scholarly journals Analyzing the Sensitivity of WRF’s Single-Layer Urban Canopy Model to Parameter Uncertainty Using Advanced Monte Carlo Simulation

2011 ◽  
Vol 50 (9) ◽  
pp. 1795-1814 ◽  
Author(s):  
Zhi-Hua Wang ◽  
Elie Bou-Zeid ◽  
Siu Kui Au ◽  
James A. Smith
Keyword(s):  
Monte Carlo ◽  
Parameter Uncertainty ◽  
Single Layer ◽  
Urban Canopy ◽  
Mitigation Strategies ◽  
Urban Atmosphere ◽  
Advective Transport ◽  
Surface Parameters ◽  
Input Parameters ◽  
The Impact

AbstractSingle-layer physically based urban canopy models (UCM) have gained popularity for modeling urban–atmosphere interactions, especially the energy transport component. For a UCM to capture the physics of conductive, radiative, and turbulent advective transport of energy, it is important to provide it with an accurate parameter space, including both mesoscale meteorological forcing and microscale surface inputs. While field measurement of all input parameters to a UCM is rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty for model performance. In this paper, an advanced Monte Carlo approach—namely, subset simulation—is used to quantify the impact of the uncertainty of surface input parameters on the output of an offline modified version of the Weather Research and Forecasting (WRF)-UCM. On the basis of the conditional sampling technique, the importance of surface parameters is determined in terms of their impact on critical model responses. It is found that model outputs (both critical energy fluxes and surface temperatures) are highly sensitive to uncertainties in urban geometry, whereas variations in emissivities and building interior temperatures are relatively insignificant. In addition, the sensitivity of the model to input surface parameters is also shown to be very weakly dependent on meteorological parameters. The statistical quantification of the model’s sensitivity to input parameters has practical implications, such as surface parameter calibrations in UCM and guidance for urban heat island mitigation strategies.

Spiegel Online

2017 ◽  
pp. 1-11
Author(s):  
Karl Schmedders ◽  
Armin Rott
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Web Site ◽  
Business Plan ◽  
Decision Makers ◽  
Bottom Line ◽  
Art Objects ◽  
Input Parameters ◽  
High Level ◽  
The Impact

Spiegel Online (www.spiegel.de) is the leading news Web site in Germany. The site was first designed to accompany Der Spiegel, one of Europe's largest and Germany's most influential weekly magazine, which has a weekly circulation of around one million. The site's content is produced by a team of more than fifty journalists writing in several categories: politics, business, networld, panorama, arts and entertainment, science, university, school, sports, travel, weather, and automobiles. The original content is complemented by articles purchased from news agencies and selected articles from the print edition. Spiegel-Verlag is a major contributor to the Hamburg Media School, which offers professional master's degree programs in Media Management (MBA), film, and journalism. In their second year, MBA students typically engage in consulting projects with major media companies. In a recent assignment, Spiegel Online posed two questions to the MBA team: are there any chances for an economically successful entry into the market for interactive classifieds? And if so, what should the business model look like in detail? A student team analyzed markets for classified ads and found one market segment that appeared to be particularly promising: the market for art objects. During the development of a business plan for a new venture in this market it became apparent that there is much uncertainty about the key input parameters to the business plan. As a result, it is very difficult to assess the viability of the business idea. How can the team properly account for the uncertain input parameters? What is the impact of this uncertainty on the bottom line? Will a Web site for art objects earn or lose money? How can the team communicate this uncertainty to a group of high-level decision makers who want a simple “go or no-go” recommendation?The objective is to make students aware of the applicability of Monte Carlo simulation to the analysis of complex business plans. Students should learn how to explicitly account for uncertain inputs in a business plan, how to assess the impact of uncertainty on the bottom line via Monte Carlo simulation, and how to communicate the results of their analysis to high-level decision makers.

A Monte Carlo Analysis of the Impact of Material Parameter Uncertainty on RCS Predictions

2021 ◽  
Author(s):  
Jon T. Kelley ◽  
Clifton C. Courtney ◽  
David A. Chamulak ◽  
Ali E. Yilmaz
Keyword(s):  
Monte Carlo ◽  
Parameter Uncertainty ◽  
Material Parameter ◽  
Monte Carlo Analysis ◽  
The Impact

Sensitivity of Life-Cycle Assessment Outcomes to Parameter Uncertainty: Implications for Material Procurement Decision-Making

2019 ◽  
Vol 2673 (3) ◽  
pp. 106-114 ◽  
Author(s):  
Chaitanya G. Bhat ◽  
Amlan Mukherjee
Keyword(s):  
Decision Making ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Parameter Uncertainty ◽  
Asphalt Mixtures ◽  
Point Estimates ◽  
Input Parameters ◽  
Material Procurement ◽  
Construct Equivalence ◽  
The Impact

This paper aims to apply an analytical approach to propagate parameter uncertainty through Life-Cycle Assessment (LCA) outcomes, and identify equivalence intervals that are applicable during material procurement decision-making. LCA outputs are usually presented as point estimates without accompanying confidence intervals, or associated margins of error, due to methodological ambiguity in accounting for uncertainties, be they epistemic (due to inherent randomness) or aleatory (due to lack of knowledge). This reduces the reliability of using LCA for design selection, and of decision-making during material procurement. This paper aims to fill this gap using a methodology based on Taylor’s first-order approximation to examine LCA outcomes for asphalt mixtures. The method is applied to assess the impact of variation in input flows on the estimated output emissions by propagating the parameter uncertainties through the LCA. It allows for the reporting of LCA outputs using intervals rather than point estimates. For competing designs, the overlap in intervals is used to construct equivalence intervals within which the effective impact of the designs can be considered equivalent due to expected variability in input parameters. The method is applied to construct equivalence intervals for the Global Warming Potential (GWP) of three asphalt mixtures, each having different levels of Reclaimed Asphalt Pavement (RAP). Their role in communicating LCA outcomes for decision-making is illustrated. Foreground data collected from 40 North American asphalt plants were used to estimate uncertainty in the input parameters of electricity and energy use in asphalt production. The paper adds to existing literature on uncertainties in pavement LCAs by establishing the need to incorporate uncertainty when using LCA to support decision-making during material procurement.

scholarly journals Assessing the Impact of Enhanced Hydrological Processes on Urban Hydrometeorology with Application to Two Cities in Contrasting Climates

2016 ◽  
Vol 17 (4) ◽  
pp. 1031-1047 ◽  
Author(s):  
Jiachuan Yang ◽  
Zhi-Hua Wang ◽  
Matei Georgescu ◽  
Fei Chen ◽  
Mukul Tewari
Keyword(s):  
Water Cycle ◽  
Wrf Model ◽  
Single Layer ◽  
Urban Canopy ◽  
Field Measurements ◽  
Green Roofs ◽  
The United States ◽  
Climatic Conditions ◽  
Hydrological Processes ◽  
The Impact

Abstract To enhance the capability of models in better characterizing the urban water cycle, physical parameterizations of urban hydrological processes have been implemented into the single-layer urban canopy model in the widely used Weather Research and Forecasting (WRF) Model. While the new model has been evaluated offline against field measurements at various cities, its performance in online settings via coupling to atmospheric dynamics requires further examination. In this study, the impact of urban hydrological processes on regional hydrometeorology of the fully integrated WRF–urban modeling system for two major cities in the United States, namely, Phoenix and Houston, is assessed. Results show that including hydrological processes improves prediction of the 2-m dewpoint temperature, an indicative measure of coupled thermal and hydrological processes. The implementation of green roof systems as an urban mitigation strategy is then tested at the annual scale. The reduction of environmental temperature and increase of humidity by green roofs indicate strong diurnal and seasonal variations and are significantly affected by geographical and climatic conditions. Comparison with offline studies reveals that land–atmosphere interactions play a crucial role in determining the effect of green roofs.

scholarly journals Modeling the Impacts of City-Scale “Ventilation Corridor” Plans on Human Exposure to Intra-Urban PM2.5 Concentrations

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1269
Author(s):  
Chao Liu ◽  
Qian Shu ◽  
Sen Huang ◽  
Jingwei Guo
Keyword(s):  
Land Use ◽  
Aerodynamic Resistance ◽  
Single Layer ◽  
Urban Canopy ◽  
Simulation Models ◽  
Roughness Height ◽  
Deposition Flux ◽  
Spatial Form ◽  
Wind Speeds ◽  
The Impact

Increasingly, Chinese cities are proposing city-scale ventilation corridors (VCs) to strengthen wind velocities and decrease pollution concentrations, although their influences are ambiguous. To assess VC impacts, an effort has been made to predict the impact of VC solutions in the high density and diverse land use of the coastal city of Shanghai, China, in this paper. One base scenario and three VC scenarios, with various VC widths, locations, and densities, were first created. Then, the combination of the Weather Research and Forecasting/Single-Layer Urban Canopy Model (WRFv.3.4/UCM) and Community Multiscale Air Quality (CMAQv.5.0.1) numerical simulation models were employed to comprehensively evaluate the impacts of urban spatial form and VC plans on PM2.5 concentrations. The modeling results indicated that concentrations increased within the VCs in both summer and winter, and the upwind concentration decreased in winter. These counter-intuitive results could be explained by decreased planetary boundary layer (PBL), roughness height, deposition rate, and wind speeds induced by land use and urban height modifications. PM2.5 deposition flux decreased by 15–20% in the VCs, which was attributed to the roughness height decrease for it weakens aerodynamic resistance (Ra). PBL heights within the VCs decreased 15–100 m, and the entire Shanghai’s PBL heights also decreased in general. The modeling results suggest that VCs may not be as functional as certain urban planners have presumed.

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

scholarly journals The effect of ionic defect interactions on the hydration of yttrium-doped barium zirconate

2021 ◽  
Author(s):  
Sebastian Eisele ◽  
Fabian M. Draber ◽  
Steffen Grieshammer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
First Principles ◽  
Barium Zirconate ◽  
First Principles Calculations ◽  
Defect Interactions ◽  
The Impact ◽  
Ionic Defect

First principles calculations and Monte Carlo simulations reveal the impact of defect interactions on the hydration of barium-zirconate.

scholarly journals Improving Drought Tolerance in Mungbean (Vigna radiata L. Wilczek): Morpho-Physiological, Biochemical and Molecular Perspectives

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1534
Author(s):  
Chandra Mohan Singh ◽  
Poornima Singh ◽  
Chandrakant Tiwari ◽  
Shalini Purwar ◽  
Mukul Kumar ◽  
...  
Keyword(s):  
Drought Stress ◽  
Drought Tolerance ◽  
Crop Production ◽  
Mitigation Strategies ◽  
Theoretical Research ◽  
Whole Genome Sequence ◽  
Complex Nature ◽  
Drought Tolerant ◽  
Breeding Programmes ◽  
The Impact

Drought stress is considered a severe threat to crop production. It adversely affects the morpho-physiological, biochemical and molecular functions of the plants, especially in short duration crops like mungbean. In the past few decades, significant progress has been made towards enhancing climate resilience in legumes through classical and next-generation breeding coupled with omics approaches. Various defence mechanisms have been reported as key players in crop adaptation to drought stress. Many researchers have identified potential donors, QTLs/genes and candidate genes associated to drought tolerance-related traits. However, cloning and exploitation of these loci/gene(s) in breeding programmes are still limited. To bridge the gap between theoretical research and practical breeding, we need to reveal the omics-assisted genetic variations associated with drought tolerance in mungbean to tackle this stress. Furthermore, the use of wild relatives in breeding programmes for drought tolerance is also limited and needs to be focused. Even after six years of decoding the whole genome sequence of mungbean, the genome-wide characterization and expression of various gene families and transcriptional factors are still lacking. Due to the complex nature of drought tolerance, it also requires integrating high throughput multi-omics approaches to increase breeding efficiency and genomic selection for rapid genetic gains to develop drought-tolerant mungbean cultivars. This review highlights the impact of drought stress on mungbean and mitigation strategies for breeding high-yielding drought-tolerant mungbean varieties through classical and modern omics technologies.

Sign in / Sign up

Export Citation Format

Share Document