996 resultados para Pom-Pom model


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A three-dimensional ocean circulation model, called Princeton Ocean Model (POM), is employed to simulate tides and tidal currents in Liaodong Bay. The nested grid technique is adopted to improve the computation precision. Computed harmonic constants of M-1, M-2 tides at five tidal gauge stations and surface elevations at two oil platforms are compared with those observed, and show good agreements with them. Based on the calculated results, the co-amplitude and co-phase tag lines of nil and M-2 tidal constituents, the residual current field of M-2 constituent, tidal form, tidal Current ellipse and the moving style of tidal current are given. It is found that diurnal tidal constituents have no amphidromic point whereas semi-diurnal constituents have one in the region of interest. Meanwhile, some meaningful results are concluded and presented, which are conducive to a thorough knowledge of the characteristics of tides and tidal currents in the Liaodong Bay.

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Aquí hem aplicat el Princeton Ocean Model als embassaments de Sau i Boadella, situats a Catalunya, Espanya. Les simulacions s'han realitzat a l'estació d'estiu, quan la columna d'aigua està estratificada de forma contínua, i sota un règim de brisa amb velocitats de fins a 4 m/s. Basant-nos en aquestes simulacions hem analitzat el camp d'ones internes i comparat els resultats numèrics amb dades experimentals disponibles. El model reprodueix adequadament tots els modes observats en l'espectre de la velocitat i temperatura mesurades i ajuda a identificar els diferents modes. Les simulacions mostren la importància dels modes rotacionals en el camp d'ones internes dels embassaments estratificats. En el període estudiat, el radi de Rossby per l'embassament de Sau és de l'ordre de 100 m, que és varies vegades més petit que la amplitud de l'àrea lacustre de l'embassament, i el número de Rossby és de l'ordre de 0.1, corroborant la importancia de l'efecte de Coriolis.

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Particulate organic matter (POM) derived from permafrost soils and transported by the Lena River represents a quantitatively important terrestrial carbon pool exported to Laptev Sea sediments (next to POM derived from coastal erosion). Its fate in a future warming Arctic, i.e., its remobilization and remineralization after permafrost thawing as well as its transport pathways to and sequestration in marine sediments, is currently under debate. We present one of the first radiocarbon (14C) data sets for surface water POM within the Lena Delta sampled in the summers of 2009 - 2010 and spring 2011 (n = 30 samples). The bulk D14C values varied from -55 to -391 per mil translating into 14C ages of 395 to 3920 years BP. We further estimated the fraction of soil-derived POM to our samples based on (1) particulate organic carbon to particulate nitrogen ratios (POC : PN) and (2) on the stable carbon isotope (d13C) composition of our samples. Assuming that this phytoplankton POM has a modern 14C concentration, we inferred the 14C concentrations of the soil-derived POM fractions. The results ranged from -322 to -884 per mil (i.e., 3060 to 17 250 14C years BP) for the POC : PN-based scenario and from -261 to -944 per mil (i.e., 2370 to 23 100 14C years BP) for the d13C-based scenario. Despite the limitations of our approach, the estimated D14C values of the soil-derived POM fractions seem to reflect the heterogeneous 14C concentrations of the Lena River catchment soils covering a range from Holocene to Pleistocene ages better than the bulk POM D14C values. We further used a dual-carbon-isotope three-end-member mixing model to distinguish between POM contributions from Holocene soils and Pleistocene Ice Complex (IC) deposits to our soil-derived POM fraction. IC contributions are comparatively low (mean of 0.14) compared to Holocene soils (mean of 0.32) and riverine phytoplankton (mean of 0.55), which could be explained with the restricted spatial distribution of IC deposits within the Lena catchment. Based on our newly calculated soil-derived POM D14C values, we propose an isotopic range for the riverine soil-derived POM end member with D14C of -495 ± 153 per mil deduced from our d13C-based binary mixing model and d13C of -26.6 ± 1 per mil deduced from our data of Lena Delta soils and literature values. These estimates can help to improve the dual-carbon-isotope simulations used to quantify contributions from riverine soil POM, Pleistocene IC POM from coastal erosion, and marine POM in Siberian shelf sediments.

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Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.

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本文以吉林省公主岭“国家黑土肥力与肥料效益长期定位监测基地”的黑土为材料,研究长期施肥对黑土POM的分布及POM(FPOM和OPOM)中碳水化合物特性的影响,结果表明: 有机肥及有机肥与化肥配施显著提高了土壤中碳水化合物的含量,促进了植物来源的中性糖和真菌来源的氨基糖在土壤中的积累。在有机质含量较高的黑土上长期施用高量有机肥会出现养分过剩的现象。不同施肥处理下黑土有机质中中性糖的相对含量与不施肥相比无显著变化,氨基糖的相对含量则显著增加。随着有机肥施用量的增加,土壤中中性糖的含量也随之显著增加,而氨基糖则没有明显变化。 有机肥及有机肥与化肥配施能显著增加黑土中POM以及POM-C、POM-N和碳水化合物的含量,且均随有机肥施用量的增加而增加。各个处理中OPOM的碳、氮和碳水化合物含量远远高于FPOM。POM中各个单糖对施肥的响应与碳水化合物的总量基本一致。单施高量有机肥及有机肥与化肥配施均能显著提高POM中中性糖和氨基糖占有机质的比例,单施低量有机肥对POM中氨基糖和FPOM中中性糖占有机质的比例作用不明显,而能显著增加OPOM中中性糖占SOM的比例。在POM的中性糖中葡萄糖和木糖对SOM的贡献较大,氨基糖中氨基葡萄糖的贡献较大。OPOM中碳水化合物对SOM的贡献大于FPOM。FPOM中中性糖主要来源于植物,而OPOM中则主要来源于植物和微生物。在短期范围内,施肥并没有引起POM中两种来源氨基糖比例的显著变化,而从长期来看,有机肥处理却使POM中细菌源氨基糖的积累得到了加强。单施化肥对黑土有机质和黑土POM的含量以及二者中的碳、氮和碳水化合物的含量和组成均没有显著的影响。

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A Cu-Zn-Al methanol catalyst combined with HZSM-5 was used for dimethyl ether (DME) synthesis from a syngas containing nitrogen, which was produced by air-partial oxidation of methane (air-POM). Air-POM occurred at 850 degreesC, 0.8 MPa, CH4/air/H2O/CO2 ratio of 1/2.4/0.8/0.4 over a Ni-based catalyst modified by magnesia and lanthanum oxide with 96% CH4 conversion and constantly gave syngas with a H-2/CO ratio of 2/1 during a period of 450 h. The obtained N-2-containing syngas was used directly for DME synthesis. About 90% CO per-pass conversion, 78% DME selectivity and 70% DME yield could be achieved during 450 h stability testing under the pressure of 5.0 MPa. the temperature of 240 degreesC and the space velocity of 1000 h(-1). (C) 2002 Elsevier Science B. V. All rights reserved.

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Turbulence characteristics in the Indonesian seas on the horizontal scale of order of 100 km were calculated with a regional model of the Indonesian seas circulation in the area based on the Princeton Ocean Model (POM). As is well known, the POM incorporates the Mellor–Yamada turbulence closure scheme. The calculated characteristics are: twice the turbulence kinetic energy per unit mass, <i>q</i><sup>2</sup>; the turbulence master scale, &ell;; mixing coefficients of momentum, <i>K</i><sub>M</sub>; and temperature and salinity, <i>K</i><sub>H</sub>; etc. The analyzed turbulence has been generated essentially by the shear of large-scale ocean currents and by the large-scale wind turbulence. We focused on the analysis of turbulence around important topographic features, such as the Lifamatola Sill, the North Sangihe Ridge, the Dewakang Sill, and the North and South Halmahera Sea Sills. In general, the structure of turbulence characteristics in these regions turned out to be similar. For this reason, we have carried out a detailed analysis of the Lifamatola Sill region because dynamically this region is very important and some estimates of mixing coefficients in this area are available. <br><br> Briefly, the main results are as follows. The distribution of <i>q</i><sup>2</sup> is quite adequately reproduced by the model. To the north of the Lifamatola Sill (in the Maluku Sea) and to the south of the Sill (in the Seram Sea), large values of <i>q</i><sup>2</sup> occur in the deep layer extending several hundred meters above the bottom. The observed increase of <i>q</i><sup>2</sup> near the very bottom is probably due to the increase of velocity shear and the corresponding shear production of <i>q</i><sup>2</sup> very close to the bottom. The turbulence master scale, &ell;, was found to be constant in the main depth of the ocean, while &ell; rapidly decreases close to the bottom, as one would expect. However, in deep profiles away from the sill, the effect of topography results in the &ell; structure being unreasonably complicated as one moves towards the bottom. Values of 15 to 20 × 10<sup>&minus;4</sup> m<sup>2</sup> s<sup>-1</sup> were obtained for <i>K</i><sub>M</sub> and <i>K</i><sub>H</sub> in deep water in the vicinity of the Lifamatola Sill. These estimates agree well with basin-scale averaged values of 13.3 × 10<sup>&minus;4</sup> m<sup>2</sup> s<sup>-1</sup> found diagnostically for <i>K</i><sub>H</sub> in the deep Banda and Seram Seas (Gordon et al., 2003) and a value of 9.0 × 10<sup>&minus;4</sup> m<sup>2</sup> s<sup>-1</sup> found diagnostically for <i>K</i><sub>H</sub> for the deep Banda Sea system (van Aken et al., 1988). The somewhat higher simulated values can be explained by the presence of steep topography around the sill.

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The International Nusantara Stratification and Transport (INSTANT) program measured currents through multiple Indonesian Seas passages simultaneously over a three-year period (from January 2004 to December 2006). The Indonesian Seas region has presented numerous challenges for numerical modelers - the Indonesian Throughflow (ITF) must pass over shallow sills, into deep basins, and through narrow constrictions on its way from the Pacific to the Indian Ocean. As an important region in the global climate puzzle, a number of models have been used to try and best simulate this throughflow. In an attempt to validate our model, we present a comparison between the transports calculated from our model and those calculated from the INSTANT in situ measurements at five passages within the Indonesian Seas (Labani Channel, Lifamatola Passage, Lombok Strait, Ornbai Strait, and Timor Passage). Our Princeton Ocean Model (POM) based regional Indonesian Seas model was originally developed to analyze the influence of bottom topography on the temperature and salinity distributions in the Indonesian seas region, to disclose the path of the South Pacific Water from the continuation of the New Guinea Coastal Current entering the region of interest up to the Lifamatola Passage, and to assess the role of the pressure head in driving the ITF and in determining its total transport. Previous studies found that this model reasonably represents the general long-term flow (seasons) through this region. The INSTANT transports were compared to the results of this regional model over multiple timescales. Overall trends are somewhat represented but changes on timescales shorter than seasonal (three months) and longer than annual were not considered in our model. Normal velocities through each passage during every season are plotted. Daily volume transports and transport-weighted temperature and salinity are plotted and seasonal averages are tabulated.

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