Download or read book Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model written by and published by . This book was released on 2013 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Global Sensitivity Analysis Probabilistic Calibration and Predictive Assessment for the Data Assimilation Linked Ecosystem Carbon Model written by and published by . This book was released on 2015 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employed in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.
Download or read book Description Calibration and Sensitivity Analysis of the Local Ecosystem Submodel of a Global Model of Carbon and Nitrogen Cycling and the Water Balance in the Terrestrial Biosphere written by and published by . This book was released on 1995 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have developed a geographically-distributed ecosystem model for the carbon, nitrogen, and water dynamics of the terrestrial biosphere TERRA. The local ecosystem model of TERRA consists of coupled, modified versions of TEM and DAYTRANS. The ecosystem model in each grid cell calculates water fluxes of evaporation, transpiration, and runoff; carbon fluxes of gross primary productivity, litterfall, and plant and soil respiration; and nitrogen fluxes of vegetation uptake, litterfall, mineralization, immobilization, and system loss. The state variables are soil water content; carbon in live vegetation; carbon in soil; nitrogen in live vegetation; organic nitrogen in soil and fitter; available inorganic nitrogen aggregating nitrites, nitrates, and ammonia; and a variable for allocation. Carbon and nitrogen dynamics are calibrated to specific sites in 17 vegetation types. Eight parameters are determined during calibration for each of the 17 vegetation types. At calibration, the annual average values of carbon in vegetation C, show site differences that derive from the vegetation-type specific parameters and intersite variation in climate and soils. From calibration, we recover the average C{sub v} of forests, woodlands, savannas, grasslands, shrublands, and tundra that were used to develop the model initially. The timing of the phases of the annual variation is driven by temperature and light in the high latitude and moist temperate zones. The dry temperate zones are driven by temperature, precipitation, and light. In the tropics, precipitation is the key variable in annual variation. The seasonal responses are even more clearly demonstrated in net primary production and show the same controlling factors.
Download or read book Description Calibration and Sensitivity Analysis of the Local Ecosystem Submodel of a Global Model of Carbon and Nitrogen Cycling and the Water Balance of the Terrestrial Biosphere written by and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Download or read book A Review of Parameter Sensitivity Methods Applicable to Ecosystem Models written by K. A. Rose and published by . This book was released on 1981 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ecology and the Environment written by Russell K. Monson and published by Springer. This book was released on 2014-10-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, plant biology is considered from the perspective of plants and their surrounding environment, including both biotic and abiotic interactions. The intended audience is undergraduate students in the middle or final phases of their programs of study. Topics are developed to provide a rudimentary understanding of how plant-environment interactions span multiple spatiotemporal scales, and how this rudimentary knowledge can be applied to understand the causes of ecosystem vulnerabilities in the face of global climate change and expansion of natural resource use by human societies. In all chapters connections are made from smaller to larger scales of ecological organization, providing a foundation for understanding plant ecology. Where relevant, environmental threats to ecological systems are identified and future research needs are discussed. As future generations take on the responsibility for managing ecosystem goods and services, one of the most effective resources that can be passed on is accumulated knowledge of how organisms, populations, species, communities and ecosystems function and interact across scales of organization. This book is intended to provide some of that knowledge, and hopefully provide those generations with the ability to avoid some of the catastrophic environmental mistakes that prior generations have made.
Download or read book Land Carbon Cycle Modeling written by Yiqi Luo and published by CRC Press. This book was released on 2022-08-18 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon moves through the atmosphere, through the oceans, onto land, and into ecosystems. This cycling has a large effect on climate – changing geographic patterns of rainfall and the frequency of extreme weather – and is altered as the use of fossil fuels adds carbon to the cycle. The dynamics of this global carbon cycling are largely predicted over broad spatial scales and long periods of time by Earth system models. This book addresses the crucial question of how to assess, evaluate, and estimate the potential impact of the additional carbon to the land carbon cycle. The contributors describe a set of new approaches to land carbon cycle modeling for better exploring ecological questions regarding changes in carbon cycling; employing data assimilation techniques for model improvement; and doing real- or near-time ecological forecasting for decision support. This book strives to balance theoretical considerations, technical details, and applications of ecosystem modeling for research, assessment, and crucial decision making. Key Features Helps readers understand, implement, and criticize land carbon cycle models Offers a new theoretical framework to understand transient dynamics of land carbon cycle Describes a suite of modeling skills – matrix approach to represent land carbon, nitrogen, and phosphorus cycles; data assimilation and machine learning to improve parameterization; and workflow systems to facilitate ecological forecasting Introduces a new set of techniques, such as semi-analytic spin-up (SASU), unified diagnostic system with a 1-3-5 scheme, traceability analysis, and benchmark analysis, for model evaluation and improvement Related Titles Isabel Ferrera, ed. Climate Change and the Oceanic Carbon Cycle: Variables and Consequences (ISBN 978-1-774-63669-5) Lal, R. et al., eds. Soil Processes and the Carbon Cycle (ISBN 978-0-8493-7441-8) Windham-Myers, L., et al., eds. A Blue Carbon Primer: The State of Coastal Wetland Carbon Science, Practice and Policy (ISBN 978-0-367-89352-1)
Download or read book Sensitivity Analysis in Earth Observation Modelling written by George P. Petropoulos and published by Elsevier. This book was released on 2016-10-07 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling. Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement. Outlines challenges and future prospects of sensitivity analysis implementation in earth observation modeling Provides readers with a roadmap for directing future efforts Includes case studies with applications from different regions around the globe, helping readers to explore strengths and weaknesses of the different methods in earth observation modeling Presents a step-by-step guide, providing the principles of each method followed by the application of variants, making the reference easy to use and follow
Download or read book Sensitivity Analysis of a Carbon Simulation Model and Its Application in a Montane Forest Environment written by Shiyong Xu and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sensitivity Analysis as an Aid in Modelling and Control of poorly defined Ecological Systems written by George M. Hornberger and published by . This book was released on 1982 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parameter Sensitivity and Interaction in Complex Environmental Models written by Thomas Michael Grieb and published by . This book was released on 2000 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ecological Forecasting written by Michael C. Dietze and published by Princeton University Press. This book was released on 2017-05-30 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online
Download or read book Advanced Modelling Techniques Studying Global Changes in Environmental Sciences written by and published by Elsevier. This book was released on 2015-10-08 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Modelling Techniques Studying Global Changes in Environmental Sciences discusses the need for immediate and effective action, guided by a scientific understanding of ecosystem function, to alleviate current pressures on the environment. Research, especially in Ecological Modeling, is crucial to support the sustainable development paradigm, in which the economy, society, and the environment are integrated and positively reinforce each other. Content from this book is drawn from the 2013 conference of the International Society for Ecological Modeling (ISEM), an important and active research community contributing to this arena. Some progress towards gaining a better understanding of the processes of global change has been achieved, but much more is needed. This conference provides a forum to present current research using models to investigate actions towards mitigating and adapting to change. - Presents state-of-the-art modeling techniques - Drawn from the 2013 conference of the International Society for Ecological Modeling (ISEM), an important and active research community contributing to this arena - Integrates knowledge of advanced modeling techniques in ecological and environmental sciences - Describes new applications for sustainability
Download or read book Global Sensitivity Analysis in Integrated Assessment Modeling written by Alena Miftakhova and published by . This book was released on 2019 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrated assessment modeling studies the nexus between the systems of climate and economy, both known for their high complexity and vast uncertainty. One key question is how sensitive climate policy inference produced by such models is to the uncertainty in their initial assumptions and the results of calibrations. Despite the broad literature on the topic--rich in both single-model and multi-model sensitivity analyses--universal, well-established practices for of analyzing the uncertainty in model's outcome are still missing. In this paper we argue for structured global sensitivity analysis (GSA) as an indispensable routine in climate-economic modeling.We apply a high-efficiency GSA method based on polynomial chaos expansions to the most commonly employed integrated assessment model (IAM), DICE. Our analysis provides two key insights. First, the subjective preselection of a subset of parameters of interest might omit the most influential ones. Second, the opposite strategy--one of pooling all parameters together and considering the model as a "black box"--might distort sensitivity indices. The best practice is thus to consider all exogenous parameters but adjust their set such that the fundamental relations within the model's structure are respected. The methodology of efficient GSA provides a clear, comprehensive decomposition of the uncertainty in model's output while minimizing computational costs, and hence is easily applicable to IAMs of higher complexity.
Download or read book Carbon Sequestration written by Mirhamed Sarkarfarshi and published by . This book was released on 2015 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon Capture and Sequestration (CCS) appears to be a practical technology for large-scale storage of CO2 to reduce anthropogenic CO2 emissions. Risk is an inevitable component of any geological project with the aim of storing CO2, and thus, is a concern to the public, policy makers, and scientists. Uncertainty that arises in the application of mathematical Carbon Sequestration (CS) models has a negative impact on the quality of risk assessment. Parameter uncertainty is believed to play a dominant role in the uncertainty of the outputs of the CS system models. However, reducing parameter uncertainty in CS models involves a trade-off between accuracy and computational efficiency of the model calibration methodology. The goal of this thesis is to reduce the trade-off between accuracy and computational efficiency when calibrating CS models. This is accomplished by, one, reducing the dimensionality of the parameter space; two, developing efficient calibration algorithms; and, three, reducing the computational cost of model simulation during calibration. The primary contributions of this thesis are: 1. The development of a sensitivity analysis to identify which parameters contribute the most to the uncertainty of the CS system model output, accounting for both parameter uncertainty and model structure. 2. The development of a computationally efficient and flexible Bayesian Importance Sampling (IS) method for continuous calibration of CS models using noisy monitoring data collected during the injection phase. 3. The development of the Response Surface Methodology (RSM) in a novel adaptive way to mitigate the computational demand of CS model calibration with negligible effect on the accuracy of the results. The methodologies and results presented in this thesis contribute to efficient calibration of CS models by identifying the most influential parameters in uncertainty of CS model outputs and calibrating those models accurately and efficiently.
Download or read book Improving Terrestrial Carbon Modeling written by Brett Raczka and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. This dissertation evaluates ways to improve biosphere model performance by 1) evaluating short term (5 years) performance across a broad range of representation complexity, 2) identifying sources of parametric uncertainty for long term (~100 years) performance within a mechanistically detailed model (Ecosystem Demography) and 3) identifying observations that best constrain long term performance. Chapter 2 evaluates the performance of continental-scale carbon flux estimates from 17 models against carbon flux observations from 36 North American flux towers. On average the regional model runs overestimate the annual gross primary productivity (5%) and total respiration (15%), and significantly underestimate the annual net carbon uptake (64%) during the time period 2000-2005. Comparison with site-level simulations implicate choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models perform the best at simulating carbon exchange at deciduous broadleaf sites; likely because a number of models use prescribed phenology to simulate seasonal fluxes. In general, the models do not perform as well for crop, grass and evergreen sites in terms of bias, correlation and magnitude of variation. The regional models match the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but have very little skill at inter-annual correlation and minimal skill at inter-annual magnitude of variability. The comparison of site versus regional level model runs demonstrate that 1) the inter-annual correlation is higher for site-level model runs but the skill remains low, and 2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best performing regional models that do not use flux tower calibration are CLM-CN, CASA--GFEDv2 and SIB3. Two empirical models, calibrated with flux towers observations, EC-MOD and MOD17+, perform as well as the best process-based models. This suggests that 1) empirical, calibrated models can perform as well as complex, process-based models, and 2) combining process-based model structure with relevant constraining data could significantly improve model performance. Through a sensitivity analysis of the Ecosystem Demography model (version 2.1), Chapter 3 identifies quantum efficiency and leaf respiration rate parameters as the highest contributors to model uncertainty regardless of time frame (annual, decadal, centennial). This finding is sensitive to methodological choices within the meta-analysis process. Trait data provides relatively modest constraint upon the model simulation whereas integrative measurements of NEE and AGB provide strong constraints to the model and parameter uncertainty. Key actions for model improvement include 1) locating additional measurements related to quantum efficiency, leaf respiration rate and water fluxes (e.g. sap flux, soil moisture) and 2) implementing a more mechanistic representation of growth respiration within the model.
