941 resultados para Pan American Union


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The Bay of Bengal, a semienclosed tropical basin that comes under the influence of monsoonal wind and freshwater influx, is distinguished by a strongly stratified surface layer and a seasonally reversing circulation. We discuss characteristics of these features in the western Bay during the northeast monsoon, when the East India Coastal Current (EICC) flows southward, using hydrographic data collected during December 1991. Vertical profiles show uniform temperature and salinity in a homogeneous surface layer, on average, 25 m deep but shallower northward and coastward. The halocline, immediately below, is approximately 50 m thick; salinity changes by approximately 3 parts per thousand. About two thirds of the profiles show temperature inversions in this layer. Salinity below the halocline hardly changes, and stratification is predominantly due to temperature variation, The halocline is noticeably better developed and the surface homogeneous layer is thinner in a low-salinity plume that hugs the coastline along the entire east coast of India, The plume is, on average, 50 km wide, with isohalines sloping down toward the coast. Most prominent in the geostrophic velocity field is the equatorward EICC. Its transport north of about 13 degrees N, computed with 1000 dbar as the level of reference, varies between 2.6 and 7.1 x 10(6) m(3) s(-1); just south of this latitude, a northwestward flow from offshore recurves and merges with the coastal current. At the southern end of the region surveyed, the transport is 7.7 x 10(6) m(3) s(-1). Recent model studies lead us to conclude that the EICC during the northeast monsoon is driven by winds along the east coast of India and Ekman pumping in the interior bay. In the south, Ekman pumping over the southwestern bay is responsible for the northwestward flow that merges with the EICC.

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Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

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[1] During a comprehensive aerosol field campaign, simultaneous measurements were made of aerosol spectral optical depths, black carbon mass concentration (M-b), total (M-t) and size segregated aerosol mass concentrations over an urban continental location, Bangalore (13 degreesN, 77 degreesE, 960 m msl), in India. Large amounts of BC were observed; both in absolute terms and fraction of total mass (similar to11%) and submicron mass (similar to23%) implying a significantly low single scatter albedo. The aerosol visible optical depth (tau(p)) was in the range 0.24 to 0.45. Estimated surface forcing is as high as -23 W m(-2) and top of the atmosphere (TOA) forcing is +5 Wm(-2) during relatively cleaner periods (tau(p) similar to 0.24). The net atmospheric absorption translates to an atmospheric heating of similar to0.8 K day(-1) for cleaner periods and similar to1.5 K day(-1) for less cleaner periods (tau(p) similar to 0.45). Our observations raise several issues, which may have impacts to regional climate and monsoon.

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[1] Recent experiments conducted over the oceanic regions adjacent to the Indian sub continent have revealed the presence of anthropogenic aerosol haze during January to March. It has been suggested that the major source of this aerosol is South and Southeast Asia. Here we show from long term, multi-station and ship borne observations that aerosols transported from regions northwest of Indian subcontinent especially Arabian and Saharan regions (mostly natural dust) along with the locally produced sea-salt aerosols by sea-surface winds constitute a more significant source of aerosols during April-May period. The radiative forcing due to Arabian/Saharan aerosols (mostly natural) during April May period is comparable and often exceed (as much as 1.5 times) the forcing due to anthropogenic aerosols during January to March period. The presence of dust load over the Arabian Sea can influence the temperature profile and radiative balance in this region.

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A spectrally resolved discrete-ordinates radiative transfer model is used to calculate the change in downwelling surface and top-of-the-atmosphere (TOA) outgoing longwave (3.9-500 mum) radiative fluxes induced by tropospheric aerosols of the type observed over the Indian Ocean during the Indian Ocean Experiment (INDOEX). Both external and internal aerosol mixtures were considered. Throughout the longwave, the aerosol volume extinction depends more strongly on relative humidity than in most of the shortwave (0.28-3.9 mum), implying that particle growth factors and realistic relative humidity profiles must be taken into account when modeling the longwave radiative effects of aerosols. A typical boundary layer aerosol loading, with a 500-nm optical depth of 0.3, will increase the downwelling longwave flux at the surface by 7.7 W m(-2) over the clean air case while decreasing the outgoing longwave radiation by 1.3 W m(-2). A more vertically extended aerosol loading, exhibiting a high opacity plume between 2 and 3 km above the surface and having a typical 500-nm optical depth of 0.7, will increase the downwelling longwave flux at the surface by 11.2 W m(-2) over the clean air case while decreasing the outgoing longwave radiation by 2.7 W m(-2). For a vertically extended aerosol profile, approximately 30% of the TOA radiative forcing comes from sea salt and approximately 60% of the forcing comes from the combination of sea salt and dust. The remaining forcing is from anthropogenic constituents. These results are for the external mixture. For an internal mixture, TOA longwave forcings can be up to a factor of two larger. Therefore, to complete our understanding of this region's longwave aerosol radiative properties, more detailed information is needed about aerosol mixing states. These longwave radiative effects partially offset the large shortwave aerosol radiative forcing and should be included in regional and global climate modeling simulations.

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Observations from moored buoys during spring of 1998-2000 suggest that the warming of the mixed layer (similar to20 m deep) of the north Indian Ocean warm pool is a response to net surface heat flux Q(net) (similar to100 W m(-2)) minus penetrative solar radiation Q(pen) (similar to45 W m(-2)). A residual cooling due to vertical mixing and advection is indirectly estimated to be about 25 W m(-2). The rate of warming due to typical values of Q(net) minus Q(pen) is not very sensitive to the depth of the mixed layer if it lies between 10 m and 30 m.

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We have analysed the diurnal cycle of rainfall over the Indian region (10S-35N, 60E-100E) using both satellite and in-situ data, and found many interesting features associated with this fundamental, yet under-explored, mode of variability. Since there is a distinct and strong diurnal mode of variability associated with the Indian summer monsoon rainfall, we evaluate the ability of the Weather Research and Forecasting Model (WRF) to simulate the observed diurnal rainfall characteristics. The model (at 54km grid-spacing) is integrated for the month of July, 2006, since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST), by using two different SST datasets, namely, Final Analyses (FNL) and Real-time Global (RTG). It was found that with RTG SST the rainfall simulation over central India (CI) was significantly better than that with FNL. On the other hand, over the Bay of Bengal (BoB), rainfall simulated with FNL was marginally better than with RTG. However, the overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the role of the convective parameterization scheme on the simulation of diurnal cycle of rainfall. We found that the Kain-Fritsch (KF) scheme performs significantly better than Betts-Miller-Janjić (BMJ) and Grell-Devenyi schemes. We also studied the impact of other physical parameterizations, namely, microphysics, boundary layer, land surface, and the radiation parameterization, on the simulation of diurnal cycle of rainfall, and identified the “best” model configuration. We used this configuration of the “best” model to perform a sensitivity study on the role of various convective components used in the KF scheme. In particular, we studied the role of convective downdrafts, convective timescale, and feedback fraction, on the simulated diurnal cycle of rainfall. The “best” model simulations, in general, show a good agreement with observations. Specifically, (i) Over CI, the simulated diurnal rainfall peak is at 1430 IST, in comparison to the observed 1430-1730 IST peak; (ii) Over Western Ghats and Burmese mountains, the model simulates a diurnal rainfall peak at 1430 IST, as opposed to the observed peak of 1430-1730 IST; (iii) Over Sumatra, both model and observations show a diurnal peak at 1730 IST; (iv) The observed southward propagating diurnal rainfall bands over BoB are weakly simulated by WRF. Besides the diurnal cycle of rainfall, the mean spatial pattern of total rainfall and its partitioning between the convective and stratiform components, are also well simulated. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over CI and BoB. While, the 54km and 18km simulations were conducted for the whole of July, 2006, the 6km simulation was carried out for the period 18 - 24 July, 2006. The results of our coarse- and fine-scale numerical simulations of the diurnal cycle of monsoon rainfall will be discussed.

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The swirling colors of aurorae, familiar to many in polar communities, can occasionally be seen at middle latitudes in locations such as southern Canada and central Europe. But in rare instances, aurorae can even be seen in the tropics. On 6 February 1872, news of the sighting of one such aurora was carried by the Times of India newspaper. The aurora occurred on 4 February 1872 and, as noted, was also observed over the Middle East.

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In this study, we analyse simultaneous measurements (at 50 Hz) of velocity at several heights and shear stress at the surface made during the Utah field campaign for the presence of ranges of scales, where distinct scale-to-scale interactions between velocity and shear stress can be identified. We find that our results are similar to those obtained in a previous study [Venugopal et al., 2003] (contrary to the claim in V2003, that the scaling relations might be dependent on Reynolds number) where wind tunnel measurements of velocity and shear stress were analysed. We use a wavelet-based scale-to-scale cross-correlation to detect three ranges of scales of interaction between velocity and shear stress, namely, (a) inertial subrange, where the correlation is negligible; (b) energy production range, where the correlation follows a logarithmic law; and (c) for scales larger than the boundary layer height, the correlation reaches a plateau.

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The influences of the springtime northern Indian biomass burning are shown for the first time over the central Himalayas by using three years (2007-2009) of surface and space based observations along with a radiative transfer model. Near-surface ozone, black carbon (BC), spectral aerosol optical depths (AODs) and the meteorological parameters are measured at a high altitude site Nainital (29.37 degrees N, 79.45 degrees E, 1958 m amsl) located in the central Himalayas. The satellite observations include the MODIS derived fire counts and AOD (0.55 mu m), and OMI derived tropospheric column NO(2), ultraviolet aerosol index and single scattering albedo. MODIS fire counts and BC observations are used to identify the fire-impacted periods (372 h during 2007-2009) and hence the induced enhancements in surface BC, AOD (0.5 mu m) and ozone are estimated to be 1802 ng m(-3) (similar to 145%), 0.3 (similar to 150%) and 19 ppbv (similar to 34%) respectively. Large enhancements (53-100%) are also seen in the satellite derived parameters over a 2 degrees x 2 degrees region around Nainital. The present analysis highlights the northern Indian biomass burning induced cooling at the surface (-27 W m(-2)) and top of the atmosphere (-8 W m(-2)) in the lesser polluted high altitude regions of the central Himalayas. This cooling leads to an additional atmospheric warming of 19 W m(-2) and increases the lower atmospheric heating rate by 0.8 K day(-1). These biomass burning induced changes over the central Himalayan atmosphere during spring may also lead to enhanced short-wave absorption above clouds and might have an impact on the monsoonal rainfall.

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We have demonstrated the synthesis of light-sensitive polyelectrolyte capsules (PECs) by utilizing a novel polyol reduction method and investigated its applicability as photosensitive drug delivery vehicle. The nanostructured capsules were prepared via layer by layer (LbL) assembly of poly(allylamine hydrochloride) (PAN) and dextran sulfate (DS) on silica particles followed by in-situ synthesis of silver nanoparticles (NPs). Capsules without silver NPs were permeable to low molecular weight (A(w), 479 g/mol) rhodamine but impermeable to higher molecular weight fluorescence labeled dextran (FITC-dextran). However, capsules synthesized with silver NPs showed porous morphology and were permeable to higher molecular weight (M(w) 70 kDa) FITC-dextran also. These capsules were loaded with FITC-dextran using thermal encapsulation method by exploiting temperature induced shrinking of the capsules. During heat treatment the porous morphology of the capsules transformed into smooth pore free structure which prevents the movement of dextran into bulk during the loading process. When these loaded capsules are exposed to laser pulses, the capsule wall ruptured, resulting in the release of the loaded drug/dye. The rupture of the capsules was dependent on particle size, laser pulse energy and exposure time. The release was linear with time when pulse energy of 400 mu J was used and burst release was observed when pulse energy increased to 600 mu J.

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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.