56 resultados para Precipitation (Meteorology) -- Catalonia -- Begur


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The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

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The precipitation processes in dilute nitrogen alloys of titanium have been examined in detail by conventional transmission electron microscopy (CTEM) and high-resolution electron microscopy (HREM). The alloy Ti-2 at. pct N on quenching from its high-temperature beta phase field has been found to undergo early stages of decomposition. The supersaturated solid solution (alpha''-hcp) on decomposition gives rise to an intimately mixed, irresolvable product microstructure. The associated strong tweed contrast presents difficulties in understanding the characteristic features of the process. Therefore, HREM has been carried out with a view to getting a clear picture of the decomposition process. Studies on the quenched samples of the alloy suggest the formation of solute-rich zones of a few atom layers thick, randomly distributed throughout the matrix. On aging, these zones grow to a size beyond which the precipitate/matrix interfaces appear to become incoherent and the alpha' (tetragonal) product phase is seen distinctly. The structural details, the crystallography of the precipitation process, and the sequence of precipitation reaction in the system are illustrated.

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Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

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Part I (Manjunath et al., 1994, Chem. Engng Sci. 49, 1451-1463) of this paper showed that the random particle numbers and size distributions in precipitation processes in very small drops obtained by stochastic simulation techniques deviate substantially from the predictions of conventional population balance. The foregoing problem is considered in this paper in terms of a mean field approximation obtained by applying a first-order closure to an unclosed set of mean field equations presented in Part I. The mean field approximation consists of two mutually coupled partial differential equations featuring (i) the probability distribution for residual supersaturation and (ii) the mean number density of particles for each size and supersaturation from which all average properties and fluctuations can be calculated. The mean field equations have been solved by finite difference methods for (i) crystallization and (ii) precipitation of a metal hydroxide both occurring in a single drop of specified initial supersaturation. The results for the average number of particles, average residual supersaturation, the average size distribution, and fluctuations about the average values have been compared with those obtained by stochastic simulation techniques and by population balance. This comparison shows that the mean field predictions are substantially superior to those of population balance as judged by the close proximity of results from the former to those from stochastic simulations. The agreement is excellent for broad initial supersaturations at short times but deteriorates progressively at larger times. For steep initial supersaturation distributions, predictions of the mean field theory are not satisfactory thus calling for higher-order approximations. The merit of the mean field approximation over stochastic simulation lies in its potential to reduce expensive computation times involved in simulation. More effective computational techniques could not only enhance this advantage of the mean field approximation but also make it possible to use higher-order approximations eliminating the constraints under which the stochastic dynamics of the process can be predicted accurately.

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Homogeneous precipitation from solution by hydrolysis of urea at elevated temperatures (T=120 degrees C) yields novel ammonia-intercalated alpha-type hydroxide phases of the formula M(OH)(x)(NH3)(0.4)(H2O)(y)(NO3)(2-x) where x=2, y=0.68 for M=Ni and x=1.85, y=0 for M=Co. These triple-layered hexagonal phases (a=3.08+/-0.01 Angstrom, c=21.7+/-0.05 Angstrom) are more crystalline than similar phases obtained by chemical precipitation or electrosynthesis. This method can be adapted as a convenient chemical route to the bulk synthesis of alpha-hydroxides.

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Direct precipitation of fine powders of lead zirconate titanate (PZT) in the complete range of solid solution, is investigated under hydrothermal conditions, starting from lead oxide and titania/zirconia mixed gels. The perovskite phase is formed in the temperature range of 165 – 340°C. Sequence of the hydrothermal reactions is studied by identifying the intermediate phases. The initial formation of PbO: TiO2 solid solution is followed by the reaction of the same with the remaining mixed gels giving rise to X-ray amorphous PZT phase. Further, through crystallite growth, the X-ray crystalline PZT is formed. This method can be extended for the preparation of PLZT powder as well. The resulting powders are sinterable to high density ceramics.

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Fine powders of TiO2 (rutile) with high degree of crystallinity are formed from aqueous titanium oxychloride solution under hydrothermal conditions at 160–230°C and 15–100 kg/cm2 for 1–2 hours. The anatase phase is produced from the same medium when sulfate ion impurity is present, with Image . Both these fine powders are converted to BaTiO3, SrTiO3 or CaTiO3 when suspended in Ba(OH)2 or Sr(OH)2 solution or in an aqueous slurry of carbonate-free CaO with Image , at 180–280°C and 12–65 kg/cm2 for 4–8 hours. The resulting fine powders contain monocrystallites of the perovskite phase with 0.1–1.5 μm particle size.

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It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

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Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

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We investigate the ability of a global atmospheric general circulation model (AGCM) to reproduce observed 20 year return values of the annual maximum daily precipitation totals over the continental United States as a function of horizontal resolution. We find that at the high resolutions enabled by contemporary supercomputers, the AGCM can produce values of comparable magnitude to high quality observations. However, at the resolutions typical of the coupled general circulation models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, the precipitation return values are severely underestimated.

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We describe the synthesis and structure of Barium sulfate nanoparticles by precipitation method in the presence of water soluble inorganic stabilizing agent, sodium hexametaphosphate, (NaPO3)(6). The structural parameters were refined by the Rietveld refinement method using powder X-ray diffraction data. Barium sulfate nanoparticles were crystallized in the orthorhombic structure with space group Pbnm (No. 62) having the lattice parameters a = 7.215(1) (angstrom), b = 8.949(1) (angstrom) and c = 5.501 (1) (angstrom) respectively. Transmission electron microscopy study reveals that the nanoparticles are size range, 30-50 nm. Fourier transform infrared spectra showed distinct absorption due to the SO42- moiety at 1115 and 1084 cm(-1) indicating formation of barium sulfate nanoparticles free from the phosphate group from the stabilizer used in the synthesis. (C) 2009 Elsevier Ltd. All rights reserved.

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The mechanism of sub-microscopic precipitation in an Al-Zn-Mg alloy selected for its maximum response to ageing has been studied by a standardized oxide-replica technique in a 100 kV. Philips Electron Microscope. Contrary to earlier conclusions, examination of the oxide replicas has been shown to reveal details of the precipitation process almost as clearly as the thin-foil transmission technique. The reported formation of spherical Guinier-Preston zones followed by the development of a Widmanstaetten pattern of precipitated platelets has been confirmed. The zones have, however, been shown to grow into the platelets and not to dissolve in the matrix as reported earlier. The precipitation process has been correlated with the Hardness/Ageing Time curve and the structure of the precipitates has also been discussed.

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Precipitation involving mixing of two sets of reverse micellar solutions-containing a reactant and precipitant respectively-has been analyzed. Particle formation in such systems has been simulated by a Monte Carlo (MC) scheme (Li, Y.; Park, C. W. Langmuir 1999, 15, 952), which however is very restrictive in its approach. We have simulated particle formation by developing a general Monte Carlo scheme, using the interval of quiescence technique (IQ). It uses Poisson distribution with realistic, low micellar occupancies of reactants, Brownian collision of micelles with coalescence efficiency, fission of dimers with binomial redispersion of solutes, finite nucleation rate of particles with critical number of molecules, and instantaneous particle growth. With the incorporation of these features, the previous work becomes a special case of our simulation. The present scheme was then used to predict experimental data on two systems. The first is the experimental results of Lianos and Thomas (Chem. Phys. Lett. 1986, 125, 299, J. Colloid Interface Sci. 1987, 117, 505) on formation of CdS nanoparticles. They reported the number of molecules in a particle as a function of micellar size and reactant concentrations, which have been predicted very well. The second is on the formation of Fe(OH)(3) nanoparticles, reported by Li and Park. Our simulation in this case provides a better prediction of the experimental particle size range than the prediction of the authors. The present simulation scheme is general and can be applied to explain nanoparticle formation in other systems.