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  • 1
    Electronic Resource
    Electronic Resource
    Woodbury, NY : American Institute of Physics (AIP)
    Applied Physics Letters 72 (1998), S. 698-700 
    ISSN: 1077-3118
    Source: AIP Digital Archive
    Topics: Physics
    Notes: Scanning capacitance spectroscopy (SCS), a variant of scanning capacitance microscopy (SCM), is presented. By cycling the applied dc bias voltage between the tip and sample on successive scan lines, several points of the high-frequency capacitance–voltage characteristic C(V) of the metal–oxide–semiconductor capacitor formed by the tip and oxidized Si surface are sampled throughout an entire image. By numerically integrating dC/dV, spatially resolved C(V) curves are obtained. Physical interpretation of the C(V) curves is simpler than for a dC/dV image as in a single-voltage SCM image, so that the pn junction may be unambiguously localized inside a narrow and well-defined region. We show SCS data of a transistor in which the pn junction is delineated with a spatial resolution of ±30 nm. This observation is consistent with the conclusion that SCS can delineate the pn junction to a precision comparable to the Si depletion width, in other words, the actual size of the electrical pn junction. A physical model to explain the observed SCS data near the pn junction is presented. © 1998 American Institute of Physics.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1089-7550
    Source: AIP Digital Archive
    Topics: Physics
    Notes: The scanning capacitance microscope (SCM) is a carrier-sensitive imaging tool based upon the well-known scanning-probe microscope (SPM). As reported in Edwards et al. [Appl. Phys. Lett. 72, 698 (1998)], scanning capacitance spectroscopy (SCS) is a new data-taking method employing an SCM. SCS produces a two-dimensional map of the electrical pn junctions in a Si device and also provides an estimate of the depletion width. In this article, we report a series of microelectronics applications of SCS in which we image submicron transistors, Si bipolar transistors, and shallow-trench isolation structures. We describe two failure-analysis applications involving submicron transistors and shallow-trench isolation. We show a process-development application in which SCS provides microscopic evidence of the physical origins of the narrow-emitter effect in Si bipolar transistors. We image the depletion width in a Si bipolar transistor to explain an electric field-induced hot-carrier reliability failure. We show two sample geometries that can be used to examine different device properties. © 2000 American Institute of Physics.
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  • 3
    ISSN: 1077-3118
    Source: AIP Digital Archive
    Topics: Physics
    Notes: The maximum entropy method is presented in this letter as a highly interesting procedure for the investigation of high frequency noise properties of bulk semiconductors and electron devices at microscopic level. A Monte Carlo simulation of the hot electron velocity fluctuations in bulk GaAs has been performed to illustrate the efficiency and usefulness of this procedure. Comparisons with the most popular techniques presently used in Monte Carlo simulations of noise have also been performed. © 1998 American Institute of Physics.
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  • 4
    Publication Date: 2016-10-13
    Description: This is the second in a pair of papers in which the performance of Statistical Downscaling Methods (SDMs) is critically re-assessed with respect to their robust applicability in climate change studies. Whereas Part I focused on temperatures (Gutiérrez et al. 2013), the present manuscript deals with precipitation and considers an ensemble of twelve SDMs from the analog, weather typing and regression families. First, the performance of the methods is cross-validated considering reanalysis predictors, screening different geographical domains and predictor sets. Standard accuracy and distributional similarity scores, and a test for extrapolation capability are considered. The results are highly dependent on the predictor sets, with optimum configurations including information from middle tropospheric humidity. Second, a reduced ensemble of good performing SDMs is applied to four GCMs to properly assess the uncertainty of downscaled future climate projections. The results are compared with an ensemble of Regional Climate Models (RCMs) produced in the ENSEMBLES project. Generally, the mean signal is similar with both methodologies (with the exception of Summer, which is drier for the RCMs) but the uncertainty (spread) is larger for the SDM ensemble. Finally, the spread contribution of the GCM and SDM-derived components is assessed using a simple analysis of variance previously applied to the RCMs, obtaining larger interaction terms. Results show that the main contributor to the spread is the choice of the GCM, although the SDM dominates the uncertainty in some cases during Autumn and Summer due to the diverging projections from different families.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 5
    Publication Date: 2013-01-01
    Description: The performance of statistical downscaling (SD) techniques is critically reassessed with respect to their robust applicability in climate change studies. To this end, in addition to standard accuracy measures and distributional similarity scores, the authors estimate the robustness of the methods under warming climate conditions working with anomalous warm historical periods. This validation framework is applied to intercompare the performances of 12 different SD methods (from the analog, weather typing, and regression families) for downscaling minimum and maximum temperatures in Spain. First, a calibration of these methods is performed in terms of both geographical domains and predictor sets; the results are highly dependent on the latter, with optimum predictor sets including near-surface temperature data (in particular 2-m temperature), which appropriately discriminate cold episodes related to temperature inversion in the lower troposphere. Although regression methods perform best in terms of correlation, analog and weather generator approaches are more appropriate for reproducing the observed distributions, especially in case of wintertime minimum temperature. However, the latter two families significantly underestimate the temperature anomalies of the warm periods considered in this work. This underestimation is found to be critical when considering the warming signal in the late twenty-first century as given by a global climate model [the ECHAM5–Max Planck Institute (MPI) model]. In this case, the different downscaling methods provide warming values with differences in the range of 1°C, in agreement with the robustness significance values. Therefore, the proposed test is a promising technique for detecting lack of robustness in statistical downscaling methods applied in climate change studies.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 6
    Publication Date: 2015-05-12
    Description: This work shows that local-scale climate projections obtained by means of statistical downscaling are sensitive to the choice of reanalysis used for calibration. To this aim, a generalized linear model (GLM) approach is applied to downscale daily precipitation in the Philippines. First, the GLMs are trained and tested separately with two distinct reanalyses (ERA-Interim and JRA-25) using a cross-validation scheme over the period 1981–2000. When the observed and downscaled time series are compared, the attained performance is found to be sensitive to the reanalysis considered if climate change signal–bearing variables (temperature and/or specific humidity) are included in the predictor field. Moreover, performance differences are shown to be in correspondence with the disagreement found between the raw predictors from the two reanalyses. Second, the regression coefficients calibrated either with ERA-Interim or JRA-25 are subsequently applied to the output of a global climate model (MPI-ECHAM5) in order to assess the sensitivity of local-scale climate change projections (up to 2100) to reanalysis choice. In this case, the differences detected in present climate conditions are considerably amplified, leading to “delta-change” estimates differing by up to 35% (on average for the entire country) depending on the reanalysis used for calibration. Therefore, reanalysis choice is an important contributor to the uncertainty of local-scale climate change projections and, consequently, should be treated with as much care as other better-known sources of uncertainty (e.g., the choice of the GCM and/or downscaling method). Implications of the results for the entire tropics, as well as for the model output statistics downscaling approach are also briefly discussed.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2015-07-01
    Description: Limited area models (LAMs) are widely used tools to downscale the wind speed forecasts issued by general circulation models. However, only a few studies have systematically analyzed the value added by the LAMs to the coarser-resolution-model wind. The goal of the present work is to investigate how added value depends on the resolution of the driving global model. With this aim, the Weather Research and Forecasting (WRF) Model was used to downscale three different global datasets (GFS, ERA-Interim, and NCEP–NCAR) to a 9-km-resolution grid for a 1-yr period. Model results were compared with a large set of surface observations, including land station and offshore buoy data. Substantial biases were found at this resolution over mountainous terrain, and a slight modification to the subgrid orographic drag parameterization was introduced to alleviate the problem. It was found that, at this resolution, WRF is able to produce significant added value with respect to the NCEP–NCAR reanalysis and ERA-Interim but only a small amount of added value with respect to GFS forecasts. Results suggest that, as model resolution increases, traditional skill scores tend to saturate. Thus, adding value to high-resolution global models becomes significantly more difficult.
    Print ISSN: 1558-8424
    Electronic ISSN: 1558-8432
    Topics: Geography , Physics
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  • 8
    Publication Date: 2019-10-01
    Description: Climate predictions, from three weeks to a decade into the future, can provide invaluable information for climate-sensitive socioeconomic sectors, such as renewable energy, agriculture, or insurance. However, communicating and interpreting these predictions is not straightforward. Barriers hindering user uptake include a terminology gap between climate scientists and users, the difficulties of dealing with probabilistic outcomes for decision-making, and the lower skill of climate predictions compared to the skill of weather forecasts. This paper presents a gaming approach to break communication and understanding barriers through the application of the Weather Roulette conceptual framework. In the game, the player can choose between two forecast options, one that uses ECMWF seasonal predictions against one using climatology-derived probabilities. For each forecast option, the bet is spread proportionally to the predicted probabilities, either in a single year game or a game for the whole period of 33 past years. This paper provides skill maps of forecast quality metrics commonly used by the climate prediction community (e.g., ignorance skill score and ranked probability skill score), which in the game are linked to metrics easily understood by the business sector (e.g., interest rate and return on investment). In a simplified context, we illustrate how in skillful regions the economic benefits of using ECMWF predictions arise in the long term and are higher than using climatology. This paper provides an example of how to convey the usefulness of climate predictions and transfer the knowledge from climate science to potential users. If applied, this approach could provide the basis for a better integration of knowledge about climate anomalies into operational and managerial processes.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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