scholarly journals The potential for structural errors in emergent constraints

2021 ◽  
Vol 12 (3) ◽  
pp. 899-918
Author(s):  
Benjamin M. Sanderson ◽  
Angeline G. Pendergrass ◽  
Charles D. Koven ◽  
Florent Brient ◽  
Ben B. B. Booth ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Structural Model ◽  
Future Climate ◽  
Anthropogenic Emissions ◽  
Probability Bounds ◽  
Climate Simulations ◽  
Emergent Constraints ◽  
Modelling Assumptions ◽  
Response Variation ◽  
Climate Responses

Abstract. Studies of emergent constraints have frequently proposed that a single metric can constrain future responses of the Earth system to anthropogenic emissions. Here, we illustrate that strong relationships between observables and future climate across an ensemble can arise from common structural model assumptions with few degrees of freedom. Such cases have the potential to produce strong yet overconfident constraints when processes are represented in a common, oversimplified fashion throughout the ensemble. We consider these issues in the context of a collection of published constraints and argue that although emergent constraints are potentially powerful tools for understanding ensemble response variation and relevant observables, their naïve application to reduce uncertainties in unknown climate responses could lead to bias and overconfidence in constrained projections. The prevalence of this thinking has led to literature in which statements are made on the probability bounds of key climate variables that were confident yet inconsistent between studies. Together with statistical robustness and a mechanism, assessments of climate responses must include multiple lines of evidence to identify biases that can arise from shared, oversimplified modelling assumptions that impact both present and future climate simulations in order to mitigate against the influence of shared structural biases.

scholarly journals On structural errors in emergent constraints

2021 ◽  
Author(s):  
Benjamin M. Sanderson ◽  
Angeline Pendergrass ◽  
Charles D. Koven ◽  
Florent Brient ◽  
Ben B. B. Booth ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Climate Models ◽  
Future Climate ◽  
Anthropogenic Emissions ◽  
Probability Bounds ◽  
The Earth ◽  
Climate Simulations ◽  
Emergent Constraints ◽  
Out Of Sample ◽  
Climate Responses

Abstract. Studies of emergent constraints have frequently proposed that a single metric alone can constrain future responses of the Earth system to anthropogenic emissions. The prevalence of this thinking has led to literature and messaging which is sometimes confusing to policymakers, with a series of studies over the last decade making confident, yet contradictory, claims on the probability bounds of key climate variables. Here, we illustrate that emergent constraints are more likely to occur where the variance across an ensemble of climate models of both observable and future climate arises from common structural assumptions and few degrees of freedom. Such cases are likely to occur when processes are represented in a common, oversimplified fashion throughout the ensemble, about which we have the least confidence in performance out of sample. We consider these issues in the context of a number of published constraints, and argue that the application of emergent constraints alone to estimate uncertainties in unknown climate responses can potentially lead to bias and overconfidence in constrained projections. Together with statistical robustness and plausibility of mechanism, assessments of climate responses must include multiple lines of evidence to identify biases that arise from common oversimplified modeling assumptions which impact both present and future climate simulations in order to mitigate against the influence of common structural biases.

Relation Between Local Structure, Electric Dipole and Charge Carrier Dynamics in DHICA Melanin, a Model for Biocompatible Semiconductors

2019 ◽  
Author(s):  
Micaela Matta ◽  
Alessandro Pezzella ◽  
Alessandro Troisi
Keyword(s):  
Electronic Structure ◽  
Degrees Of Freedom ◽  
Structural Model ◽  
Computational Study ◽  
Oxidative Polymerization ◽  
Radical Scavenging ◽  
Charge Carriers ◽  
Electronic Charge ◽  
Polymer Semiconductors ◽  
Synthetic Pigments

<div><div><div><p>Eumelanins are a family of natural and synthetic pigments obtained by oxidative polymerization of their natural precursors: 5,6 dihydroxyindole and its 2-carboxy derivative (DHICA). The simultaneous presence of ionic and electronic charge carriers makes these pigments promising materials for applications in bioelectronics. In this computational study we build a structural model of DHICA melanin considering the interplay between its many degrees of freedom, then we examine the electronic structure of representative oligomers. We find that a non-vanishing dipole along the polymer chain sets this system apart from conventional polymer semiconductors, determining its electronic structure, reactivity toward oxidation and localization of the charge carriers. Our work sheds light on previously unnoticed features of DHICA melanin that not only fit well with its radical scavenging and photoprotective properties, but open new perspectives towards understanding and tuning charge transport in this class of materials.<br></p></div></div></div>

scholarly journals d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Masayoshi Ishii ◽  
Nobuhito Mori
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
High Resolution ◽  
Climate Changes ◽  
Future Climate ◽  
Atmospheric Models ◽  
Large Ensemble ◽  
Past Climate ◽  
The Past ◽  
Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

Are there pre-Quaternary geological analogues for a future greenhouse warming?

2011 ◽  
Vol 369 (1938) ◽  
pp. 933-956 ◽  
Author(s):  
Alan M. Haywood ◽  
Andy Ridgwell ◽  
Daniel J. Lunt ◽  
Daniel J. Hill ◽  
Matthew J. Pound ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Future Climate ◽  
Future Climate Change ◽  
Anthropogenic Emissions ◽  
Earth System ◽  
System Sensitivity ◽  
Earth History ◽  
Scientific Papers

Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race’s current grand climate experiment . This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean–atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene–Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO 2 forcing—whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate—or the sensitivity of the climate system itself to CO 2 was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO 2 ) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO 2 concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO 2 thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.

Bias correction of extreme values of high resolution climate simulations for risk analysis.

2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Values ◽  
The Body ◽  
Future Climate ◽  
Return Periods ◽  
Climate Conditions ◽  
Mitigation And Adaptation ◽  
Climate Simulations ◽  
The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

A Weighted Rearranged Spectral Equation Method for Structural Model Updating

1995 ◽  
Author(s):  
José Roberto F. Arruda ◽  
Carlson Antonio M. Verçosa
Keyword(s):  
Degrees Of Freedom ◽  
Structural Model ◽  
Model Updating ◽  
Structural Connectivity ◽  
Computational Cost ◽  
Force Balance ◽  
Dynamic Force ◽  
Stiffness Coefficients ◽  
Spring System ◽  
Spectral Equation

Abstract A new structural model updating method based on the dynamic force balance is presented. The method consists of rearranging the spectral equation so that measured modes and natural frequencies can be used to compute directly updated stiffness coefficients. The proposed method preserves both the structural connectivity and reciprocity, which translate into sparsity and symmetry of the stiffness matrix, respectively. Large changes in small-valued stiffness coefficients are avoided using parameter weighting in the rearranged spectral equation solution. It is shown that the proposed method produces results which are similar to the results obtained using Alvar Kabe’s method, with the advantages of simpler formulation and smaller computational cost. A simple example of an 8 degrees-of-freedom mass-spring system, originally used by Kabe to present his method, is used here to evaluate the proposed method.

scholarly journals Impacts of the North Atlantic Warming Hole in Future Climate Projections: Mean Atmospheric Circulation and the North Atlantic Jet

2019 ◽  
Vol 32 (10) ◽  
pp. 2673-2689 ◽  
Author(s):  
Melissa Gervais ◽  
Jeffrey Shaman ◽  
Yochanan Kushnir
Keyword(s):  
Atmospheric Circulation ◽  
North Atlantic ◽  
Forced Response ◽  
Future Climate ◽  
Climate Projections ◽  
Transient Eddy ◽  
The North ◽  
Climate Simulations ◽  
The North Atlantic ◽  
The Impact

Abstract In future climate simulations there is a pronounced region of reduced warming in the subpolar gyre of the North Atlantic Ocean known as the North Atlantic warming hole (NAWH). This study investigates the impact of the North Atlantic warming hole on atmospheric circulation and midlatitude jets within the Community Earth System Model (CESM). A series of large-ensemble atmospheric model experiments with prescribed sea surface temperature (SST) and sea ice are conducted, in which the warming hole is either filled or deepened. Two mechanisms through which the NAWH impacts the atmosphere are identified: a linear response characterized by a shallow atmospheric cooling and increase in sea level pressure shifted slightly downstream of the SST changes, and a transient eddy forced response whereby the enhanced SST gradient produced by the NAWH leads to increased transient eddy activity that propagates vertically and enhances the midlatitude jet. The relative contributions of these two mechanisms and the details of the response are strongly dependent on the season, time period, and warming hole strength. Our results indicate that the NAWH plays an important role in midlatitude atmospheric circulation changes in CESM future climate simulations.

scholarly journals Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

2019 ◽  
Vol 124 (7) ◽  
pp. 3903-3929 ◽  
Author(s):  
Almudena García‐García ◽  
Francisco José Cuesta‐Valero ◽  
Hugo Beltrami ◽  
Jason E. Smerdon
Keyword(s):  
Ground Temperature ◽  
Future Climate ◽  
Climate Simulations

scholarly journals Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations

2018 ◽  
Vol 31 (6) ◽  
pp. 2115-2131 ◽  
Author(s):  
Steven C. Chan ◽  
Elizabeth J. Kendon ◽  
Nigel Roberts ◽  
Stephen Blenkinsop ◽  
Hayley J. Fowler
Keyword(s):  
Extreme Precipitation ◽  
Land Surface ◽  
Large Scale ◽  
Future Climate ◽  
Cumulus Parameterization ◽  
Hourly Precipitation ◽  
Vertical Stability ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Precipitation Events

Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach.

Modular Distributed Models of Engineering Structures

2003 ◽  
Author(s):  
Clark J. Radcliffe ◽  
Jon Sticklen
Keyword(s):  
Engineering Design ◽  
Degrees Of Freedom ◽  
Structural Model ◽  
Integrated Design ◽  
Model Systems ◽  
Structural Stiffness ◽  
Engineering Structures ◽  
Distributed Modeling ◽  
Communications Network ◽  
Component Models

Approaches to engineering design and manufacturing such as integrated design and manufacture and just in time fabrication depend on interaction with and among component supply companies that most often use very diverse technologies. The Internet Engineering Design Agents (i-EDA) software system uses a distributed, component-based, agent methodology that is realized following a strong black box approach to modeling. An individual Design Agent (DA) is a virtual product capable of encapsulating both descriptive and model based information about the product it represents. Hierarchically recursive agents for sub-systems and/or components are linked via a communications network to form larger integrated model systems. A two dimensional bridge system structural model is used as an example to illustrate the distributed assembly of structural models from components registered as DA’s on a communications network. Modular Distributed Modeling (MDM) of engineering structures performs static deflection analysis using traditional, fixed causality, structural stiffness models. This paper presents the methodology required to assemble traditional structural stiffness models provided by internet agents representing structural components. The methodology discussed assembles these component models into the structural stiffness model of an assembly distributed by an agents represent that physical assembly of components. Using this modular distributed modeling method; models of complex assemblies can be built and distributed while hiding the topology and characteristics of their structural subassemblies. The automated, modular, assembly of structural stiffness models will be derived for discrete physical connections. Discrete connections are important to the assembly of components such as truss and shaft structures where the relationship between component displacements involve discrete, matching, degrees of freedom on components to be assembled. Specific examples of discrete assembly of truss bridge component models will be presented.

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