scholarly journals A Community Convention for Ecological Forecasting: Output Files and Metadata

2021 ◽  
Author(s):  
Michael Dietze ◽  
R. Quinn Thomas ◽  
Jody Peters ◽  
Carl Boettiger ◽  
Alexey N Shiklomanov ◽  
...  
Keyword(s):  
Uncertainty Propagation ◽  
R Package ◽  
Ensemble Member ◽  
Model Complexity ◽  
State Variables ◽  
Ecological Forecasting ◽  
Trade Offs ◽  
Data Volume ◽  
The Common ◽  
Second Tier

This document summarizes the open community standards developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast adoption, distribution, validation, and synthesis. For output files EFI has adopted a three-tiered approach reflecting trade-offs in forecast data volume and technical expertise. The preferred output file format is netCDF following the Climate and Forecast Convention for dimensions and variable naming, including an ensemble dimension where appropriate. The second-tier option is a semi-long CSV format, with state variables as columns and each row representing a unique issue datetime, prediction datetime, location, ensemble member, etc. The third-tier option is similar to option 2, but each row represents a specific summary statistic (mean, upper/lower CI) rather than individual ensemble members. For metadata, EFI expands upon the Ecological Metadata Language (EML), using additionalMetadata tags to store information designed to facilitate cross-forecast synthesis (e.g. uncertainty propagation, data assimilation, model complexity) and setting a subset of base EML tags (e.g. temporal resolution, output variables) to be required. To facilitate community adoption we also provides a R package containing a number of vignettes on how to both write and read in the EFI standard, as well as a metadata validator tool.

Eight-Axle Railcar Carbody Roll Performance: Center of Gravity and Track Wavelength Effects

2006 ◽  
Author(s):  
William Shust ◽  
Nicholas Wilson ◽  
Stan Gurule
Keyword(s):  
Contact Stresses ◽  
Center Of Gravity ◽  
Heavy Duty ◽  
Body Style ◽  
Trade Offs ◽  
The Common ◽  
Center Body

Heavy-duty railcars carry greater than typical payloads by employing additional wheelsets to lessen wheel/rail contact stresses. Rather than the common 4-axle designs, these cars may have up to 16 axles supporting one deck. Traditionally, these car types have not performed as well as desired. As a response, designers have created depressed center body styles to lower the overall center-of-gravity (CG) height. Such designs lead to more complexity and expense. In this investigation, a heavy-duty 8-axle flatcar has been modeled, both with a flat carbody and a depressed body style. Simulations of harmonic roll perturbations were performed using various CG heights, track perturbation wavelengths and operating speeds. Results include comparisons of design versus performance trade-offs.

scholarly journals Research on Mediating Mechanisms and the Impact on Food Provision Services in Poor Areas from the Perspective of Stakeholders

2021 ◽  
Vol 18 (19) ◽  
pp. 10510
Author(s):  
Tianwei Geng ◽  
Hai Chen ◽  
Di Liu ◽  
Qinqin Shi ◽  
Hang Zhang
Keyword(s):  
Ecosystem Service ◽  
Behavioral Responses ◽  
The Loess Plateau ◽  
Trade Offs ◽  
Different Types ◽  
Mediating Mechanisms ◽  
The Common ◽  
Food Provision ◽  
The Impact ◽  
The Relationship

Exploring and analyzing the common demands and behavioral responses of different stakeholders is important for revealing the mediating mechanisms of ecosystem service (ES) and realizing the management and sustainable supply of ES. This study took Mizhi County, a poverty-stricken area on the Loess Plateau in China, as an example. First, the main stakeholders, common demands, and behavioral responses in the food provision services were identified. Second, the relationship among stakeholders was analyzed. Finally, this study summarized three types of mediating mechanisms of food provision services and analyzed the influence of the different types of mediating mechanisms. The main conclusions are as follows: (1) Five main stakeholders in the study area were identified: government, farmers, enterprises, cooperatives, and middlemen. (2) Increasing farmers’ income is the common demand of most stakeholders in the study area, and this common demand has different effects on the behavioral responses of different stakeholders. (3) There are three types of mediating mechanisms in the study area: government + farmers mediating corn and mutton, government + enterprises mediating millet, and government + cooperatives mediating apples. On this basis, the effects of the different types of mediating mechanisms on variations in food yield, and trade-offs and synergies in typical townships, were analyzed.

scholarly journals The Economic Value of Digital Earth

2019 ◽  
pp. 623-643 ◽  
Author(s):  
Max Craglia ◽  
Katarzyna Pogorzelska
Keyword(s):  
Common Good ◽  
Economic Value ◽  
Open Data ◽  
Earth Observation ◽  
Economic Approach ◽  
Scarce Resources ◽  
Digital Earth ◽  
Trade Offs ◽  
The Common ◽  
Definition Of

Abstract In this chapter, we approach the economic value of Digital Earth with a broad definition of economic value, i.e., the measure of benefits from goods or services to an economic agent and the trade-offs the agent makes in view of scarce resources. The concept of Digital Earth has several components: data, models, technology and infrastructure. We focus on Earth Observation (EO) data because this component has been undergoing the most dramatic change since the beginning of this century. We review the available recent studies to assess the value of EO/geospatial/open data and related infrastructures and identify three main sets of approaches focusing on the value of information, the economic approach to the value of EO to the economy from both macro- and microeconomic perspectives, and a third set that aims to maximize value through infrastructure and policy. We conclude that the economic value of Digital Earth critically depends on the perspective: the value for whom, what purpose, and when. This multiplicity is not a bad thing: it acknowledges that Digital Earth is a global concept in which everyone can recognize their viewpoint and collaborate with others to increase the common good.

scholarly journals Quantifying location error to define uncertainty in volcanic mass flow hazard simulations

2021 ◽  
Vol 21 (8) ◽  
pp. 2447-2460
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi
Keyword(s):  
Mass Flow ◽  
Performance Metrics ◽  
Numerical Models ◽  
Model Performance ◽  
Flow Simulation ◽  
Model Complexity ◽  
Model Parameters ◽  
Spatial Covariance ◽  
Trade Offs ◽  
Pixel Pair

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (“actual”) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano, as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This “fuzzification” of simulated results yields improvements in targeted performance metrics relative to a length scale parameter at the expense of decreases in opposing metrics (e.g. fewer false negatives result in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision-making from simulated data.

scholarly journals Spatial Uncertainty Propagation Analysis with the spup R Package

The R Journal ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 180
Author(s):  
Kasia Sawicka ◽  
Gerard,B.M. Heuvelink ◽  
Dennis,J.J. Walvoort
Keyword(s):  
Uncertainty Propagation ◽  
R Package ◽  
Spatial Uncertainty ◽  
Uncertainty Propagation Analysis ◽  
Propagation Analysis

scholarly journals Quantifying location error to define uncertainty in volcanic mass flow hazard simulations

2021 ◽  
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi
Keyword(s):  
Mass Flow ◽  
Performance Metrics ◽  
Numerical Models ◽  
Model Performance ◽  
Flow Simulation ◽  
Model Complexity ◽  
Model Parameters ◽  
Spatial Covariance ◽  
Trade Offs ◽  
Pixel Pair

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (actual) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This fuzzification of simulated results yields improvements in targeted performance metrics relative to a length scale parameter, at the expense of decreases in opposing metrics (e.g. less false negatives results in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated, and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision making from simulated data.

scholarly journals Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

2019 ◽  
Vol 11 (10) ◽  
pp. 1227 ◽  
Author(s):  
Nadia Smith ◽  
Christopher D. Barnet
Keyword(s):  
Uncertainty Propagation ◽  
State Variables ◽  
Product System ◽  
Atmospheric Infrared Sounder ◽  
Cloud Properties ◽  
Infrared Measurements ◽  
Highly Correlated ◽  
Cross Track ◽  
Correlated Signals

The Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) retrieves multiple Essential Climate Variables (ECV) about the vertical atmosphere from hyperspectral infrared measurements made by the Atmospheric InfraRed Sounder (AIRS, 2002–present) and its successor, the Cross-track Infrared Sounder (CrIS, 2011–present). CLIMCAPS ECVs are profiles of temperature and water vapor, column amounts of greenhouse gases (CO2, CH4), ozone (O3) and precursor gases (CO, SO2) as well as cloud properties. AIRS (and CrIS) spectral measurements are highly correlated signals of many atmospheric state variables. CLIMCAPS inverts an AIRS (and CrIS) measurement into a set of discrete ECVs by employing a sequential Bayesian approach in which scene-dependent uncertainty is rigorously propagated. This not only linearizes the inversion problem but explicitly accounts for spectral interference from other state variables so that the correlation among ECVs (and their uncertainty) may be minimized. Here, we outline the CLIMCAPS retrieval methodology with specific focus given to its sequential scene-dependent uncertainty propagation system. We conclude by demonstrating continuity in two CLIMCAPS ECVs across AIRS and CrIS so that a long-term data record may be generated to study the feedback cycles characterizing our climate system.

scholarly journals A Heuristic Approach for Precipitation Data Assimilation: Characterization Using OSSEs

2019 ◽  
Vol 147 (9) ◽  
pp. 3445-3466 ◽  
Author(s):  
Andrés A. Pérez Hortal ◽  
Isztar Zawadzki ◽  
M. K. Yau
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Grid Point ◽  
Wrf Model ◽  
Ensemble Member ◽  
Absolute Difference ◽  
Time Interval ◽  
State Variables ◽  
Vertical Column ◽  
A New Technique

Abstract We introduce a new technique for the assimilation of precipitation observations, the localized ensemble mosaic assimilation (LEMA). The method constructs an analysis by selecting, for each vertical column in the model, the ensemble member with precipitation at the ground that is locally closest to the observed values. The proximity between the modeled and observed precipitation is determined by the mean absolute difference of precipitation intensity, converted to reflectivity and measured over a spatiotemporal window centered at each grid point of the model. The underlying hypothesis of the approach is that the ensemble members that are locally closer to the observed precipitation are more probable to be closer to the “truth” in the state variables than the other members. The initial conditions for the new forecast are obtained by nudging the background states toward the mosaic of the closest ensemble members (analysis) over a 30 min time interval, reducing the impacts of the imbalances at the boundaries between the different selected members. The potential of the method is studied using observing system simulation experiments (OSSEs) employing a small ensemble of 20 members. The ensemble is produced by the WRF Model, run at a horizontal grid spacing of 20 km. The experiments lend support to the validity of the hypothesis and allow the determination of the optimal parameters for the approach. In the context of OSSE, this new data assimilation technique is able to produce forecasts with considerable and long-lived error reductions in the fields of precipitation, temperature, humidity, and wind.

Can we have it all? Sustainability trade-offs and cross-insurance mechanisms in supply chains

2020 ◽  
Vol 40 (9) ◽  
pp. 1339-1366 ◽  
Author(s):  
Mauro Fracarolli Nunes ◽  
Camila Lee Park ◽  
Ely Laureano Paiva
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Food Industry ◽  
Poor Performance ◽  
Content Type ◽  
Trade Offs ◽  
Typical Food ◽  
Retail Chains ◽  
Second Tier ◽  
Insurance Mechanism

PurposeThe study investigates the interaction of sustainability dimensions in supply chains. Along with the analysis of sustainability trade-offs (i.e. prioritizing one dimension to the sacrifice of others), we develop and test the concept of cross-insurance mechanism (i.e. meeting of one sustainability goal possibly attenuating the effects of poor performance in another).Design/methodology/approachThrough the analysis of a 20-variation vignette-based experiment, we evaluate the effects of these issues on the corporate credibility (expertise and trustworthiness) of four tiers of a typical food supply chain: pesticide producers, farmers, companies from the food industry and retail chains.FindingsResults suggest that both sustainability trade-offs and cross-insurance mechanisms have different impacts across the chain. While pesticide producers (first tier) and retail chains (fourth tier) seem to respond better to a social trade-off, the social cross-insurance mechanism has shown to be particularly beneficial to companies from the food industry (third tier). Farmers (second tier), in turn, seem to be more sensitive to the economic cross-insurance mechanism.Originality/valueAlong with adding to the study of sustainability trade-offs in supply chain contexts, results suggest that the efficiency of the insurance mechanism is not conditional on the alignment among sustainability dimensions (i.e. social responsibility attenuating social irresponsibility). In this sense, empirical evidences support the development of the cross-insurance mechanism as an original concept.

The Influence of Muscle Model Complexity in Musculoskeletal Motion Modeling

1985 ◽  
Vol 107 (2) ◽  
pp. 147-157 ◽  
Author(s):  
M. L. Audu ◽  
D. T. Davy
Keyword(s):  
Control Algorithm ◽  
Complex Model ◽  
Model Complexity ◽  
Model Choice ◽  
Motion Modeling ◽  
Advantages And Disadvantages ◽  
Trade Offs ◽  
Motion Problem ◽  
Motion Studies ◽  
Muscle Models

A comparative study of four different muscle models in a musculoskeletal motion problem is made. The models vary in complexity from the simple input-output model to the more complex model of Hatze [I]. These models are used to solve a minimum time kicking problem using an optimal control algorithm. The results demonstrate the strong influence of the model choice on the various predicted kinematic and kinetic parameters in the problem. The study illustrates some of the advantages and disadvantages involved in trade-offs between model complexity and practicability in musculoskeletal motion studies. The results also illustrate the importance of appropriate detailed parameter estimation studies in the mathematical modeling of the musculoskeletal system.

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