87 resultados para Calibration coefficients


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High-resolution, well-calibrated records of lake sediments are critically important for quantitative climate reconstructions, but they remain a methodological and analytical challenge. While several comprehensive paleotemperature reconstructions have been developed across Europe, only a few quantitative high-resolution studies exist for precipitation. Here we present a calibration and verification study of lithoclastic sediment proxies from proglacial Lake Oeschinen (46°30′N, 7°44′E, 1,580 m a.s.l., north–west Swiss Alps) that are sensitive to rainfall for the period AD 1901–2008. We collected two sediment cores, one in 2007 and another in 2011. The sediments are characterized by two facies: (A) mm-laminated clastic varves and (B) turbidites. The annual character of the laminae couplets was confirmed by radiometric dating (210Pb, 137Cs) and independent flood-layer chronomarkers. Individual varves consist of a dark sand-size spring-summer layer enriched in siliciclastic minerals and a lighter clay-size calcite-rich winter layer. Three subtypes of varves are distinguished: Type I with a 1–1.5 mm fining upward sequence; Type II with a distinct fine-sand base up to 3 mm thick; and Type III containing multiple internal microlaminae caused by individual summer rainstorm deposits. Delta-fan surface samples and sediment trap data fingerprint different sediment source areas and transport processes from the watershed and confirm the instant response of sediment flux to rainfall and erosion. Based on a highly accurate, precise and reproducible chronology, we demonstrate that sediment accumulation (varve thickness) is a quantitative predictor for cumulative boreal alpine spring (May–June) and spring/summer (May–August) rainfall (rMJ = 0.71, rMJJA = 0.60, p < 0.01). Bootstrap-based verification of the calibration model reveals a root mean squared error of prediction (RMSEPMJ = 32.7 mm, RMSEPMJJA = 57.8 mm) which is on the order of 10–13 % of mean MJ and MJJA cumulative precipitation, respectively. These results highlight the potential of the Lake Oeschinen sediments for high-resolution reconstructions of past rainfall conditions in the northern Swiss Alps, central and eastern France and south-west Germany.

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Water-conducting faults and fractures were studied in the granite-hosted A¨ spo¨ Hard Rock Laboratory (SE Sweden). On a scale of decametres and larger, steeply dipping faults dominate and contain a variety of different fault rocks (mylonites, cataclasites, fault gouges). On a smaller scale, somewhat less regular fracture patterns were found. Conceptual models of the fault and fracture geometries and of the properties of rock types adjacent to fractures were derived and used as input for the modelling of in situ dipole tracer tests that were conducted in the framework of the Tracer Retention Understanding Experiment (TRUE-1) on a scale of metres. After the identification of all relevant transport and retardation processes, blind predictions of the breakthroughs of conservative to moderately sorbing tracers were calculated and then compared with the experimental data. This paper provides the geological basis and model calibration, while the predictive and inverse modelling work is the topic of the companion paper [J. Contam. Hydrol. 61 (2003) 175]. The TRUE-1 experimental volume is highly fractured and contains the same types of fault rocks and alterations as on the decametric scale. The experimental flow field was modelled on the basis of a 2D-streamtube formalism with an underlying homogeneous and isotropic transmissivity field. Tracer transport was modelled using the dual porosity medium approach, which is linked to the flow model by the flow porosity. Given the substantial pumping rates in the extraction borehole, the transport domain has a maximum width of a few centimetres only. It is concluded that both the uncertainty with regard to the length of individual fractures and the detailed geometry of the network along the flowpath between injection and extraction boreholes are not critical because flow is largely one-dimensional, whether through a single fracture or a network. Process identification and model calibration were based on a single uranine breakthrough (test PDT3), which clearly showed that matrix diffusion had to be included in the model even over the short experimental time scales, evidenced by a characteristic shape of the trailing edge of the breakthrough curve. Using the geological information and therefore considering limited matrix diffusion into a thin fault gouge horizon resulted in a good fit to the experiment. On the other hand, fresh granite was found not to interact noticeably with the tracers over the time scales of the experiments. While fracture-filling gouge materials are very efficient in retarding tracers over short periods of time (hours–days), their volume is very small and, with time progressing, retardation will be dominated by altered wall rock and, finally, by fresh granite. In such rocks, both porosity (and therefore the effective diffusion coefficient) and sorption Kds are more than one order of magnitude smaller compared to fault gouge, thus indicating that long-term retardation is expected to occur but to be less pronounced.

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PURPOSE Positron emission tomography (PET)∕computed tomography (CT) measurements on small lesions are impaired by the partial volume effect, which is intrinsically tied to the point spread function of the actual imaging system, including the reconstruction algorithms. The variability resulting from different point spread functions hinders the assessment of quantitative measurements in clinical routine and especially degrades comparability within multicenter trials. To improve quantitative comparability there is a need for methods to match different PET∕CT systems through elimination of this systemic variability. Consequently, a new method was developed and tested that transforms the image of an object as produced by one tomograph to another image of the same object as it would have been seen by a different tomograph. The proposed new method, termed Transconvolution, compensates for differing imaging properties of different tomographs and particularly aims at quantitative comparability of PET∕CT in the context of multicenter trials. METHODS To solve the problem of image normalization, the theory of Transconvolution was mathematically established together with new methods to handle point spread functions of different PET∕CT systems. Knowing the point spread functions of two different imaging systems allows determining a Transconvolution function to convert one image into the other. This function is calculated by convolving one point spread function with the inverse of the other point spread function which, when adhering to certain boundary conditions such as the use of linear acquisition and image reconstruction methods, is a numerically accessible operation. For reliable measurement of such point spread functions characterizing different PET∕CT systems, a dedicated solid-state phantom incorporating (68)Ge∕(68)Ga filled spheres was developed. To iteratively determine and represent such point spread functions, exponential density functions in combination with a Gaussian distribution were introduced. Furthermore, simulation of a virtual PET system provided a standard imaging system with clearly defined properties to which the real PET systems were to be matched. A Hann window served as the modulation transfer function for the virtual PET. The Hann's apodization properties suppressed high spatial frequencies above a certain critical frequency, thereby fulfilling the above-mentioned boundary conditions. The determined point spread functions were subsequently used by the novel Transconvolution algorithm to match different PET∕CT systems onto the virtual PET system. Finally, the theoretically elaborated Transconvolution method was validated transforming phantom images acquired on two different PET systems to nearly identical data sets, as they would be imaged by the virtual PET system. RESULTS The proposed Transconvolution method matched different PET∕CT-systems for an improved and reproducible determination of a normalized activity concentration. The highest difference in measured activity concentration between the two different PET systems of 18.2% was found in spheres of 2 ml volume. Transconvolution reduced this difference down to 1.6%. In addition to reestablishing comparability the new method with its parameterization of point spread functions allowed a full characterization of imaging properties of the examined tomographs. CONCLUSIONS By matching different tomographs to a virtual standardized imaging system, Transconvolution opens a new comprehensive method for cross calibration in quantitative PET imaging. The use of a virtual PET system restores comparability between data sets from different PET systems by exerting a common, reproducible, and defined partial volume effect.

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Graphical presentation of regression results has become increasingly popular in the scientific literature, as graphs are much easier to read than tables in many cases. In Stata such plots can be produced by the -marginsplot- command. However, while -marginsplot- is very versatile and flexible, it has two major limitations: it can only process results left behind by -margins- and it can only handle one set of results at the time. In this article I introduce a new command called -coefplot- that overcomes these limitations. It plots results from any estimation command and combines results from several models into a single graph. The default behavior of -coefplot- is to plot markers for coefficients and horizontal spikes for confidence intervals. However, -coefplot- can also produce various other types of graphs. The capabilities of -coefplot- are illustrated in this article using a series of examples.

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coefplot plots results from estimation commands or Stata matrices. Results from multiple models or matrices can be combined in a single graph. The default behavior of coefplot is to draw markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce various other types of graphs.

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We measured the concentrations and isotopic compositions of He, Ne, and Ar in bulk samples and metal separates of 14 ordinary chondrite falls with long exposure ages and high metamorphic grades. In addition, we measured concentrations of the cosmogenic radionuclides 10Be, 26Al, and 36Cl in metal separates and in the nonmagnetic fractions of the selected meteorites. Using cosmogenic 36Cl and 36Ar measured in the metal separates, we determined 36Cl-36Ar cosmic-ray exposure (CRE) ages, which are shielding-independent and therefore particularly reliable. Using the cosmogenic noble gases and radionuclides, we are able to decipher the CRE history for the studied objects. Based on the correlation 3He/21Ne versus 22Ne/21Ne, we demonstrate that, among the meteorites studied, only one suffered significant diffusive losses (about 35%). The data confirm that the linear correlation 3He/21Ne versus 22Ne/21Ne breaks down at high shielding. Using 36Cl-36Ar exposure ages and measured noble gas concentrations, we determine 21Ne and 38Ar production rates as a function of 22Ne/21Ne. The new data agree with recent model calculations for the relationship between 21Ne and 38Ar production rates and the 22Ne/21Ne ratio, which does not always provide unique shielding information. Based on the model calculations, we determine a new correlation line for 21Ne and 38Ar production rates as a function of the shielding indicator 22Ne/21Ne for H, L, and LL chondrites with preatmospheric radii less than about 65 cm. We also calculated the 10Be/21Ne and 26Al/21Ne production rate ratios for the investigated samples, which show good agreement with recent model calculations.

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Middle atmospheric water vapour can be used as a tracer for dynamical processes. It is mainly measured by satellite instruments and ground-based microwave radiometers. Ground-based instruments capable of measuring middle-atmospheric water vapour are sparse but valuable as they complement satellite measurements, are relatively easy to maintain and have a long lifetime. MIAWARA-C is a ground-based microwave radiometer for middle-atmospheric water vapour designed for use on measurement campaigns for both atmospheric case studies and instrument intercomparisons. MIAWARA-C's retrieval version 1.1 (v1.1) is set up in a such way as to provide a consistent data set even if the instrument is operated from different locations on a campaign basis. The sensitive altitude range for v1.1 extends from 4 hPa (37 km) to 0.017 hPa (75 km). For v1.1 the estimated systematic error is approximately 10% for all altitudes. At lower altitudes it is dominated by uncertainties in the calibration, with altitude the influence of spectroscopic and temperature uncertainties increases. The estimated random error increases with altitude from 5 to 25%. MIAWARA-C measures two polarisations of the incident radiation in separate receiver channels, and can therefore provide two measurements of the same air mass with independent instrumental noise. The standard deviation of the difference between the profiles obtained from the two polarisations is in excellent agreement with the estimated random measurement error of v1.1. In this paper, the quality of v1.1 data is assessed for measurements obtained at two different locations: (1) a total of 25 months of measurements in the Arctic (Sodankylä, 67.37° N, 26.63° E) and (2) nine months of measurements at mid-latitudes (Zimmerwald, 46.88° N, 7.46° E). For both locations MIAWARA-C's profiles are compared to measurements from the satellite experiments Aura MLS and MIPAS. In addition, comparisons to ACE-FTS and SOFIE are presented for the Arctic and to the ground-based radiometer MIAWARA for the mid-latitude campaigns. In general, all intercomparisons show high correlation coefficients, confirming the ability of MIAWARA-C to monitor temporal variations of the order of days. The biases are generally below 13% and within the estimated systematic uncertainty of MIAWARA-C. No consistent wet or dry bias is identified for MIAWARA-C. In addition, comparisons to the reference instruments indicate the estimated random error of v1.1 to be a realistic measure of the random variation on the retrieved profile between 45 and 70 km.

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The reliability of millimeter and sub-millimeter wave radiometer measurements is dependent on the accuracy of the loads they employ as calibration targets. In the recent past on-board calibration loads have been developed for a variety of satellite remote sensing instruments. Unfortunately some of these have suffered from calibration inaccuracies which had poor thermal performance of the calibration target as the root cause. Stringent performance parameters of the calibration target such as low reflectivity, high temperature uniformity, low mass and low power consumption combined with low volumetric requirements remain a challenge for the space instrument developer. In this paper we present a novel multi-layer absorber concept for a calibration load which offers an excellent compromise between very good radiometric performance and temperature uniformity and the mass and volumetric constraints required by space-borne calibration targets.

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The aim of this study was to analyse the effects of climatic factors (i.e. monthly mean temperature and total precipitation) on radial growth (earlywood width, latewood width, and total ringwidth) and on latewood stable carbon isotope composition in a pedunculate oak (Quercus robur L) stand in northeastern Hungary. Earlywood widths showed the weakest common variance and lack of statistically significant relationship to monthly precipitation and temperature. Latewood width showed the strongest common chronological signal. Correlation analysis with the monthly climate series pointed out the strongest positive/negative correlation with June precipitation for latewood width/stable carbon isotope ratio. These parameters shared the strongest climatic response also for seasonal scale since the highest correlation coefficients, 0.49 and -0.62 for latewood width and stable carbon isotope ratio, respectively, were obtained for both with a 10-month precipitation total (from previous November to current August of the growing season). A combined parameter, derived as difference between latewood width and stable carbon isotope indices showed improved statistical relationship compared to the hydroclimatic calibration target both for local and regional spatial scales. Spatial correlation analysis indicated that the hydroclimatic signal encoded in these moisture sensitive tree-ring parameters from Bakta Forest is expected to be representative for the northeastern Carpathians and for the large part of the Great Hungarian Plain. In addition, the hydroclimatic signal of latewood width chronology was compared to three independent records. Results showed that neither the strength nor the rank of the similarity of the local hydroclimate signals were stable throughout the past two centuries. Future palaeo(hydro)climatological efforts targeting the Carpathian(-Balkan) region are recommended to track carefully the spatial domains for which a given, local, proxy-derived hydroclimate reconstruction might provide useful information.