939 resultados para precipitation gradient


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A coupled-column liquid chromatographic method for the direct analysis of 14 urinary nucleosides is described. Efficient on-line clean-up and concentration of 14 nucleosides from urine samples were obtained by using a boronic acid-substituted silica column (40 turn x 4.0 mm I.D.) as the first column (Col-1) and a Hypersil ODS2 column (250 mm x 4.6 mm I.D.) as the second column (Col-2). The mobile phases applied consisted of 0.25 mol/L ammonium acetate (pH 8.5) on Col-1, and of 25 mmol/L potassium dihydrogen phosphate (pH 4.5) on Col-2, respectively. Determination of urinary nucleosides was performed on Col-2 column by using a linear gradient elution comprising 25 mmol/L potassium dihydrogen phosphate (pH 4.5) and methanol-water (60:40, v/v) with UV detection at 260 nm. Urinary nucleosides analysis can be carried out by this procedure in 50 min requiring only pH adjustment and the protein precipitation by centrifugation of urine samples. Calibration plots of 14 standard nucleosides showed excellent linearity (r > 0.995) and the limits of detection were at micromolar levels. Both of intra- and inter-day precisions of the method were better than 6.6% for direct determination of 14 nucleosides. The validated method was applied to quantify 14 nucleosides in 20 normal urines to establish reference ranges. (c) 2005 Elsevier B.V. All rights reserved.

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Jednym z wyników prognoz wykonywanych z zastosowaniem globalnych i regionalnych modeli klimatycznych jest odkrycie wysokiego prawdopodobieństwa wzrostu częstości oraz natężenia ekstremalnych opadów. Poznanie prawidłowości ich powtarzalności i zasięgu przestrzennego ma oczywiście bardzo duże znaczenie gospodarcze i społeczne. Dlatego, niezależnie od wprowadzania nowych technik pomiarowych należy dokonywać analizy i reinterpretacji archiwalnych danych, korzystając z możliwości stwarzanych przez rozwój GIS. Głównym celem opracowania jest analiza prawidłowości przestrzennej i czasowej zmienności miesięcznych oraz rocznych maksymalnych dobowych sum opadów (MSDO) z lat 1956-1980, z obszaru Polski. W pracy wykorzystano nowe w geografii polskiej metody geostatystyczne. Do publikacji dołączono dysk DVD ze źródłową bazą danych i najważniejszymi wynikami w postaci numerycznej i kartograficznej.

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The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L»l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (~25-km grid spacing) to the same resolution as the NCEP stage IV products (~4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied. © 2010 American Meteorological Society.

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© 2014, Springer-Verlag Berlin Heidelberg.This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical–extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the modeled precipitation biases over the SE US. In conclusion, our study demonstrates that the NASH western ridge is an important factor responsible for the RCM skill in simulating SE US summer precipitation. Furthermore, the improvements in the PBL parameterizations for the Gulf of Mexico might help advance RCM skill in representing the NASH western ridge circulation and summer precipitation over the SE US.

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© 2014, Springer-Verlag Berlin Heidelberg.The frequency and severity of extreme events are tightly associated with the variance of precipitation. As climate warms, the acceleration in hydrological cycle is likely to enhance the variance of precipitation across the globe. However, due to the lack of an effective analysis method, the mechanisms responsible for the changes of precipitation variance are poorly understood, especially on regional scales. Our study fills this gap by formulating a variance partition algorithm, which explicitly quantifies the contributions of atmospheric thermodynamics (specific humidity) and dynamics (wind) to the changes in regional-scale precipitation variance. Taking Southeastern (SE) United States (US) summer precipitation as an example, the algorithm is applied to the simulations of current and future climate by phase 5 of Coupled Model Intercomparison Project (CMIP5) models. The analysis suggests that compared to observations, most CMIP5 models (~60 %) tend to underestimate the summer precipitation variance over the SE US during the 1950–1999, primarily due to the errors in the modeled dynamic processes (i.e. large-scale circulation). Among the 18 CMIP5 models analyzed in this study, six of them reasonably simulate SE US summer precipitation variance in the twentieth century and the underlying physical processes; these models are thus applied for mechanistic study of future changes in SE US summer precipitation variance. In the future, the six models collectively project an intensification of SE US summer precipitation variance, resulting from the combined effects of atmospheric thermodynamics and dynamics. Between them, the latter plays a more important role. Specifically, thermodynamics results in more frequent and intensified wet summers, but does not contribute to the projected increase in the frequency and intensity of dry summers. In contrast, atmospheric dynamics explains the projected enhancement in both wet and dry summers, indicating its importance in understanding future climate change over the SE US. The results suggest that the intensified SE US summer precipitation variance is not a purely thermodynamic response to greenhouse gases forcing, and cannot be explained without the contribution of atmospheric dynamics. Our analysis provides important insights to understand the mechanisms of SE US summer precipitation variance change. The algorithm formulated in this study can be easily applied to other regions and seasons to systematically explore the mechanisms responsible for the changes in precipitation extremes in a warming climate.

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© 2015 Published by Elsevier B.V.Tree growth resources and the efficiency of resource-use for biomass production determine the productivity of forest ecosystems. In nutrient-limited forests, nitrogen (N)-fertilization increases foliage [N], which may increase photosynthetic rates, leaf area index (L), and thus light interception (IC). The product of such changes is a higher gross primary production and higher net primary production (NPP). However, fertilization may also alter carbohydrate partitioning from below- to aboveground, increasing aboveground NPP (ANPP). We analyzed effects of long-term N-fertilization on NPP, and that of long-term carbon storing organs (NPPS) in a Pinus sylvestris forest on sandy soil, a wide-ranging forest type in the boreal region. We based our analyses on a combination of destructive harvesting, consecutive mensuration, and optical measurements of canopy openness. After eight-year fertilization with a total of 70gNm-2, ANPP was 27±7% higher in the fertilized (F) relative to the reference (R) stand, but although L increased relative to its pre-fertilization values, IC was not greater than in R. On the seventh year after the treatment initiation, the increase of ANPP was matched by the decrease of belowground NPP (78 vs. 92gCm-2yr-1; ~17% of NPP) and, given the similarity of IC, suggests that the main effect of N-fertilization was changed carbon partitioning rather than increased canopy photosynthesis. Annual NPPS increased linearly with growing season temperature (T) in both treatments, with an upward shift of 70.2gCm-2yr-1 by fertilization, which also caused greater amount of unexplained variation (r2=0.53 in R, 0.21 in F). Residuals of the NPPS-T relationship of F were related to growing season precipitation (P, r2=0.48), indicating that T constrains productivity at this site regardless of fertility, while P is important in determining productivity where N-limitation is alleviated. We estimated that, in a growing season average T (11.5±1.0°C; 33-year-mean), NPPS response to N-fertilization will be nullified with P 31mm less than the mean (325±85mm), and would double with P 109mm greater than the mean. These results suggest that inter-annual variation in climate, particularly in P, may help explaining the reported large variability in growth responses to fertilization of pine stands on sandy soils. Furthermore, forest management of long-rotation systems, such as those of boreal and northern temperate forests, must consider the efficiency of fertilization in terms of wood production in the context of changes in climate predicted for the region.

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MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

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In high intensity and high gradient magnetic fields the volumetric force on diamagnetic material, such as water, leads to conditions very similar to microgravity in a terrestrial laboratory. In principle, this opens the possibility to determine material properties of liquid samples without wall contact, even for electrically non-conducting materials. In contrast, AC field levitation is used for conductors, but then terrestrial conditions lead to turbulent flow driven by Lorentz forces. DC field damping of the flow is feasible and indeed practiced to allow property measurements. However, the AC/DC field combination acts preferentially on certain oscillation modes and leads to a shift in the droplet oscillation spectrum.What is the cause? A nonlinear spectral numerical model is presented, to address these problems

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In high intensity and high gradient magnetic fields the volumetric force on diamagnetic material, such as water, leads to conditions very similar to microgravity in a terrestrial laboratory. In principle, this opens the possibility to determine material properties of liquid samples without wall contact, even for electrically non-conducting materials. In contrast, AC field levitation is used for conductors, but then terrestrial conditions lead to turbulent flow driven by Lorentz forces. DC field damping of the flow is feasible and indeed practiced to allow property measurements. However, the AC/DC field combination acts preferentially on certain oscillation modes and leads to a shift in the droplet oscillation spectrum.What is the cause? A nonlinear spectral numerical model is presented, to address these problems.

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Lime is a preferred precipitant for the removal of heavy metals from industrial wastewater due to its relatively low cost. To reduce heavy metal concentration to an acceptable level for discharge, in this work, fly ash was added as a seed material to enhance lime precipitation and the suspension was exposed to CO2 gas. The fly ash-lime-carbonation treatment increased the particle size of the precipitate and significantly improved sedimentation of sludge and the efficiency of heavy metal removal. The residual concentrations of chromium, copper, lead and zinc in effluents can be reduced to (mg L-1) 0.08, 0.14, 0.03 and 0.45, respectively. Examination of the precipitates by XRD and thermal analysis techniques showed that calcium-heavy metal double hydroxides and carbonates were present. The precipitate agglomerated and hardened naturally, facilitating disposal without the need for additional solidification/stabilization measures prior to landfill. It is suggested that fly ash, lime and CO2, captured directly from flue gas, may have potential as a method for wastewater treatment. This method could allow the ex-situ sequestration of CO2, particularly where flue-gas derived CO2 is available near wastewater treatment facilities. (C) 2009 Elsevier Ltd. All rights reserved.