Stable and Perfect Model Semantics

2016 ◽  
pp. 169-183
Author(s):  
Pascal Hitzler ◽  
Anthony Seda
Keyword(s):  
Perfect Model

Domina Paupertas: the praise of voluntary poverty by St. Francis of Assisi and its reflection in late medieval Spanish painting

2014 ◽  
Vol 14 (2) ◽  
pp. 105
Author(s):  
José María Salvador González
Keyword(s):  
San Francisco ◽  
Middle Ages ◽  
Jesus Christ ◽  
Large Set ◽  
Late Medieval ◽  
Late Middle Ages ◽  
Perfect Model ◽  
Material Goods ◽  
Potential Impact ◽  
Francis Of Assisi

As is well known, St. Francis of Assisi heroically embraced evangelical poverty, renouncing material goods and living in abject poverty, in imitation of Jesus Christ. Furthermore, through his writings and oral testimonies collected by his disciples, the saint fervently urged Christians to live to some degree voluntary poverty , of which Christ was the perfect model. By basing this reading on some Poverello’s quotations, this paper intends to show the potential impact that these exhortations from San Francisco to poverty may have had in the late medieval Spanish painting, in some iconographic themes so significantly Franciscan as the Nativity and the Passion of the Redeemer. Through the analysis of a large set of paintings representing both issues, we will attempt to put into light if the teachings of St. Francis on evangelical poverty are reflected somehow in Spanish painting of the late Middle Ages.

Reexamining the tropical Atlantic influence on ENSO using perfect model predictability experiments

2021 ◽  
Author(s):  
Ingo Richter ◽  
Yu Kosaka ◽  
Hiroki Tokinaga ◽  
Shoichiro Kido
Keyword(s):  
Initial Conditions ◽  
Boreal Summer ◽  
Similar Amount ◽  
Tropical Atlantic ◽  
Equatorial Atlantic ◽  
Boreal Spring ◽  
Modes Of Variability ◽  
Control Simulation ◽  
Starting Point ◽  
Perfect Model

<p>The potential influence of the tropical Atlantic on the development of ENSO has received increased attention over recent years. In particular equatorial Atlantic variability (also known as the Atlantic zonal mode or AZM) has been shown to be anticorrelated with ENSO, i.e. cold AZM events in boreal summer (JJA) tend to be followed by El Niño in winter (DJF), and vice versa for warm AZM events. One problem with disentangling the two-way interaction between the equatorial Atlantic and Pacific is that both ENSO and the AZM tend to develop in boreal spring (MAM).</p><p>Here we use a set of GCM sensitivity experiments to quantify the strength of the Atlantic-Pacific link. The starting point is a 1000-year free-running control simulation with the GFDL CM 2.1 model. From this control simulation, we pick years in which a cold AZM event in JJA is followed by an El Niño in DJF. These years serve as initial conditions for “perfect model” prediction experiments with 10 ensemble members each. In the control experiments, the predictions evolve freely for 12 months from January 1 of each selected year. In the second set of predictions, SSTs are gradually relaxed to climatology in the tropical Atlantic, so that the cold AZM event is suppressed. In the third set of predictions, we restore the tropical Pacific SSTs to climatology, so that the El Niño event is suppressed.</p><p>The results suggest that, on average, the tropical Atlantic SST anomalies increase the strength of El Niño in the following winter by about 10-20%. If, on the other hand, El Niño development is suppressed, the amplitude of the cold AZM event also reduces by a similar amount. The results suggest that, in the context of this GCM, the influence of AZM events on ENSO development is relatively weak but not negligible. The fact that ENSO also influences the AZM in boreal spring highlights the complex two-way interaction between these two modes of variability.</p>

scholarly journals Data-Driven Localization Mappings in Filtering the Monsoon–Hadley Multicloud Convective Flows

2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim
Keyword(s):  
Learning Algorithm ◽  
Data Driven ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Errors ◽  
Accurate Analysis ◽  
Perfect Model ◽  
Nonlinear Stochastic Model ◽  
Correlation Statistics ◽  
The Impact

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.

scholarly journals Comment on "Quantitative performance metrics for stratospheric-resolving chemistry-climate models" by Waugh and Eyring (2008)

2009 ◽  
Vol 9 (23) ◽  
pp. 9101-9110 ◽  
Author(s):  
V. Grewe ◽  
R. Sausen
Keyword(s):  
Observational Data ◽  
Confidence Intervals ◽  
Climate Models ◽  
Performance Metrics ◽  
Statistical Tests ◽  
Low Grade ◽  
Perfect Model ◽  
Special Cases ◽  
Quantitative Performance ◽  
The Difference

Abstract. This comment focuses on the statistical limitations of a model grading, as applied by D. Waugh and V. Eyring (2008) (WE08). The grade g is calculated for a specific diagnostic, which basically relates the difference of means of model and observational data to the standard deviation in the observational dataset. We performed Monte Carlo simulations, which show that this method has the potential to lead to large 95%-confidence intervals for the grade. Moreover, the difference between two model grades often has to be very large to become statistically significant. Since the confidence intervals were not considered in detail for all diagnostics, the grading in WE08 cannot be interpreted, without further analysis. The results of the statistical tests performed in WE08 agree with our findings. However, most of those tests are based on special cases, which implicitely assume that observations are available without any errors and that the interannual variability of the observational data and the model data are equal. Without these assumptions, the 95%-confidence intervals become even larger. Hence, the case, where we assumed perfect observations (ignored errors), provides a good estimate for an upper boundary of the threshold, below that a grade becomes statistically significant. Examples have shown that the 95%-confidence interval may even span the whole grading interval [0, 1]. Without considering confidence intervals, the grades presented in WE08 do not allow to decide whether a model result significantly deviates from reality. Neither in WE08 nor in our comment it is pointed out, which of the grades presented in WE08 inhibits such kind of significant deviation. However, our analysis of the grading method demonstrates the unacceptably high potential for these grades to be insignificant. This implies that the grades given by WE08 can not be interpreted by the reader. We further show that the inclusion of confidence intervals into the grading approach is necessary, since otherwise even a perfect model may get a low grade.

scholarly journals Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

2021 ◽  
Author(s):  
Philip G. Sansom ◽  
Donald Cummins ◽  
Stefan Siegert ◽  
David B Stephenson
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Climate Model ◽  
Future Projections ◽  
Perfect Model ◽  
Global Mean Surface Temperature ◽  
Time Series Approach ◽  
Energy Balance Models ◽  
Global Mean

Abstract Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

scholarly journals Translational Animal Models for Liver Cancer

2018 ◽  
Vol 2 ◽  
pp. 2 ◽  
Author(s):  
Michele Obeid ◽  
Ramzy C. Khabbaz ◽  
Kelly D. Garcia ◽  
Kyle M. Schachtschneider ◽  
Ron C. Gaba
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Research ◽  
Animal Models ◽  
Liver Cancer ◽  
Small Animal ◽  
Large Animal ◽  
Starting Point ◽  
Perfect Model ◽  
Small Animal Models ◽  
Human Primate

Animal models have become increasingly important in the study of hepatocellular carcinoma (HCC), as they serve as a critical bridge between laboratory-based discoveries and human clinical trials. Developing an ideal animal model for translational use is challenging, as the perfect model must be able to reproduce human disease genetically, anatomically, physiologically, and pathologically. This brief review provides an overview of the animal models currently available for translational liver cancer research, including rodent, rabbit, non-human primate, and pig models, with a focus on their respective benefits and shortcomings. While small animal models offer a solid starting point for investigation, large animal HCC models are becoming increasingly important for translation of preclinical results to clinical practice.

scholarly journals Application of Boyd’s Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part II: Accuracy Analysis and Detailed Study of the Operational Impact

2012 ◽  
Vol 140 (10) ◽  
pp. 3149-3162 ◽  
Author(s):  
Daan Degrauwe ◽  
Steven Caluwaerts ◽  
Fabrice Voitus ◽  
Rafiq Hamdi ◽  
Piet Termonia
Keyword(s):  
Weather Prediction ◽  
Relaxation Method ◽  
Companion Paper ◽  
Water Model ◽  
Limited Area ◽  
Perfect Model ◽  
Depth Study ◽  
Nwp Model ◽  
The Impact ◽  
Operational Impact

Abstract Spectral limited-area models face a particular challenge at their lateral boundaries: the fields need to be made periodic. Boyd proposed a windowing-based method to improve the periodization and relaxation. In a companion paper, the implementation of this windowing method in the operational semi-implicit semi-Lagrangian spectral HARMONIE system was described and some first reproducibility tests, comparing this method to the old existing one, were presented. The present paper provides an in-depth study of the impact of this method for different configurations of the implementation. This is carried out in three steps in well-controlled experimental setups of increasing complexity. First, different aspects of Boyd’s method are analyzed in an idealized perfect-model test using a representative 1D shallow-water model. Second, the implementation is tested in an adiabatic 3D numerical weather prediction (NWP) model with perfect-model experiments. Finally, the impact of using Boyd’s method in a more operational-like NWP context is investigated as well. The presented tests show that, while the implementation of Boyd’s method is neutral in terms of scores, it is superior to the existing spline method in the case of strong dynamical forcings at the lateral boundaries.

The perspective of the use of artificial intelligence in the formation and control of modern and future urban areas

2021 ◽  
Vol 2 (80) ◽  
pp. 309-313
Author(s):  
D.N. Abilev ◽  
◽  
G.S. Dzhakipova ◽  
Keyword(s):  
Artificial Intelligence ◽  
Everyday Life ◽  
Urban Areas ◽  
Perfect Model ◽  
Routine Tasks ◽  
And Control

With the development of technologies and their introduction into everyday life, there is also the possibility of their professional use in various industries and structures. The AI system is a virtual assistant, whose development every year can create a perfect model of urban control and a virtual assistant in helping people with many routine tasks. This article describes the prospects for using AI and examples of its development.

Precarious life

2019 ◽  
pp. 77-94
Author(s):  
Miriam Leonard
Keyword(s):  
Germ Cell ◽  
Death Drive ◽  
Pleasure Principle ◽  
Life And Death ◽  
Perfect Model ◽  
The Subject ◽  
Tragic Drama ◽  
Oedipus At Colonus

In …Pleasure Principle, Freud juxtaposes his discussion of the life and death instincts in “elementary organisms” to the tragic drama he sees enacted in his grandson’s fort-da game. Freud’s insights into the death drive are given an added tragic dimension in Lacan’s reading of Oedipus at Colonus. Here Lacan establishes the anti- or even post-humanist credentials of tragedy by insisting that it is the death of the subject which is Sophocles’ ultimate preoccupation. By placing Greek tragedy’s confrontation with the death drive in dialogue with the instincts of the “germ-cell”, the chapter demonstrates how psychoanalysis offers a perfect model for understanding antiquity’s contribution to posthumanism.

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