47 resultados para STRATIFORM


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The distinction between convective and stratiform precipitation profiles around various precipitating systems existent in tropical regions is very important to the global atmospheric circulation, which is extremely sensitive to vertical latent heat distribution. In South America, the convective activity responds to the Intraseasonal Oscillation (IOS). This paper analyzes a disdrometer and a radar profiler data, installed in the Ji-Paraná airport, RO, Brazil, for the field experiment WETAMC/LBA & TRMM/LBA, during January and February of 1999. The microphysical analysis of wind regimes associated with IOS showed a large difference in type, size and microphysical processes of hydrometeor growth in each wind regime: easterly regimes had more turbulence and consequently convective precipitation formation, and westerly regimes had a more stratiform precipitation formation.

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Abstract. The electrification of stratiform clouds has is little investigated in comparison with thunderstorms and fair weather atmospheric electricity. Theory indicates that, at the upper and lower horizontal boundaries of layer clouds, charging will arise from vertical flow of cosmogenic ions in the global atmospheric electric circuit. Charge is transferred to droplets and particles, affecting cloud microphysical processes such as collision and droplet activation. Due to the lack of in-situ measurements, the magnitude and distribution of charge in stratiform clouds is not well known. A sensitive, inexpensive, balloon borne charge sensor has been developed to make in-situ measurements of edge charging in stratiform cloud using a standard meteorological radiosonde system. The charge sensor has now been flown through over 20 stratiform clouds and frequently detected charge up to 200 pC m-3 near cloud edges. These results are compared with measurements from the same sensor used to investigate charge in particle layers, such as volcanic ash from the Eyjafjallajökull eruption, and Saharan dust in the Cape Verde Isles. 1.

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The near-real time retrieval of low stratiform cloud (LSC) coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR) data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV). Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS) cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.

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É apresentado um estudo sobre sistemas convectivos linearmente organizados e observados por um radar meteorológico banda-C na região semi-árida do Nordeste do Brasil. São analisados três dias (27 a 29) de março de 1985, com ênfase na investigação do papel desempenhado por fatores locais e de grande escala no desenvolvimento dos sistemas. No cenário de grande escala, a área de cobertura do radar foi influenciada por um cavado de ar superior austral no dia 27 e por um vórtice ciclônico de altos níveis no dia 29. A convergência de umidade próxima à superfície favoreceu a atividade convectiva nos dias 27 e 29, enquanto que divergência de umidade próxima à superfície inibiu a atividade convectiva no dia 28. No cenário de mesoescala, foi observado que o aquecimento diurno é um fator importante para a formação de células convectivas, somando-se a ele o papel determinante da orografia na localização dos ecos. De maneira geral, as imagens de radar mostram os sistemas convectivos linearmente organizados em áreas elevadas e núcleos convectivos intensos envolvidos por uma área de precipitação estratiforme. Os resultados indicam que convergência do fluxo de umidade em grande escala e aquecimento radiativo, são fatores determinantes na evolução e desenvolvimento dos ecos na área de estudo.

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This article deals with the scavenging processes modeling of the particulate sulfate and the gas sulfur dioxide, emphasizing the synoptic conditions at different sampling sites in order to verify the domination of the in-cloud or below-cloud scavenging processes in the Metropolitan Area of São Paulo (RMSP). Three sampling sites were chosen: GV (Granja Viana) at RMSP surroundings, IAG-USP and Mackenzie (RMSP center). Basing on synoptic conditions, it was chosen a group of events where the numerical modeling, a simple scavenging model, was used. These synoptic conditions were usually convective cloud storms, which are usual at RMSP. The results show that the in-cloud processes were dominant (80%) for sulfate/sulfur dioxide scavenging processes, with below-cloud process indicating around 20% of the total. Clearly convective events, with total rainfall higher than 20 mm, are better modeled than the stratiform events, with correlation coefficient of 0.92. There is also a clear association with events presenting higher rainfall amount and the ratio between modeled and observed data set with correlation coefficient of 0.63. Additionally, the suburb sampling site, GV, as expected due to the pollution source distance, presents in general smaller amount of rainwater sulfate (modeled and observed) than the center sampling site, Mackenzie, where the characterization event explains partially the rainfall concentration differences.

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This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

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Samoborska Gora Mts. is situated within the westernmost part of the Zagorje-Mid-Transdanubian zone of the Internal Dinarides. The Samoborska Gora Mts. predominantly consists of Permian unmetamorphosed siliciclastic sediments and evaporites, overlain by Lower Triassic sediments. Rude mineralisation is hosted by Permian siliciclastic sediments, below gypsum and anhydrite strata. The central part of the deposit consists of a 1.5 km long stratabound mineralisation, grading laterally into ferruginous sandstone and protruding vertically into a gypsum-anhydrite layer. Siderite-polysulphide-barite-quartz veins are located below the stratabound mineralisation. The stratiform part of the deposit is situated above the stratabound and consists of haematite layer with barite concretions and veinlets. Late stage galena-barite veins overprint earlier types of mineralisation. The Rude ore deposit was generated by predominantly NaCl +/- CaCl(2)-H(2)O solutions. Detrital quartz from stratiform mineralisation contains fluid inclusions with salinities between 7 and 11 wt. % NaCl equ., homogenizing between 150 degrees C to 230 degrees C. Stratabound/siderite-polysulphide-barite-quartz vein type mineralisation was derived from solutions with salinities between 5 and 19 wt. % NaCl equ., homogenizing between 60 degrees C and 160 degrees C, while late stage galenabarite veins were precipitated from solutions with salinities between 11 and 16 wt. % NaCl equ., homogenizing between 100 degrees C to 140 degrees C. Fluid inclusion bulk leachate chemistry recorded Na(+)> Mg(2+)>K(+)>Ca(2+)>Li(+) and Cl-> SO(4)(2-) ions. Sulphur isotope composition of barites and overlying gypsum stems from Permian seawater sulphate, supported by increased Br(-) content, which follows successively the seawater evaporation line. The sulphur isotopic composition of sulphides varies between -0.2 and + 12.5 parts per thousand , as a result of thermal reduction of Permian marine sulphate. Ore-forming fluids were produced by hydrothermal convective cells (reflux brine model), and were derived primarily from Permian seawater, modified by evaporation and interaction with Permian sedimentary rocks. Rude deposits in Samoborska Gora Mts. may be declared as a prototype of the Permian siderite-polysulphide-barite deposits (products of rifting along the passive Gondwana margin), in the Inner Dinarides, and their equivalents extending northeastward into the Zagorje-Mid-Transdanubian Zone and the Gemerides, and southeastward to the Hellenide-Albanides.

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Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

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Weather radar observations are currently the most reliable method for remote sensing of precipitation. However, a number of factors affect the quality of radar observations and may limit seriously automated quantitative applications of radar precipitation estimates such as those required in Numerical Weather Prediction (NWP) data assimilation or in hydrological models. In this paper, a technique to correct two different problems typically present in radar data is presented and evaluated. The aspects dealt with are non-precipitating echoes - caused either by permanent ground clutter or by anomalous propagation of the radar beam (anaprop echoes) - and also topographical beam blockage. The correction technique is based in the computation of realistic beam propagation trajectories based upon recent radiosonde observations instead of assuming standard radio propagation conditions. The correction consists of three different steps: 1) calculation of a Dynamic Elevation Map which provides the minimum clutter-free antenna elevation for each pixel within the radar coverage; 2) correction for residual anaprop, checking the vertical reflectivity gradients within the radar volume; and 3) topographical beam blockage estimation and correction using a geometric optics approach. The technique is evaluated with four case studies in the region of the Po Valley (N Italy) using a C-band Doppler radar and a network of raingauges providing hourly precipitation measurements. The case studies cover different seasons, different radio propagation conditions and also stratiform and convective precipitation type events. After applying the proposed correction, a comparison of the radar precipitation estimates with raingauges indicates a general reduction in both the root mean squared error and the fractional error variance indicating the efficiency and robustness of the procedure. Moreover, the technique presented is not computationally expensive so it seems well suited to be implemented in an operational environment.

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The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic way.

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Gold in the quartz-pebble conglomerates of the late Archean Witwatersrand Basin, South Africa, is often intimately associated with carbonaceous matter of organic/biogenic origin which occurs in the form of stratiform carbon seams and paragenetically late bitumen nodules. Both carbon forms are believed to be formed by solidification of migrating hydrocarbons. This paper presents bulk and molecular chemical and stable carbon isotope data for the carbonaceous matter, all of which are used to provide a clue to the source of the hydrocarbons. These data are compared with those from intra-basinal shales and overlying dolostone of the Transvaal Supergroup. The delta C-13 values of the extracts from the Witwatersrand carbonaceous material show small differences (up to 2.4 parts per thousand) compared to the associated insoluble organic matter. This suggests that the auriferous rocks were stained by mobile hydrocarbons produced by thermal and oxidative alteration of indigenous bitumens, a contribution from hydrocarbons derived from intra-basinal Witwatersrand shales cannot be excluded. Individual aliphatic hydrocarbons of the various carbonaceous materials were subjected to compound specific isotope analysis using on-line gas chromatography/combustion/stable isotope ratio mass spectrometry (GC/C/IRMS). The limited variability of the molecular parameters and uniform delta C-13 values of individual n-alkanes (-31.1 +/- 1.7 parts per thousand) and isoprenoids (-30.7 +/- 1.1 parts per thousand) in the Witwatersrand samples exclude the mixing of oils from different sources. Carbonaceous matter in the dolostones shows distinctly different bulk and molecular isotope characteristics and thus cannot have been the source of the hydrocarbons in the Witwatersrand deposits. All the various forms of Witwatersrand carbon appear indigenous to the Witwatersrand Basin, and the differences between them are explained by variable, in general probably short (centimeter- to meter-scale) hydrocarbon migration during diagenesis and subsequent hydrothermal infiltration. (C) 2001 Elsevier Science B.V. All rights reserved.

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Flood simulation studies use spatial-temporal rainfall data input into distributed hydrological models. A correct description of rainfall in space and in time contributes to improvements on hydrological modelling and design. This work is focused on the analysis of 2-D convective structures (rain cells), whose contribution is especially significant in most flood events. The objective of this paper is to provide statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain). To achieve this purpose heavy rainfall events recorded between 1996 and 2000 have been analysed. By means of weather radar, and applying 2-D radar algorithms a distinction between convective and stratiform precipitation is made. These data are introduced and analyzed with a GIS. In a first step different groups of connected pixels with convective precipitation are identified. Only convective structures with an area greater than 32 km2 are selected. Then, geometric characteristics (area, perimeter, orientation and dimensions of the ellipse), and rainfall statistics (maximum, mean, minimum, range, standard deviation, and sum) of these structures are obtained and stored in a database. Finally, descriptive statistics for selected characteristics are calculated and statistical distributions are fitted to the observed frequency distributions. Statistical analyses reveal that the Generalized Pareto distribution for the area and the Generalized Extreme Value distribution for the perimeter, dimensions, orientation and mean areal precipitation are the statistical distributions that best fit the observed ones of these parameters. The statistical descriptors and the probability distribution functions obtained are of direct use as an input in spatial rainfall generators.

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The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.