2 resultados para EVENT RELATED

em Indian Institute of Science - Bangalore - Índia


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The garnet-kyanite-staurolite and garnet-biotite-staurolite gneisses were collected from a locality within Lukung area that belongs to the Pangong metamorphic complex in Shyok valley, Ladakh Himalaya. The kyanite-free samples have garnet and staurolite in equilibrium, where garnets show euhedral texture and have flat compositional profile. On the other hand, the kyanite-bearing sample shows equilibrium assemblage of garnet-kyanite-staurolite along with muscovite and biotite. In this case, garnet has an inclusion rich core with a distinct grain boundary, which was later overgrown by inclusion free euhedral garnet. Garnet cores are rich in Mn and Ca, while the rims are poor in Mn and rich in Fe and Mg, suggesting two distinct generations of growth. However, the compositional profiles and textural signature of garnets suggests the same stage of P -T evolution for the formation of the inclusion free euhedral garnets in the kyanite-free gneisses and the inclusion free euhedral garnet rims in the kyanite-bearing gneiss. Muscovites from the four samples have consistent K-Ar ages, suggesting the cooling age (∼ 10 Ma) of the gneisses. These ages make a constraint on the timing of the youngest post-collision metamorphic event that may be closely related to an activation of the Karakoram fault in Pangong metamorphic complex.

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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.