Multi-parameter uncertainty analysis of a bifurcation point

Parameter uncertainty analysis of climate models has become a standard approach for model validation and testing their sensitivity. Here we present a novel approach that allows one to estimate the robustness of a bifurcation point in a multi-parameter space. In this study we investigate a box model of the Indian summer monsoon that exhibits a saddle-node bifurcation against those parameters that govern the heat balance of the system. The bifurcation brings about a change from a wet summer monsoon regime to a regime that is characterised by low precipitation. To analyse the robustness of the bifurcation point itself and its location in parameter space, we perform a multi-parameter uncertainty analysis by applying qualitative, Monte Carlo and deterministic methods that are provided by a multi-run simulation environment. Our results show that the occurrence of the bifurcation point is robust over a wide range of parameter values. The position of the bifurcation, however, is found to be sensitive on these specific parameter choices

Advanced technology for a satellite multichannel demultiplexer/demodulator

Satellite on-board processing is needed to efficiently service multiple users while at the same time minimizing earth station complexity. The processing satellite receives a wideband uplink at 30 GHz and down-converts it to a suitable intermediate frequency. A multichannel demultiplexer then separates the composite signal into discrete channels. Each channel is then demodulated by bulk demodulators, with the baseband signals routed to the downlink processor for retransmission to the receiving earth stations. This type of processing circumvents many of the difficulties associated with traditional bent-pipe repeater satellites. Uplink signal distortion and interference are not retransmitted on the downlink. Downlink power can be allocated in accordance with user needs, independent of uplink transmissions. This allows the uplink users to employ different data rates as well as different modulation and coding schemes. In addition, all downlink users have a common frequency standard and symbol clock on the satellite, which is useful for network synchronization in time division multiple access schemes. The purpose of this program is to demonstrate the concept of an optically implemented multichannel demultiplexer (MCD). A proof-of-concept (POC) model has been developed which has the ability to receive a 40 MHz wide composite signal consisting of up to 1000 40 kHz QPSK modulated channels and perform the demultiplexing process. In addition a set of special test equipment (STE) has been configured to evaluate the performance of the POC model. The optical MCD is realized as an acousto-optic spectrum analyzer utilizing the capability of Bragg cells to perform the required channelization. These Bragg cells receive an optical input from a laser source and an RF input (the signal). The Bragg interaction causes optical output diffractions at angles proportional to the RF input frequency. These discrete diffractions are optically detected and output to individual demodulators for baseband conversion. Optimization of the MCD design was conducted in order to achieve a compromise between two opposing sources of signal degradation: adjacent channel interference and intersymbol interference. The system was also optimized to allow simple, inexpensive ground stations communications with the MCD. These design goals led to the realization of a POC MCD which demonstrates the demultiplexing function with minimal signal degradation. Performance evaluation results using the STE equipment indicate that the dynamic range of the demultiplexer in the presence of adjacent and multiple channel loading is 40 - 50 dB. Measured bit error rate (BER) probabilities varied from the predicted theoretical results by one dB or less. The performance of the proof-of-concept model indicate that the development of a space qualified optically implemented MCD are feasible. The advantages to such an implementation include reduced size, weight and power and increased reliability when compared with electronic approaches. All of these factors are critical to on-board satellite processors. Further optimization can be conducted which trade ground station complexity and MCD performance to achieve desired system results

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: Validation and parameter optimization

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower troposphere mass flux show good results in particular in the Northern Hemisphere. In the Southern Hemisphere, the model tends to produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation. We discuss possible reasons for these model biases as well as planned future model improvements and applications

Remote Ischemic Preconditioning Neither Improves Survival nor Reduces Myocardial or Kidney Injury in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI)

BACKGROUND: Peri-interventional myocardial injury occurs frequently during transcatheter aortic valve implantation (TAVI). We assessed the effect of remote ischemic preconditioning (RIPC) on myocardial injury, acute kidney injury (AKIN) and 6-month mortality in patients undergoing TAVI. METHODS: We performed a prospective single-center controlled trial. Sixty-six patients treated with RIPC prior to TAVI were enrolled in the study and were matched to a control group by propensity-score. RIPC was applied to the upper extremity using a conventional tourniquet. Myocardial injury was assessed using high-sensitive troponin-T (hsTnT), and kidney injury was assessed using serum creatinine levels. Data were compared with the Wilcoxon-Rank and McNemar tests. Mortality was analysed with the log-rank test. RESULTS: TAVI led to a significant rise of hsTnT across all patients (p < 0.001). No significant inter-group difference in maximum troponin release or areas-under-the-curve was detected. Medtronic CoreValve and Edwards Sapien valves showed similar peri-interventional troponin kinetics and patients receiving neither valve did benefit from RIPC. AKIN occurred in one RIPC patient and four non-RIPC patients (p = 0.250). No significant difference in 6-month mortality was observed. No adverse events related to RIPC were recorded. CONCLUSION: Our data do not show a beneficial role of RIPC in TAVI patients for cardio- or renoprotection, or improved survival

Reliability of regional climate model simulations of extremes and of long-term climate

We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling

Hard thermal loops for soft or collinear external momenta

We consider finite temperature 1-loop diagrams with hard loop momenta and an arbitrary number of external gauge fields when the external momenta are either soft, or near the light cone and nearly collinear with the loop momentum. We obtain a recursion relation for these diagrams which we translate into an equation for their generating functional. By integrating out the soft fields while keeping two collinear ones we find an integral equation, originally due to Arnold, Moore, and Yaffe, which sums the bremsstrahlung and pair annihilation contribution to the thermal photon production rate.Comment: 17 pages, title corrected, clarifying paragraph added to the appendix, version to appear in JHE

Effective theories for real-time correlations in hot plasmas

We discuss the sequence of effective theories needed to understand the qualitative, and quantitative, behavior of real-time correlators in ultra-relativistic plasmas. We analyze in detail the case where A is a gauge-invariant conserved current. This case is of interest because it includes a correlation recently measured in lattice simulations of classical, hot, SU(2)-Higgs gauge theory. We find that simple perturbation theory, free kinetic theory, linearized kinetic theory, and hydrodynamics are all needed to understand the correlation for different ranges of time. We emphasize how correlations generically have power-law decays at very large times due to non-linear couplings to long-lived hydrodynamic modes.Comment: 28 pages, Latex, uses revtex, epsf macro packages [Revised version: t -> sqrt{t} in a few typos on p. 10.

The hard X-ray Photon Single-Shot Spectrometer of SwissFEL - Initial characterization

SwissFEL requires the monitoring of the photon spectral distribution at a repetition rate of 100 Hz for machine optimization and experiment online diagnostics. The Photon Single Shot Spectrometer has been designed for the photon energy range of 4 keV to 12 keV provided by the Aramis beamline. It is capable of measuring the spectrum in a non-destructive manner, with an energy resolution of Δ E/E = (2-5) × 10-5 over a bandwidth of 0.5% on a shot-to-shot basis. This article gives a detailed description about the technical challenges, structures, and considerations when building such a device, and to further enhance the performance of the spectrometer

High-resolution soft X-ray beamline ADRESS at the Swiss Light Source for resonant inelastic X-ray scattering and angle-resolved photoelectron spectroscopies

Concepts and technical realization of the high-resolution soft X-ray beamline ADRESS at the Swiss Light Source are described. Optimization of the optical scheme for high resolution and photon flux as well as diagnostics tools and alignment strategies are discussed

Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe

Forest management requires prediction of forest growth, but there is no general agreement about which models best predict growth, how to quantify model parameters, and how to assess the uncertainty of model predictions. In this paper, we show how Bayesian calibration (BC), Bayesian model comparison (BMC) and Bayesian model averaging (BMA) can help address these issues. We used six models, ranging from simple parameter-sparse models to complex process-based models: 3PG, 4C, ANAFORE, BASFOR, BRIDGING and FORMIND. For each model, the initial degree of uncertainty about parameter values was expressed in a prior probability distribution. Inventory data for Scots pine on tree height and diameter, with estimates of measurement uncertainty, were assembled for twelve sites, from four countries: Austria, Belgium, Estonia and Finland. From each country, we used data from two sites of the National Forest Inventories (NFIs), and one Permanent Sample Plot (PSP). The models were calibrated using the NFI-data and tested against the PSP-data. Calibration was done both per country and for all countries simultaneously, thus yielding country-specific and generic parameter distributions. We assessed model performance by sampling from prior and posterior distributions and comparing the growth predictions of these samples to the observations at the PSPs. We found that BC reduced uncertainties strongly in all but the most complex model. Surprisingly, country-specific BC did not lead to clearly better within-country predictions than generic BC. BMC identified the BRIDGING model, which is of intermediate complexity, as the most plausible model before calibration, with 4C taking its place after calibration. In this BMC, model plausibility was quantified as the relative probability of a model being correct given the information in the PSP-data. We discuss how the method of model initialisation affects model performance. Finally, we show how BMA affords a robust way of predicting forest growth that accounts for both parametric and model structural uncertainty