scholarly journals Comparison of Rip Current Hazard Likelihood Forecasts with Observed Rip Current Speeds

2017 ◽  
Vol 32 (4) ◽  
pp. 1659-1666 ◽  
Author(s):  
Melissa Moulton ◽  
Gregory Dusek ◽  
Steve Elgar ◽  
Britt Raubenheimer
Keyword(s):  
Statistical Model ◽  
Normal Wave ◽  
Skill Score ◽  
Water Levels ◽  
High Threshold ◽  
Rip Current ◽  
Rip Currents ◽  
Skill Scores ◽  
Wide Range ◽  
The Relationship

Abstract Although rip currents are a major hazard for beachgoers, the relationship between the danger to swimmers and the physical properties of rip current circulation is not well understood. Here, the relationship between statistical model estimates of hazardous rip current likelihood and in situ velocity observations is assessed. The statistical model is part of a forecasting system that is being made operational by the National Weather Service to predict rip current hazard likelihood as a function of wave conditions and water level. The temporal variability of rip current speeds (offshore-directed currents) observed on an energetic sandy beach is correlated with the hindcasted hazard likelihood for a wide range of conditions. High likelihoods and rip current speeds occurred for low water levels, nearly shore-normal wave angles, and moderate or larger wave heights. The relationship between modeled hazard likelihood and the frequency with which rip current speeds exceeded a threshold was assessed for a range of threshold speeds. The frequency of occurrence of high (threshold exceeding) rip current speeds is consistent with the modeled probability of hazard, with a maximum Brier skill score of 0.65 for a threshold speed of 0.23 m s−1, and skill scores greater than 0.60 for threshold speeds between 0.15 and 0.30 m s−1. The results suggest that rip current speed may be an effective proxy for hazard level and that speeds greater than ~0.2 m s−1 may be hazardous to swimmers.

scholarly journals Assessing the Skill of Yes/No Forecasts for Markov Observations

2006 ◽  
Vol 134 (9) ◽  
pp. 2601-2611
Author(s):  
William Briggs ◽  
David Ruppert
Keyword(s):  
Hypothesis Testing ◽  
Skill Score ◽  
Sampling Distribution ◽  
Loss Functions ◽  
Precipitation Forecast ◽  
Present Value ◽  
First Order ◽  
Precipitation Occurrence ◽  
Skill Scores ◽  
Wide Range

Abstract Briggs and Ruppert recently introduced a new, easy-to-calculate economic skill/value score for use in yes/no forecast decisions, of which precipitation forecast decisions are an example. The advantage of this new skill/value score is that the sampling distribution is known, which allows one to perform hypothesis tests on collections of forecasts and to say whether a given skill/value score is significant or not. Here, the climate skill/value score is taken and extended to the case where the predicted series is first-order Markov in nature, of which, again, precipitation occurrence series can be an example. It is shown that, in general, Markov skill/value is different and more demanding than is persistence skill. Persistence skill is defined as improvement over forecasts that state that the next value in a series will equal the present value. It is also shown that any naive forecasts based solely on the Markov parameters is always at least as skillful/valuable as are persistence forecasts; in general, persistence forecasts should not be used. The distribution for the Markov skill score is presented, and examples of hypothesis testing for precipitation forecasts are given. These skill scores are graphed for a wide range of forecast/user loss functions, a process that makes their interpretation simple.

scholarly journals Flexible and consistent quantile estimation for intensity–duration–frequency curves

2021 ◽  
Vol 25 (12) ◽  
pp. 6479-6494
Author(s):  
Felix S. Fauer ◽  
Jana Ulrich ◽  
Oscar E. Jurado ◽  
Henning W. Rust
Keyword(s):  
Power Law ◽  
Skill Score ◽  
Observation Time ◽  
Performance Model ◽  
Wide Range ◽  
Intensity Duration Frequency ◽  
The Individual ◽  
The Relationship ◽  
Flexible Model

Abstract. Assessing the relationship between the intensity, duration, and frequency (IDF) of extreme precipitation is required for the design of water management systems. However, when modeling sub-daily precipitation extremes, there are commonly only short observation time series available. This problem can be overcome by applying the duration-dependent formulation of the generalized extreme value (GEV) distribution which fits an IDF model with a range of durations simultaneously. The originally proposed duration-dependent GEV model exhibits a power-law-like behavior of the quantiles and takes care of a deviation from this scaling relation (curvature) for sub-hourly durations (Koutsoyiannis et al., 1998). We suggest that a more flexible model might be required to model a wide range of durations (1 min to 5 d). Therefore, we extend the model with the following two features: (i) different slopes for different quantiles (multiscaling) and (ii) the deviation from the power law for large durations (flattening), which is newly introduced in this study. Based on the quantile skill score, we investigate the performance of the resulting flexible model with respect to the benefit of the individual features (curvature, multiscaling, and flattening) with simulated and empirical data. We provide detailed information on the duration and probability ranges for which specific features or a systematic combination of features leads to improvements for stations in a case study area in the Wupper catchment (Germany). Our results show that allowing curvature or multiscaling improves the model only for very short or long durations, respectively, but leads to disadvantages in modeling the other duration ranges. In contrast, allowing flattening on average leads to an improvement for medium durations between 1 h and 1 d, without affecting other duration regimes. Overall, the new parametric form offers a flexible and enhanced performance model for consistently describing IDF relations over a wide range of durations, which has not been done before as most existing studies focus on durations longer than 1 h or day and do not address the deviation from the power law for very long durations (2–5 d).

scholarly journals Verification Techniques and Simple Theoretical Forecast Models

2008 ◽  
Vol 23 (6) ◽  
pp. 1049-1068 ◽  
Author(s):  
Robert Fawcett
Keyword(s):  
Linear Regression ◽  
Skill Score ◽  
Type Model ◽  
Operating Characteristics ◽  
Linear Discriminant ◽  
Climate Forecasts ◽  
Skill Scores ◽  
Forecast Models ◽  
Verification Techniques ◽  
The Relationship

Abstract This paper investigates the performance of some skill measures [e.g., linear error in probability space, (LEPS), relative operating characteristics score (ROCS), Brier scores, and proportion correct rates], commonly used in the validation and verification of seasonal climate forecasts, within the context of some simple theoretical forecast models. The models considered include linear regression and linear discriminant analysis types, where the forecasts are presented in the form of above/below median probabilities and tercile probabilities. Above and below the median categories are also explored within the context of stratified climatology models, while tail categories are explored within the context of the linear regression type. The skill scores for the models are calculated in each case as functions of a parameter that expresses the strength of the relationship between the predictor and predictand. The skill scores investigated are found to exhibit different dependencies on the model parameter, implying that a given skill score value (0.1 say) can imply a range of strengths in the relationship between predictor and predictand, depending on which skill score is being considered. On the other hand, interrelationships between pairs of skill scores are found to be similar across the different types of models, provided model reliability is preserved. The two-category and three-category LEPS skill scores are found to be on approximately the same scale for the linear regression–type model, thereby enabling a direct comparison.

scholarly journals The Relationship between Automated Low-Level Velocity Calculations from the WSR-88D and Maximum Tornado Intensity Determined from Damage Surveys

2015 ◽  
Vol 30 (5) ◽  
pp. 1125-1139 ◽  
Author(s):  
Darrel M. Kingfield ◽  
James G. LaDue
Keyword(s):  
Peak Velocity ◽  
Detection Algorithm ◽  
Low Level ◽  
Convective Systems ◽  
Skill Scores ◽  
Wide Range ◽  
The Relationship ◽  
Optimal Strength ◽  
Convective Mode ◽  
Population Threshold

Abstract The relationship between automated low-level velocity derived from WSR-88D severe storm algorithms and two groups of tornado intensity were evaluated using a 4-yr climatology of 1975 tornado events spawned from 1655 supercells and 320 quasi-linear convective systems (QLCSs). A comparison of peak velocity from groups of detections from the Mesocyclone Detection Algorithm and Tornado Detection Algorithm for each tornado track found overlapping distributions when discriminating between weak [rated as category 0 or 1 on the enhanced Fujita scale (EF0 and EF1)] and strong (EF2–5) events for both rotational and delta velocities. Dataset thresholding by estimated affected population lowered the range of observed velocities, particularly for weak tornadoes while retaining a greater frequency of events for strong tornadoes. Heidke skill scores for strength discrimination were dependent on algorithm, velocity parameter, population threshold, and convective mode, and varied from 0.23 and 0.66. Bootstrapping the skill scores for each algorithm showed a wide range of low-level velocities (at least 7 m s−1 in width) providing an equivalent optimal skill at discriminating between weak and strong tornadoes. This ultimately limits identification of a single threshold for optimal strength discrimination but the results match closely with larger prior manual studies of low-level velocities.

scholarly journals A new method for the pragmatic choice of wind models for Wind Resource Assessment in complex terrain

2020 ◽  
Author(s):  
Sarah Barber ◽  
Alain Schubiger ◽  
Natalie Wagenbrenner ◽  
Nicolas Fatras ◽  
Henrik Nordborg
Keyword(s):  
Cost Effective ◽  
Skill Score ◽  
Effective Model ◽  
New Method ◽  
Complex Nature ◽  
Blind Test ◽  
Skill Scores ◽  
Wide Range ◽  
Before And After ◽  
Wind Resource

Abstract. The accuracy of the estimation of the wind resource has an enormous effect on the expected rate of return of a wind energy project. Due to the complex nature of the weather and the wind flow over the earth's surface, it can be very challenging to measure and model the wind resource correctly. For a given project, the modeller is faced with a difficult choice of a wide range of simulation tools with varying accuracies (or skill) and costs. In this work, a new method for helping wind modellers choose the most cost-effective model for a given project is developed by applying six different Computational Fluid Dynamics tools to simulate the Bolund Hill experiment and studying appropriate comparison metrics in detail. This is done by firstly defining various parameters for predicting the skill and cost scores before carrying out the simulations as well as for calculating skill and cost scores after carrying out the simulations. Weightings are then defined for these parameters, and values assigned to them for the six tools using a template containing pre-defined limits in a blind test. An iterative improvement process is applied by collecting inputs from the participants of the study. This allows a graph of predicted skill score against cost score to be produced, enabling modellers to choose the most cost-effective model without having to carry out the simulations beforehand. The most effective model is the one with the highest skill score for the lowest cost score, at the flattening-off part of the curve. The results show that this new method is successful, and that it is generally possible to apply it in order to choose the most appropriate model for a given project in advance. This is demonstrated by the good match between the shapes of the skill score against cost score curves before and after the simulations, and by the fact that the tool at the flattening-out point of the curve is the same before and after carrying out the simulations. It is also shown how important it is to take into account other factors that may affect the accuracy and costs of a wind modelling simulation as well as the quality of the aerodynamic equations and the run-time. Several improvements to the method are being worked on, by further examining the discrepancies between the predicted and actual cost and skill scores. Additionally, the method is being extended for calculating all wind directions and the Annual Energy Production, as well as to include mesoscale nesting or forcing. A large number of inputs are being collected as part of a simulation challenge in collaboration with IEA Wind Task 31. The method has a high potential to be extended to a wide range of other simulation applications.

scholarly journals A Comparison of Dynamical and Statistical Predictions of Weekly Tropical Cyclone Activity in the Southern Hemisphere

2010 ◽  
Vol 138 (9) ◽  
pp. 3671-3682 ◽  
Author(s):  
Frédéric Vitart ◽  
Anne Leroy ◽  
Matthew C. Wheeler
Keyword(s):  
Statistical Model ◽  
Southern Hemisphere ◽  
Economic Value ◽  
Skill Score ◽  
Model Potential ◽  
Dynamical Model ◽  
False Alarms ◽  
Relative Operating Characteristic ◽  
Skill Scores ◽  
Probabilistic Forecasts

Abstract The skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast system to predict the occurrence of tropical cyclones (TCs) over the Southern Hemisphere during weekly periods has been evaluated and compared to the skill of a state-of-the-art statistical model. Probabilistic skill scores have been applied to a common series of hindcasts produced with the dynamical and statistical models. The ECMWF hindcasts have higher relative operating characteristic (ROC) scores than the statistical model for the first three weeks of integrations. The dynamical model also has skill over the Indian Ocean in week 4. The ECMWF hindcasts have lower Brier skill scores than the statistical model after week 2, which is likely because this version of the ECMWF model creates about 30% more TCs than observations and therefore generates a large number of false alarms. A simple calibration has been applied to the ECMWF probabilistic forecasts that significantly improves their reliability, but at the expense of the sharpness. The calibrated dynamical model has higher Brier skill scores than the statistical model during the first three weeks, although the statistical model remains more reliable. The multimodel combination of the calibrated dynamical forecasts with the statistical forecasts helps to improve the reliability of the ECMWF forecasts. The Brier skill score of the multimodel exceeds the Brier skill scores of the individual models, but with less sharpness than the calibrated dynamical model. This result suggests that the statistical model can be useful as a benchmark for dynamical models and as a component of a multimodel combination to improve the skill of the dynamical model. Potential economic value diagrams confirm that the multimodel forecasts are useful up to week 3 over the Southern Hemisphere.

The Problem of Identifying and Modeling the Relationship between Monetary Factor and Inflation in the Russian Economy

2008 ◽  
pp. 61-76
Author(s):  
A. Porshakov ◽  
A. Ponomarenko
Keyword(s):  
Money Supply ◽  
Money Demand ◽  
Russian Economy ◽  
Long Run ◽  
Complex Approach ◽  
Wide Range ◽  
Long Time ◽  
The Relationship ◽  
Supply Side Factors

The role of monetary factor in generating inflationary processes in Russia has stimulated various debates in social and scientific circles for a relatively long time. The authors show that identification of the specificity of relationship between money and inflation requires a complex approach based on statistical modeling and involving a wide range of indicators relevant for the price changes in the economy. As a result a model of inflation for Russia implying the decomposition of inflation dynamics into demand-side and supply-side factors is suggested. The main conclusion drawn is that during the recent years the volume of inflationary pressures in the Russian economy has been determined by the deviation of money supply from money demand, rather than by money supply alone. At the same time, monetary factor has a long-run spread over time impact on inflation.

scholarly journals Polymorphic Iterable Sequential Effect Systems

2021 ◽  
Vol 43 (1) ◽  
pp. 1-79
Author(s):  
Colin S. Gordon
Keyword(s):  
Algebraic Structure ◽  
Position Effect ◽  
Type Systems ◽  
Sequential Effect ◽  
Prior Work ◽  
Sequential Effects ◽  
Wide Range ◽  
The Relationship ◽  
Categorical Semantics

Effect systems are lightweight extensions to type systems that can verify a wide range of important properties with modest developer burden. But our general understanding of effect systems is limited primarily to systems where the order of effects is irrelevant. Understanding such systems in terms of a semilattice of effects grounds understanding of the essential issues and provides guidance when designing new effect systems. By contrast, sequential effect systems—where the order of effects is important—lack an established algebraic structure on effects. We present an abstract polymorphic effect system parameterized by an effect quantale—an algebraic structure with well-defined properties that can model the effects of a range of existing sequential effect systems. We define effect quantales, derive useful properties, and show how they cleanly model a variety of known sequential effect systems. We show that for most effect quantales, there is an induced notion of iterating a sequential effect; that for systems we consider the derived iteration agrees with the manually designed iteration operators in prior work; and that this induced notion of iteration is as precise as possible when defined. We also position effect quantales with respect to work on categorical semantics for sequential effect systems, clarifying the distinctions between these systems and our own in the course of giving a thorough survey of these frameworks. Our derived iteration construct should generalize to these semantic structures, addressing limitations of that work. Finally, we consider the relationship between sequential effects and Kleene Algebras, where the latter may be used as instances of the former.

scholarly journals CAD-Based 3D-FE Modelling of AISI-D3 Turning with Ceramic Tooling

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Panagiotis Kyratsis ◽  
Anastasios Tzotzis ◽  
Angelos Markopoulos ◽  
Nikolaos Tapoglou
Keyword(s):  
Statistical Model ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Fe Model ◽  
Fe Modelling ◽  
3D Finite Element ◽  
Force Components ◽  
Four Levels ◽  
The Relationship ◽  
Strong Agreement

In this study, the development of a 3D Finite Element (FE) model for the turning of AISI-D3 with ceramic tooling is presented, with respect to four levels of cutting speed, feed, and depth of cut. The Taguchi method was employed in order to create the orthogonal array according to the variables involved in the study, reducing this way the number of the required simulation runs. Moreover, the possibility of developing a prediction model based on well-established statistical tools such as the Response Surface Methodology (RSM) and the Analysis of Variance (ANOVA) was examined, in order to further investigate the relationship between the cutting speed, feed, and depth of cut, as well as their influence on the produced force components. The findings of this study point out an increased correlation between the experimental results and the simulated ones, with a relative error below 10% for most tests. Similarly, the values derived from the developed statistical model indicate a strong agreement with the equivalent numerical values due to the verified adequacy of the statistical model.

Age-Dependency of Total Tau in the Cerebrospinal Fluid Is Corrected by Amyloid-β 1–40: A Correlational Study in Healthy Adults

2021 ◽  
pp. 1-8
Author(s):  
Paul Theo Zebhauser ◽  
Achim Berthele ◽  
Marie-Sophie Franz ◽  
Oliver Goldhardt ◽  
Janine Diehl-Schmid ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Amyloid Β ◽  
Healthy Adults ◽  
Tau Proteins ◽  
Clinical Settings ◽  
Inclusion Criteria ◽  
Total Tau ◽  
Potential Marker ◽  
Wide Range ◽  
The Relationship

Background: Tau proteins are established biomarkers of neuroaxonal damage in a wide range of neurodegenerative conditions. Although measurement of total-Tau in the cerebrospinal fluid is widely used in research and clinical settings, the relationship between age and total-Tau in the cerebrospinal fluid is yet to be fully understood. While past studies reported a correlation between age and total-Tau in the cerebrospinal fluid of healthy adults, in clinical practice the same cut-off value is used independently of patient’s age. Objective: To further explore the relationship between age and total-Tau and to disentangle neurodegenerative from drainage-dependent effects. Methods: We analyzed cerebrospinal fluid samples of 76 carefully selected cognitively healthy adults and included amyloid-β 1–40 as a potential marker of drainage from the brain’s interstitial system. Results: We found a significant correlation of total-Tau and age, which was no longer present when correcting total-Tau for amyloid-β 1–40 concentrations. These findings were replicated under varied inclusion criteria. Conclusion: Results call into question the association of age and total-Tau in the cerebrospinal fluid. Furthermore, they suggest diagnostic utility of amyloid-β 1–40 as a possible proxy for drainage-mechanisms into the cerebrospinal fluid when interpreting biomarker concentrations for neurodegenerative diseases.

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