Model simulations of the impact of selective credit policies and financial reforms

<p>The impact of Greenland freshwater on oceanic variables in the North Atlantic has been controversially discussed in the past. Within the framework of the German research project GROCE (Greenland Ice Sheet Ocean Interaction), we present a comprehensive study using ocean modelling results including and excluding the Greenland freshwater flux. The aim of this study is whether signatures of Greenland ice sheet melting found in ocean model simulations are visible in the observations. Therefore, we estimate changes in temperature, salinity, steric heights and sea level anomalies since the 1990s. The observational database includes altimetric and gravimetric satellite data as well as Argo floats. We will discuss similarities/differences between model simulations and observations for smaller regions around Greenland in the North Atlantic. As these experiments are available for two different horizontal resolutions, we will furthermore be able to assess the effects of an increased model resolution.</p>

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On the Choice of Ensemble Mean for Estimating the Forced Signal in the Presence of Internal Variability

Journal of Climate ◽

10.1175/jcli-d-17-0662.1 ◽

2018 ◽

Vol 31 (14) ◽

pp. 5681-5693 ◽

Cited By ~ 14

Author(s):

Leela M. Frankcombe ◽

Matthew H. England ◽

Jules B. Kajtar ◽

Michael E. Mann ◽

Byron A. Steinman

Keyword(s):

Regional Differences ◽

Climate Model ◽

Surface Air Temperature ◽

Internal Variability ◽

Single Model ◽

Sea Level Pressure ◽

Model Simulations ◽

Ensemble Mean ◽

Climate Model Simulations ◽

The Impact

Abstract In this paper we examine various options for the calculation of the forced signal in climate model simulations, and the impact these choices have on the estimates of internal variability. We find that an ensemble mean of runs from a single climate model [a single model ensemble mean (SMEM)] provides a good estimate of the true forced signal even for models with very few ensemble members. In cases where only a single member is available for a given model, however, the SMEM from other models is in general out-performed by the scaled ensemble mean from all available climate model simulations [the multimodel ensemble mean (MMEM)]. The scaled MMEM may therefore be used as an estimate of the forced signal for observations. The MMEM method, however, leads to increasing errors further into the future, as the different rates of warming in the models causes their trajectories to diverge. We therefore apply the SMEM method to those models with a sufficient number of ensemble members to estimate the change in the amplitude of internal variability under a future forcing scenario. In line with previous results, we find that on average the surface air temperature variability decreases at higher latitudes, particularly over the ocean along the sea ice margins, while variability in precipitation increases on average, particularly at high latitudes. Variability in sea level pressure decreases on average in the Southern Hemisphere, while in the Northern Hemisphere there are regional differences.

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Biomechanical Comparison of Real World Concussive Impacts in Children, Adolescents, and Adults

Journal of Biomechanical Engineering ◽

10.1115/1.4045808 ◽

2020 ◽

Vol 142 (7) ◽

Author(s):

Lauren Dawson ◽

David Koncan ◽

Andrew Post ◽

Roger Zemek ◽

Michael D. Gilchrist ◽

...

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Brain Tissue ◽

Dynamic Models ◽

Element Model ◽

Tissue Response ◽

Model Simulations ◽

Child Group ◽

Adolescents And Adults ◽

The Impact

Abstract Accidental falls occur to people of all ages, with some resulting in concussive injury. At present, it is unknown whether children and adolescents are at a comparable risk of sustaining a concussion compared to adults. This study reconstructed the impact kinematics of concussive falls for children, adolescents, and adults and simulated the associated brain tissue deformations. Patients included in this study were diagnosed with a concussion as defined by the Zurich Consensus guidelines. Eleven child, 10 adolescent, and 11 adult falls were simulated using mathematical dynamic models(MADYMO), with three ellipsoid pedestrian models sized to each age group. Laboratory impact reconstruction was conducted using Hybrid III head forms, with finite element model simulations of the brain tissue response using recorded impact kinematics from the reconstructions. The results of the child group showed lower responses than the adolescent group for impact variables of impact velocity, peak linear acceleration, and peak rotational acceleration but no statistical differences existed for any other groups. Finite element model simulations showed the child group to have lower strain values than both the adolescent and adult groups. There were no statistical differences between the adolescent and adult groups for any variables examined in this study. With the cases included in this study, young children sustained concussive injuries at lower modeled brain strains than adolescents and adults, supporting the theory that children may be more susceptible to concussive impacts than adolescents or adults.

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Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis

Natural Hazards ◽

10.1007/s11069-020-03906-z ◽

2020 ◽

Vol 101 (3) ◽

pp. 995-1017 ◽

Cited By ~ 2

Author(s):

Emrah Yalcin

Keyword(s):

Land Cover ◽

Hydrodynamic Model ◽

Flood Hazard ◽

Hazard Analysis ◽

Two Dimensional ◽

Urban Flood ◽

Model Simulations ◽

Land Cover Data ◽

The Impact

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Using Multi-Sensory and Multi-Dimensional Immersive Virtual Reality in Participatory Planning

Urban Science ◽

10.3390/urbansci4030034 ◽

2020 ◽

Vol 4 (3) ◽

pp. 34

Author(s):

Mahbubur Meenar ◽

Jennifer Kitson

Keyword(s):

Virtual Reality ◽

Focus Group ◽

Spatial Planning ◽

3D Model ◽

Emotional Responses ◽

Digital Technologies ◽

Participatory Planning ◽

Immersive Virtual Reality ◽

Model Simulations ◽

The Impact

In the last two decades, urban planners have embraced digital technologies to complement traditional public participation processes; research on the impact of smarter digital instruments, such as immersive virtual reality (IVR), however, is scant. We recruited 40 focus group participants to explore various formats of spatial planning scenario simulations in Glassboro, NJ, USA. Our study finds that the level of participation, memory recalls of scenarios, and emotional responses to design proposals are higher with multi-sensory and multi-dimensional IVR simulations than with standard presentations such as 2D videos of 3D model simulations, coupled with verbal presentations. We also discuss the limitations of IVR technology to assist urban planning practitioners in evaluating its potential in their own participatory planning efforts.

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The Impact of Nudging in the Meteorological Model for Retrospective Air Quality Simulations. Part I: Evaluation against National Observation Networks

Journal of Applied Meteorology and Climatology ◽

10.1175/2007jamc1790.1 ◽

2008 ◽

Vol 47 (7) ◽

pp. 1853-1867 ◽

Cited By ~ 74

Author(s):

Tanya L. Otte

Keyword(s):

Air Quality ◽

Meteorological Conditions ◽

Daily Maximum ◽

Air Quality Model ◽

Quality Model ◽

Meteorological Model ◽

Model Simulations ◽

Dynamic Analyses ◽

The Impact ◽

Over Time

Abstract It is common practice to use Newtonian relaxation, or nudging, throughout meteorological model simulations to create “dynamic analyses” that provide the characterization of the meteorological conditions for retrospective air quality model simulations. Given the impact that meteorological conditions have on air quality simulations, it has been assumed that the resultant air quality simulations would be more skillful by using dynamic analyses rather than meteorological forecasts to characterize the meteorological conditions, and that the statistical trends in the meteorological model fields are also reflected in the air quality model. This article, which is the first of two parts, demonstrates the impact of nudging in the meteorological model on retrospective air quality model simulations. Here, meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and using forecasts for a summertime period. The resultant fields are then used to characterize the meteorological conditions for emissions processing and air quality simulations using the Community Multiscale Air Quality (CMAQ) Modeling System. As expected, on average, the near-surface meteorological fields show a significant degradation over time in the forecasts (when nudging is not used), while the dynamic analyses maintain nearly constant statistical scores in time. The use of nudged MM5 fields in CMAQ generally results in better skill scores for daily maximum 1-h ozone mixing ratio simulations. On average, the skill of the daily maximum 1-h ozone simulation deteriorates significantly over time when nonnudged MM5 fields are used in CMAQ. The daily maximum 1-h ozone mixing ratio also degrades over time in the CMAQ simulation that uses MM5 dynamic analyses, although to a much lesser degree, despite no aggregate loss of skill over time in the dynamic analyses themselves. These results affirm the advantage of using nudging in MM5 to create the meteorological characterization for CMAQ for retrospective simulations, and it is shown that MM5-based dynamic analyses are robust at the surface throughout 5.5-day simulations.

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