Fundamental Sources Of Uncertainty Research Articles

A management strategy evaluation of the commercial sockeye salmon fishery in Bristol Bay, Alaska

Bristol Bay, Alaska, is home to the largest sockeye salmon (Oncorhynchus nerka) fishery in the world, harvesting an average of 25 million fish with an ex-vessel value exceeding US$100 million annually. Daily fishing effort is adaptively managed to achieve stock-specific escapement goals. Traditional methods for defining these goals relied on stock–recruitment analysis; however, this approach often ignores three fundamental sources of uncertainty: estimation error, implementation uncertainty, and time-varying recruitment dynamics. To compare escapement goal alternatives, we conducted a management strategy evaluation that simulated time-varying recruitment across production regimes and replicated the daily in-season management process. Results indicate (i) implementation uncertainty can be reasonably approximated with simple rules reflecting fishery managers’ daily decision process; (ii) despite implementation uncertainty, escapement goals are likely to be realized or exceeded, on average; and (iii) management strategies targeting escapement levels estimated by traditional methods to produce maximum sustainable yield may result in lower catch and greater variability in fishing opportunity compared with a strategy with defining high and low escapement goals that are targeted depending on assessed run size, which may maximize future catch while reducing the frequency of extremely low harvests.

Identification of the late Homerian Mulde Excursion at the base of the Salina Group (Michigan Basin, USA)

Constraining the age of strata is a fundamental source of uncertainty in the study of sedimentary rocks, particularly in restricted basins that generally lack index fossils. An illustrative example of this is the evaporite-bearing Salina Group in the Michigan Basin. Our integrated study of facies, paleontology, and stable isotope geochemistry from the base of the Salina Group in Wisconsin addresses long-standing chronostratigraphic uncertainty surrounding these units. Conodont samples from the basal boundary interval (Racine-Waubakee formation contact) produced non-diagnostic ‘disaster’ and ‘recovery’ faunas typical of both the Mulde (Homerian) and Lau (Ludfordian) events. Strontium isotope analysis (87Sr/86Sr) of these conodonts from five horizons just below the boundary yield values between 0.70844 and 0.70850 confirming a Homerian age. Multiple carbon isotope profiles through this interval confirm the presence of a 2.5–3‰ positive excursion. Cumulatively these data constrain the base of the Salina Group in Wisconsin to the Mulde Excursion interval (late Homerian). This integrated study provides a sound initial step towards a deeper understanding of the processes of Silurian evaporite formation in the Michigan Basin.

The ALHAMBRA survey: Estimation of the clustering signal encoded in the cosmic variance

The relative cosmic variance ($\sigma_v$) is a fundamental source of uncertainty in pencil-beam surveys and, as a particular case of count-in-cell statistics, can be used to estimate the bias between galaxies and their underlying dark-matter distribution. Our goal is to test the significance of the clustering information encoded in the $\sigma_v$ measured in the ALHAMBRA survey. We measure the cosmic variance of several galaxy populations selected with $B-$band luminosity at $0.35 \leq z < 1.05$ as the intrinsic dispersion in the number density distribution derived from the 48 ALHAMBRA subfields. We compare the observational $\sigma_v$ with the cosmic variance of the dark matter expected from the theory, $\sigma_{v,{\rm dm}}$. This provides an estimation of the galaxy bias $b$. The galaxy bias from the cosmic variance is in excellent agreement with the bias estimated by two-point correlation function analysis in ALHAMBRA. This holds for different redshift bins, for red and blue subsamples, and for several $B-$band luminosity selections. We find that $b$ increases with the $B-$band luminosity and the redshift, as expected from previous work. Moreover, red galaxies have a larger bias than blue galaxies, with a relative bias of $b_{\rm rel} = 1.4 \pm 0.2$. Our results demonstrate that the cosmic variance measured in ALHAMBRA is due to the clustering of galaxies and can be used to characterise the $\sigma_v$ affecting pencil-beam surveys. In addition, it can also be used to estimate the galaxy bias $b$ from a method independent of correlation functions.

Online Modified Greedy Algorithm for Storage Control Under Uncertainty

This paper studies the general problem of operating energy storage under uncertainty. Two fundamental sources of uncertainty are considered, namely the uncertainty in the unexpected fluctuation of the net demand process and the uncertainty in the locational marginal prices. We propose a very simple algorithm termed Online Modified Greedy (OMG) algorithm for this problem. A stylized analysis for the algorithm is performed, which shows that comparing to the optimal cost of the corresponding stochastic control problem, the sub-optimality of OMG is bounded and approaches zero in various scenarios. This suggests that, albeit simple, OMG is guaranteed to have good performance in some cases; and in other cases, OMG together with the sub-optimality bound can be used to provide a lower bound for the optimal cost. Such a lower bound can be valuable in evaluating other heuristic algorithms. For the latter cases, a semidefinite program is derived to minimize the sub-optimality bound of OMG. Numerical experiments are conducted to verify our theoretical analysis and to demonstrate the use of the algorithm.

Nuclear data sensitivity and uncertainty for the Canadian supercritical water-cooled reactor II: Full core analysis

Uncertainties in nuclear data are a fundamental source of uncertainty in reactor physics calculations. To determine their contribution to uncertainties in calculated reactor physics parameters, a nuclear data sensitivity and uncertainty study is performed on the Canadian supercritical water reactor (SCWR) concept. The nuclear data uncertainty contributions to the neutron multiplication factor keff are 6.31mk for the SCWR at the beginning of cycle (BOC) and 6.99mk at the end of cycle (EOC). Both of these uncertainties have a statistical uncertainty of 0.02mk. The nuclear data uncertainty contributions to Coolant Void Reactivity (CVR) are 1.0mk and 0.9mk for BOC and EOC, respectively, both with statistical uncertainties of 0.1mk. The nuclear data uncertainty contributions to other reactivity parameters range from as low as 3% of to as high as ten times the values of the reactivity coefficients. The largest contributors to the uncertainties in the reactor physics parameters are Pu-239, Th-232, H-2, and isotopes of zirconium.

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature.

HOW GOOD A CLOCK IS ROTATION? THE STELLAR ROTATION-MASS-AGE RELATIONSHIP FOR OLD FIELD STARS

The rotation-mass-age relationship offers a promising avenue for measuring the ages of field stars, assuming the attendant uncertainties to this technique can be well characterized. We model stellar angular momentum evolution starting with a rotation distribution from open cluster M37. Our predicted rotation-mass-age relationship shows significant zero-point offsets compared to an alternative angular momentum loss law and published gyrochronology relations. Systematic errors at the 30 percent level are permitted by current data, highlighting the need for empirical guidance. We identify two fundamental sources of uncertainty that limit the precision of rotation-based ages and quantify their impact. Stars are born with a range of rotation rates, which leads to an age range at fixed rotation period. We find that the inherent ambiguity from the initial conditions is important for all young stars, and remains large for old stars below 0.6 solar masses. Latitudinal surface differential rotation also introduces a minimum uncertainty into rotation period measurements and, by extension, rotation-based ages. Both models and the data from binary star systems 61 Cyg and alpha Cen demonstrate that latitudinal differential rotation is the limiting factor for rotation-based age precision among old field stars, inducing uncertainties at the ~2 Gyr level. We also examine the relationship between variability amplitude, rotation period, and age. Existing ground-based surveys can detect field populations with ages as old as 1-2 Gyr, while space missions can detect stars as old as the Galactic disk. In comparison with other techniques for measuring the ages of lower main sequence stars, including geometric parallax and asteroseismology, rotation-based ages have the potential to be the most precise chronometer for 0.6-1.0 solar mass stars.

A STUDY OF FUNDAMENTAL LIMITATIONS TO STATISTICAL DETECTION OF REDSHIFTED H I FROM THE EPOCH OF REIONIZATION

In this paper we explore for the first time the relative magnitudes of three fundamental sources of uncertainty, namely, foreground contamination, thermal noise and sample variance in detecting the HI power spectrum from the Epoch of Reionization (EoR). We derive limits on the sensitivity of a Fourier synthesis telescope to detect EoR based on its array configuration and a statistical representation of images made by the instrument. We use the Murchison Widefield Array (MWA) configuration for our studies. Using a unified framework for estimating signal and noise components in the HI power spectrum, we derive an expression for and estimate the contamination from extragalactic point-like sources in three-dimensional k-space. Sensitivity for EoR HI power spectrum detection is estimated for different observing modes with MWA. With 1000 hours of observing on a single field using the 128-tile MWA, EoR detection is feasible (S/N > 1 for $k\lesssim 0.8$ Mpc$^{-1}$). Bandpass shaping and refinements to the EoR window are found to be effective in containing foreground contamination, which makes the instrument tolerant to imaging errors. We find that for a given observing time, observing many independent fields of view does not offer an advantage over a single field observation when thermal noise dominates over other uncertainties in the derived power spectrum.

A framework for epistemic uncertainty quantification of turbulent scalar flux models for Reynolds-averaged Navier-Stokes simulations

Reynolds-averaged Navier-Stokes (RANS) simulations are a practical approach for solving complex multi-physics turbulent flows, but the underlying assumptions of the turbulence models introduce errors and uncertainties in the simulation outcome. The flow in scramjet combustors is an example of such a complex flow and the accurate characterization of safety and operability limits of these engines using RANS simulations requires an assessment of the model uncertainty. The objective of this paper is to present a framework for the epistemic uncertainty quantification of turbulence and mixing models in RANS simulations. The capabilities of the methodology will be demonstrated by performing simulations of the mixing of an underexpanded jet in a supersonic cross flow, which involves many flow features observed in scramjet engines. The fundamental sources of uncertainty in the RANS simulations are the models used for the Reynolds stresses in the momentum equations and the turbulent scalar fluxes in the scalar transport equations. The methodology consists in directly perturbing the modeled quantities in the equations, thereby establishing a method that is completely independent of the initial model form to overcome the limitations of traditional sensitivity studies. The perturbations are defined in terms of the decomposed Reynolds stress tensor, i.e., the tensor magnitude and the eigenvalues and eigenvectors of the normalized anisotropy tensor. The turbulent scalar fluxes are perturbed by using the perturbed Reynolds stresses in a generalized gradient diffusion model formulation and by changing the model constant. The perturbations were parameterized based on a comparison between the Reynolds stresses obtained from a baseline RANS simulation and those obtained from a large-eddy simulation database. Subsequently an optimization problem was solved, varying the parameters in the perturbation functions to maximize a quantity of interest that quantifies the downstream mixing. The result encompasses the value for the quantity of interest obtained from the LES database. It is shown that a traditional sensitivity study, in which the turbulent Schmidt number is varied, cannot capture this uncertainty, which further demonstrates the effectiveness of the proposed approach.

MULTIPLE-ATTRACTOR BIFURCATIONS AND QUASIPERIODICITY IN PIECEWISE-SMOOTH MAPS

It is known that border-collision bifurcations in piecewise-smooth maps can lead to situations where several attractors are created simultaneously in so-called "multiple-attractor" or "multiple-choice" bifurcations. It has been shown that such a situation leads to a fundamental source of uncertainty regarding which attractor the system will follow as a parameter is varied through the bifurcation point. Phenomena of this type have been observed in various physical and engineering systems. We have recently demonstrated that piecewise-smooth systems can exhibit a new type of border-collision bifurcation in which a stable invariant curve, associated with a quasiperiodic or a mode-locked periodic orbit, arises from a fixed point. In this paper we consider a particular variant of the multiple-attractor bifurcation in which a stable periodic orbit arises simultaneously with a closed invariant curve. We also show examples of simultaneously appearing stable periodic orbits and of the simultaneous generation of periodic and chaotic attractors.

Fundamental uncertainties in projects and the scope of project management

This paper builds on discussions that took place over a series of meetings in the UK of the Rethinking Project Management Network. The management of uncertainty is seen as a necessary condition for effective project management. Sources of uncertainty are wide ranging and have a fundamental effect on projects and project management. These sources are not confined to potential events, and include lack of information, ambiguity, characteristics of project parties, tradeoffs between trust and control mechanisms, and varying agendas in different stages of the project life cycle. Common project management practice does not address many fundamental sources of uncertainty, particularly in ‘soft’ projects where flexibility and tolerance of vagueness are necessary. More sophisticated efforts to recognise and manage important sources of uncertainty are needed. Such efforts need to encompass organisational capabilities, including some aspects of organisation culture and learning.

Weather derivatives valuation and market price of weather risk

AbstractThis paper has two objectives: (1) to propose and implement a valuation framework for temperature derivatives (a specific class of weather derivatives); and (2) to study the significance of the market price of weather risk. The objectives are accomplished by generalizing the Lucas model of 1978 to include the weather as another fundamental source of uncertainty in the economy. Daily temperature is modeled by incorporating such key properties as seasonal cycles and uneven variations throughout the year. The temperature variable is related to the aggregate dividend or output through both contemporaneous and lagged correlations, as corroborated by the data. Numerical analysis shows that the market price of weather risk is significant for temperature derivatives. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1065–1089, 2004

Fiscal Policy and Uncertainty

Government fiscal aggregates are often manipulated over the course of the business cycle in order to provide counter–cyclical stimulus. Changes that are not discretionary – the so–called ‘built–in stabilizers’– also significantly vary over the business cycle, in a manner that is even more predicatable than the periodic discretionary measures.Such measures introduce important bi–directional interactions between policy and uncertainty. On the one hand, activist policy may heighten the general level of uncertainty in the economy, by adding policy ambiguity to the more fundamental sources of uncertainty. On the other hand, the design of optimal policy itself depends crucially on levels of uncertainty concerning the state of the economy in the short and long run. In this paper we review recent work that explores the impact of uncertainty on optimal policy design, proceeding from the short to the long run.

Considerations in Designing Stabilization Schemes

Stabilization schemes have, in the current more fundamental sources of uncertainty, national and international debates, come to such as production risks, price stabilization is mean almost exclusively price stabilization unlikely to be a first-best policy, schemes. Economic theory, while somewhat ambiguous on the topic, is far from supportive of the need for price stabilization schemes. A key feature of these analyses is to define commodities by possible states of nature as well as by their physical characteristics, so that Pareto-optimal equilibria are defined for the economy for each state of nature. The conclusion in this case is that stabilization must always be desirable and that the first-best policy is to remove the source of uncertainty. The authors shall largely share this preoccupation in this paper, but it is worth considering briefly the rationale of this focus.