Discussion Of Model Limitations Research Articles

A hierarchical Bayesian model of storm surge and total water levels across the Great Lakes shoreline – Lake Ontario

This study presents a novel approach to determine the distribution of compound flood events composed of storm surge and static water levels along the Great Lakes shoreline. A mixture distribution of the bulk (Student-t) and tail (GPD-negative binomial) components of storm surge is estimated in a hierarchical Bayesian modeling framework. Parameters are modeled across the entire shoreline using Gaussian processes and hourly gauged data, with priors for spatial autocorrelation informed by numerical output from a lake hydrodynamic model. The distribution of total water levels is obtained through Monte Carlo sampling that combines the estimated distribution of surge with stochastic traces of static lake levels that account for water level management, seasonality, and plausible variability in water supplies. The approach can therefore support coastal flood risk assessments in cases when the distribution of static water levels changes are due to altered water level management or climate change. The model is applied in a case study on Lake Ontario. Results suggest that spatial variability in parameter estimates varies significantly by month and mixture distribution component. Evaluations of performance indicate the model is able to capture adequately storm surge behavior at gauges across the lakeshore, even under cross-validation. A frequency analysis of total water levels at two ungauged sites is presented, with specific attention given to the implications of model assumptions on uncertainty in design events. The paper concludes with a discussion of model limitations and avenues for future work.

Ocean Biogeochemistry in GFDL's Earth System Model 4.1 and Its Response to Increasing Atmospheric CO2

AbstractThis contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation of GFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2yr−1simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments.

Potential COVID-19 Outbreak in Fire Camp: Modeling Scenarios and Interventions

The global COVID-19 pandemic will pose unique challenges to the management of wildland fire in 2020. Fire camps may provide an ideal setting for the transmission of SARS-CoV-2, the virus that causes COVID-19. However, intervention strategies can help minimize disease spread and reduce the risk to the firefighting community. We developed a COVID-19 epidemic model to highlight the risks posed by the disease during wildland fire incidents. Our model accounts for the transient nature of the population on a wildland fire incident, which poses unique risks to the management of communicable diseases in fire camps. We used the model to assess the impact of two types of interventions: the screening of a firefighter arriving on an incident, and social distancing measures. Our results suggest that both interventions are important to mitigate the risks posed by the SARS-CoV-2 virus. However, screening is relatively more effective on short incidents, whereas social distancing is relatively more effective during extended campaigns. We conclude with a discussion of model limitations and potential extensions to the model.

TH-C-108-01: Radiobiological Models in Brachytherapy Treatment Planning and Evaluation

Brachytherapy utilizes a multitude of radioactive sources and treatment techniques that often exhibit drastically different spatial and temporal dose delivery patterns from one another and from external beam radiotherapy. Typical photon energies vary from 0.02 MeV to 1 MeV and decay half-lives vary from days to years. Treatments can consist of single-fraction continuous low-dose-rate irradiations over a period of days or months to multi-fraction high-dose-rate irradiations of different dose fractionations. The clinical impact of such diverse spatial-temporal variations cannot be adequately assessed using traditional physical dose-based indices alone because these indices do not take into account the complex interplay between the dynamics of dose delivery and the biological response of the irradiated cells. Radiobiological models that capture the interacting effects of dose delivery with cellular biology can potentially provide a useful clinical tool for comparing and optimizing the relative clinical effectiveness of different brachytherapy treatment strategies. These models have been used increasingly by clinical medical physicists over the last decade in research settings. Currently, there are several different models presented in the literature with a range of applications and limitations. Information on model parameters, uncertainties, and their impact on model predictions are also scattered in the literature. The primary goal of this educational course is to provide a comprehensive review of existing radiobiological models and parameters, and their use in the evaluation of selected brachytherapy modalities. Particular emphasis will be placed on discussion of model limitations that may hinder the proper interpretation of model predictions and practical implementation. Learning Objectives: 1. To understand the rationale and basis of existing radiobiological models used in the evaluation of brachytherapy treatments. 2. To recognize the underlying assumptions and limitations of existing models and their proper application in the relative comparison of competing brachytherapy modalities. 3. To be aware of the pitfalls regarding the selection, use, and interpretation of radiobiological models in treatment planning and evaluation ZC would like to acknowledge partial support of NIH grant R01 CA134627

The HAMP NPV Model: Development and Early Performance

The foreclosure crisis that began in 2008 triggered the need for new approaches to treat distressed mortgages. A key component of the Obama Administration's Home Affordable Modification Program (HAMP) was the development of a standardized Net Present Value (NPV) Model to identify troubled loans that were value‐enhancing candidates for payment‐reducing modifications. This article discusses the development of the HAMP NPV Model,1 its purpose and some important constraints that dictated its structure and limitations. We describe the structure and the estimation of the model in detail. We also describe the responsiveness of the model to key characteristics, such as loan‐to‐value and credit score, as well as provide new evidence on the relationship between HAMP modification performance and key borrower and modification characteristics. The article concludes with a discussion of model limitations and the future role of systematic loan modification using NPV analysis.

The HAMP NPV Model: Development and Early Performance

The foreclosure crisis that began in 2008 triggered the need for new approaches to treat distressed mortgages. A key component of the Obama Administration’s Home Affordable Modification Program (HAMP) was the development of a standardized Net Present Value (NPV) model to identify troubled loans that were value-enhancing candidates for payment-reducing modifications. This paper discusses the development of the HAMP NPV model, its purpose, and some important constraints that dictated its structure and limitations. We describe the structure and the estimation of the model in detail. Furthermore, we describe the responsiveness of the model to key characteristics, such as loan to value and credit score and provide new evidence on the relationship between HAMP modification performance and key borrower and modification characteristics. The paper concludes with a discussion of model limitations and suggestions for further refinement of the model.

Developing a Computer Model to Simulate DBP Formation During Water Treatment

A computer program was developed to simulate disinfection by‐product formation, removal of natural organic matter, inorganic water quality changes, and disinfectant decay in water treatment processes. This article presents equations that simulate the formation of total trihalomethanes (TTHMs), removal of total organic carbon (TOC) and ultraviolet absorbance by alum coagulation, and changes in alkalinity and pH. These equations represent only a small fraction of the entire computer model. Model simulations are compared with limited sets of observed values. The central tendency of the model is to underpredict finished‐water pH by 4 percent, finished‐water TOC by 7 percent, and simulated distribution system TTHMs by 20–30 percent. A discussion of model limitations and research needs concludes the article.

An analytical method for aircraft collision risk estimation

Transportation system safety is difficult to assess, particularly when examining future systems that are unlike existing systems. The absence of consensus concerning safety metrics and associated mathematical techniques inhibits implementation of improvements. One method for assessing safety was recently applied to assess new air traffic control procedures. The method contains several steps, including use of a collision risk model. The model uses probability theory to assess collision risk between aircraft due to random deviations from course. Techniques that recognize human monitoring and intervention to avoid collisions must be combined with the model to obtain absolute values of risk. Examples of model application are presented, together with a discussion of model limitations and use.