. This mean structure results in a sharply localized longitudinal gradient of PW. Remarkably, regions with positive gradients (such as the Northern and Southern Hemisphere western Indian Ocean), i.e. they have larger PW to the east, are the very zones that are implicated in the formation, and show high levels of convective activity, of the eastward-moving MJO. On the other hand, regions with negative gradients (such as the Southern Hemisphere central Pacific) are the very regions where genesis, and maxima in variance, of westward-moving moist equatorial Rossby waves are known to occur. Apart from providing a first-order longitudinal footprint of the convective phase of these systems, this correspondence reinforces the role of the mean climatic state in tropical ISV. Copyright (c) 2012 Royal Meteorological Society

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In monsoon regions, the seasonal migration of the intertropical convergence zone (ITCZ) is manifested as a seasonal reversal of winds. Most of the summer monsoon rainfall over India occurs owing to synoptic and large-scale convection associated with the continental ITCZ (Fig. 1). We have investigated the interaction between these large-scale convective systems and the ocean over which they are generated1â3, concentrating on the relationship between organized convection over the Indian Ocean and sea surface temperature (SST). We report here that on a monthly basis the degree of cloudiness correlates well with SST for the relatively colder oceans, but when SST is maintained above 28 °C it ceases to be an important factor in determining the variability of cloudiness. Over the major regions of convection east of 70°E, which are warm year after year, the observed cloudiness cannot be correlated with variations in SST.

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An Ocean General Circulation Model of the Indian Ocean with high horizontal (0.25 degrees x 0.25 degrees) and vertical (40 levels) resolutions is used to study the dynamics and thermodynamics of the Arabian Sea mini warm pool (ASMWP), the warmest region in the northern Indian Ocean during January-April. The model simulates the seasonal cycle of temperature, salinity and currents as well as the winter time temperature inversions in the southeastern Arabian Sea (SEAS) quite realistically with climatological forcing. An experiment which maintained uniform salinity of 35 psu over the entire model domain reproduces the ASMWP similar to the control run with realistic salinity and this is contrary to the existing theories that stratification caused by the intrusion of low-salinity water from the Bay of Bengal into the SEAS is crucial for the formation of ASMWP. The contribution from temperature inversions to the warming of the SEAS is found to be negligible. Experiments with modified atmospheric forcing over the SEAS show that the low latent heat loss over the SEAS compared to the surroundings, resulting from the low winds due to the orographic effect of Western Ghats, plays an important role in setting up the sea surface temperature (SST) distribution over the SEAS during November March. During March-May, the SEAS responds quickly to the air-sea fluxes and the peak SST during April-May is independent of the SST evolution during previous months. The SEAS behaves as a low wind, heat-dominated regime during November-May and, therefore, the formation and maintenance of the ASMWP is not dependent on the near surface stratification.

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Before the onset of the south Asian summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30–32°C. Climatological mean mixed layer depth in spring (March–May) is 10–20 m, and net surface heat flux (Q net ) is 80–100 W m−2 into the ocean. Previous work suggests that observed spring SST warming is small mainly because of (1) penetrative flux of solar radiation through the base of the mixed layer (Q pen ) and (2) advective cooling by upper ocean currents. We estimate the role of these two processes in SST evolution from a two-week Arabian Sea Monsoon Experiment process experiment in April–May 2005 in 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, although the ocean gains heat at the surface: Q net is about 105 W m−2 in the warming phase and 25 W m−2 in the cooling phase; penetrative loss Q pen is 80 W m−2 and 70 W m−2. In the warming phase, SST rises mainly because of heat absorbed within the mixed layer, i.e., Q net minus Q pen ; Q pen reduces the rate of SST warming by a factor of 3. In the second phase, SST cools rapidly because (1) Q pen is larger than Q net and (2) advective cooling is ∼85 W m−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 timescale. Buoy and satellite data suggest that a typical premonsoon intraseasonal cooling event occurs under clear skies when the ocean is gaining heat through the surface. In this respect, premonsoon SST cooling in the north Indian Ocean is different from that due to the Madden-Julian oscillation or monsoon intraseasonal oscillation.

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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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The simulation characteristics of the Asian-Australian monsoon are documented for the Community Climate System Model, version 4 (CCSM4). This is the first part of a two part series examining monsoon regimes in the global tropics in the CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 Community Atmosphere Model, version 4, (CAM4)] to deduce differences in the monsoon simulations run with observed sea surface temperatures (SSTs) and with ocean-atmosphere coupling. These simulations are also compared to a previous version of the model (CCSM3) to evaluate progress. In general, monsoon rainfall is too heavy in the uncoupled AMIP run with CAM4, and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Most aspects of the Asian-Australian monsoon simulations are improved in CCSM4 compared to CCSM3. There is a reduction of the systematic error of rainfall over the tropical Indian Ocean for the South Asian monsoon, and well-simulated connections between SSTs in the Bay of Bengal and regional South Asian monsoon precipitation. The pattern of rainfall in the Australian monsoon is closer to observations in part because of contributions from the improvements of the Indonesian Throughflow and diapycnal diffusion in CCSM4. Intraseasonal variability of the Asian-Australian monsoon is much improved in CCSM4 compared to CCSM3 both in terms of eastward and northward propagation characteristics, though it is still somewhat weaker than observed. An improved simulation of El Nino in CCSM4 contributes to more realistic connections between the Asian-Australian monsoon and El Nino-Southern Oscillation (ENSO), though there is considerable decadal and century time scale variability of the strength of the monsoon-ENSO connection.

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Arabian Sea Mini Warm Pool (ASMWP) is a part of the Indian Ocean Warm Pool and formed in the eastern Arabian Sea prior to the onset of the summer monsoon season. This warm pool attained its maximum intensity during the pre-monsoon season and dissipated with the commencement of summer monsoon. The main focus of the present work was on the triggering of the dissipation of this warm pool and its relation to the onset of summer monsoon over Kerala. This phenomenon was studied utilizing NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric and Research) re-analysis data, TRMM Micro wave Imager (TMI) and observational data. To define the ASMWP, sea surface temperature exceeding 30.25A degrees C was taken as the criteria. The warm pool attained its maximum dimension and intensity nearly 2 weeks prior to the onset of summer monsoon over Kerala. Interestingly, the warm pool started its dissipation immediately after attaining its maximum core temperature. This information can be included in the present numerical models to enhance the prediction capability. It was also found that the extent and intensity of the ASMWP varied depending on the type of monsoon i.e., excess, normal, and deficient monsoon. Maximum core temperature and wide coverage of the warm pool observed during the excess monsoon years compared to normal and deficient monsoon years. The study also revealed a strong relationship between the salinity in the eastern Arabian Sea and the nature of the monsoon.

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A network of ship-mounted real-time Automatic Weather Stations integrated with Indian geosynchronous satellites Indian National Satellites (INSATs)] 3A and 3C, named Indian National Centre for Ocean Information Services Real-Time Automatic Weather Stations (I-RAWS), is established. The purpose of I-RAWS is to measure the surface meteorological-ocean parameters and transmit the data in real time in order to validate and refine the forcing parameters (obtained from different meteorological agencies) of the Indian Ocean Forecasting System (INDOFOS). Preliminary validation and intercomparison of analyzed products obtained from the National Centre for Medium Range Weather Forecasting and the European Centre for Medium-Range Weather Forecasts using the data collected from I-RAWS were carried out. This I-RAWS was mounted on board oceanographic research vessel Sagar Nidhi during a cruise across three oceanic regimes, namely, the tropical Indian Ocean, the extratropical Indian Ocean, and the Southern Ocean. The results obtained from such a validation and intercomparison, and its implications with special reference to the usage of atmospheric model data for forcing ocean model, are discussed in detail. It is noticed that the performance of analysis products from both atmospheric models is similar and good; however, European Centre for Medium-Range Weather Forecasts air temperature over the extratropical Indian Ocean and wind speed in the Southern Ocean are marginally better.