Validation and Quantification of Uncertainty in Coupled Climate Models Using Network Analysis

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Publisher :
ISBN 13 :
Total Pages : 12 pages
Book Rating : 4.:/5 (946 download)

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Book Synopsis Validation and Quantification of Uncertainty in Coupled Climate Models Using Network Analysis by :

Download or read book Validation and Quantification of Uncertainty in Coupled Climate Models Using Network Analysis written by and published by . This book was released on 2015 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ''areas'', i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956-2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the 'strength' of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.

Calibration of Watershed Models

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Publisher : John Wiley & Sons
ISBN 13 : 087590355X
Total Pages : 356 pages
Book Rating : 4.8/5 (759 download)

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Book Synopsis Calibration of Watershed Models by : Qingyun Duan

Download or read book Calibration of Watershed Models written by Qingyun Duan and published by John Wiley & Sons. This book was released on 2003-01-10 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. These models are based on general mathematical descriptions of the watershed processes that transform natural forcing (e.g., rainfall over the landscape) into response (e.g., runoff in the rivers). The user of a watershed hydrology model must specify the model parameters before the model is able to properly simulate the watershed behavior.

Uncertainty Quantification and Verification an Validation for Climate Modeling

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Publisher :
ISBN 13 :
Total Pages : 2 pages
Book Rating : 4.:/5 (971 download)

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Book Synopsis Uncertainty Quantification and Verification an Validation for Climate Modeling by :

Download or read book Uncertainty Quantification and Verification an Validation for Climate Modeling written by and published by . This book was released on 2016 with total page 2 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Reinforcement Learning

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Publisher :
ISBN 13 : 9781680830880
Total Pages : 146 pages
Book Rating : 4.8/5 (38 download)

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Book Synopsis Bayesian Reinforcement Learning by : Mohammad Ghavamzadeh

Download or read book Bayesian Reinforcement Learning written by Mohammad Ghavamzadeh and published by . This book was released on 2015-11-18 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods for machine learning have been widely investigated, yielding principled methods for incorporating prior information into inference algorithms. This monograph provides the reader with an in-depth review of the role of Bayesian methods for the reinforcement learning (RL) paradigm. The major incentives for incorporating Bayesian reasoning in RL are that it provides an elegant approach to action-selection (exploration/exploitation) as a function of the uncertainty in learning, and it provides a machinery to incorporate prior knowledge into the algorithms. Bayesian Reinforcement Learning: A Survey first discusses models and methods for Bayesian inference in the simple single-step Bandit model. It then reviews the extensive recent literature on Bayesian methods for model-based RL, where prior information can be expressed on the parameters of the Markov model. It also presents Bayesian methods for model-free RL, where priors are expressed over the value function or policy class. Bayesian Reinforcement Learning: A Survey is a comprehensive reference for students and researchers with an interest in Bayesian RL algorithms and their theoretical and empirical properties.

Uncertainty Management in Remote Sensing of Climate Data

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Publisher : National Academies Press
ISBN 13 : 0309139589
Total Pages : 63 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Uncertainty Management in Remote Sensing of Climate Data by : National Research Council

Download or read book Uncertainty Management in Remote Sensing of Climate Data written by National Research Council and published by National Academies Press. This book was released on 2009-10-01 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users. In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data. The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.

Demystifying Climate Models

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Publisher : Springer
ISBN 13 : 3662489597
Total Pages : 282 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Demystifying Climate Models by : Andrew Gettelman

Download or read book Demystifying Climate Models written by Andrew Gettelman and published by Springer. This book was released on 2016-04-09 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.

From Maps to Models

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Publisher : National Academies Press
ISBN 13 : 0309449944
Total Pages : 135 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis From Maps to Models by : National Academies of Sciences, Engineering, and Medicine

Download or read book From Maps to Models written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-10-31 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: The United States faces numerous, varied, and evolving threats to national security, including terrorism, scarcity and disruption of food and water supplies, extreme weather events, and regional conflicts around the world. Effectively managing these threats requires intelligence that not only assesses what is happening now, but that also anticipates potential future threats. The National Geospatial-Intelligence Agency (NGA) is responsible for providing geospatial intelligence on other countriesâ€"assessing where exactly something is, what it is, and why it is importantâ€"in support of national security, disaster response, and humanitarian assistance. NGA's approach today relies heavily on imagery analysis and mapping, which provide an assessment of current and past conditions. However, augmenting that approach with a strong modeling capability would enable NGA to also anticipate and explore future outcomes. A model is a simplified representation of a real-world system that is used to extract explainable insights about the system, predict future outcomes, or explore what might happen under plausible what-if scenarios. Such models use data and/or theory to specify inputs (e.g., initial conditions, boundary conditions, and model parameters) to produce an output. From Maps to Models: Augmenting the Nation's Geospatial Intelligence Capabilities describes the types of models and analytical methods used to understand real-world systems, discusses what would be required to make these models and methods useful for geospatial intelligence, and identifies supporting research and development for NGA. This report provides examples of models that have been used to help answer the sorts of questions NGA might ask, describes how to go about a model-based investigation, and discusses models and methods that are relevant to NGA's mission.

New techniques for improving climate models, predictions and projections

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Publisher : Frontiers Media SA
ISBN 13 : 2889741397
Total Pages : 178 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis New techniques for improving climate models, predictions and projections by : Matthew Collins

Download or read book New techniques for improving climate models, predictions and projections written by Matthew Collins and published by Frontiers Media SA. This book was released on 2022-01-24 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space

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Publisher : National Academies Press
ISBN 13 : 0309492432
Total Pages : 29 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space by : National Academies of Sciences, Engineering, and Medicine

Download or read book Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-06-18 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space (National Academies Press, 2018) provides detailed guidance on how relevant federal agencies can ensure that the United States receives the maximum benefit from its investments in Earth observations from space, while operating within realistic cost constraints. This short booklet, designed to be accessible to the general public, provides a summary of the key ideas and recommendations from the full decadal survey report.

Handbook of Uncertainty Quantification

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Publisher : Springer
ISBN 13 : 9783319123844
Total Pages : 0 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Handbook of Uncertainty Quantification by : Roger Ghanem

Download or read book Handbook of Uncertainty Quantification written by Roger Ghanem and published by Springer. This book was released on 2016-05-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.

Uncertainty Quantification in Stochastic Climate Models

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis Uncertainty Quantification in Stochastic Climate Models by :

Download or read book Uncertainty Quantification in Stochastic Climate Models written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Adjusting to Policy Expectations in Climate Change Modeling

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Publisher :
ISBN 13 :
Total Pages : 40 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Adjusting to Policy Expectations in Climate Change Modeling by :

Download or read book Adjusting to Policy Expectations in Climate Change Modeling written by and published by . This book was released on 1998 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper surveys and interprets the attitudes of scientists to the use of flux adjustments in climate projections with coupled Atmosphere Ocean General Circulation Models. The survey is based largely on the responses of 19 climate modellers to several questions and a discussion document circulated in 1995. We interpret the responses in terms of the following factors: the implicit assumptions which scientists hold about how the environmental policy process deals with scientific uncertainty over human-related global warming; the different scientific styles that exist in climate research; and the influence of organisations, institutions, and policy upon research agendas. We find evidence that scientists' perceptions of the policy process do play a role in shaping their scientific practices. In particular, many of our respondents expressed a preference for keeping discussion of the issue of flux adjustments within the climate modeling community, apparently fearing that climate contrarians would exploit the issue in the public domain. While this may be true, we point to the risk that such an approach may backfire. We also identify assumptions and cultural commitments lying at a deeper level which play at least as important a role as perceptions of the policy process in shaping scientific practices. This leads us to identify two groups of scientists, 'pragmatists' and 'purists, ' who have different implicit standards for model adequacy, and correspondingly are or are not willing to use flux adjustments.

Uncertainty Quantification in Laminated Composites

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Publisher : CRC Press
ISBN 13 : 1498784461
Total Pages : 375 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Uncertainty Quantification in Laminated Composites by : Sudip Dey

Download or read book Uncertainty Quantification in Laminated Composites written by Sudip Dey and published by CRC Press. This book was released on 2018-09-19 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.

Uncertainties in Climate Data Analysis

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Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.:/5 (935 download)

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Book Synopsis Uncertainties in Climate Data Analysis by :

Download or read book Uncertainties in Climate Data Analysis written by and published by . This book was released on 2015 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific inquiry requires that we formulate not only what we know, but also what we do not know and by how much. In climate data analysis, this involves an accurate specification of measured quantities and a consequent analysis that consciously propagates the measurement errors at each step. The dissertation presents a thorough analytical method to quantify errors of measurement inherent in paleoclimate data. An additional focus are the uncertainties in assessing the coupling between different factors that influence the global mean temperature (GMT). Paleoclimate studies critically rely on `proxy variables' that record climatic signals in natural archives. However, such proxy records inherently involve uncertainties in determining the age of the signal. We present a generic Bayesian approach to analytically determine the proxy record along with its associated uncertainty, resulting in a time-ordered sequence of correlated probability distributions rather than a precise time series. We further develop a recurrence based method to detect dynamical events from the proxy probability distributions. The methods are validated with synthetic examples and demonstrated with real-world proxy records. The proxy estimation step reveals the interrelations between proxy variability and uncertainty. The recurrence analysis of the East Asian Summer Monsoon during the last 9000 years confirms the well-known `dry' events at 8200 and 4400 BP, plus an additional significantly dry event at 6900 BP. We also analyze the network of dependencies surrounding GMT. We find an intricate, directed network with multiple links between the different factors at multiple time delays. We further uncover a significant feedback from the GMT to the El Niño Southern Oscillation at quasi-biennial timescales. The analysis highlights the need of a more nuanced formulation of influences between different climatic factors, as well as the limitations in trying to estimate such dependencies

Uncertainties in Climate Data Analysis

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (935 download)

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Book Synopsis Uncertainties in Climate Data Analysis by : Bedartha Goswami

Download or read book Uncertainties in Climate Data Analysis written by Bedartha Goswami and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific inquiry requires that we formulate not only what we know, but also what we do not know and by how much. In climate data analysis, this involves an accurate specification of measured quantities and a consequent analysis that consciously propagates the measurement errors at each step. The dissertation presents a thorough analytical method to quantify errors of measurement inherent in paleoclimate data. An additional focus are the uncertainties in assessing the coupling between different factors that influence the global mean temperature (GMT). Paleoclimate studies critically rely on `proxy variables' that record climatic signals in natural archives. However, such proxy records inherently involve uncertainties in determining the age of the signal. We present a generic Bayesian approach to analytically determine the proxy record along with its associated uncertainty, resulting in a time-ordered sequence of correlated probability distributions rather than a precise time series. We further develop a recurrence based method to detect dynamical events from the proxy probability distributions. The methods are validated with synthetic examples and demonstrated with real-world proxy records. The proxy estimation step reveals the interrelations between proxy variability and uncertainty. The recurrence analysis of the East Asian Summer Monsoon during the last 9000 years confirms the well-known `dry' events at 8200 and 4400 BP, plus an additional significantly dry event at 6900 BP. We also analyze the network of dependencies surrounding GMT. We find an intricate, directed network with multiple links between the different factors at multiple time delays. We further uncover a significant feedback from the GMT to the El Niño Southern Oscillation at quasi-biennial timescales. The analysis highlights the need of a more nuanced formulation of influences between different climatic factors, as well as the limitations in trying to estimate such dependencies

Uncertainty Quantification in Multiscale Materials Modeling

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Publisher : Woodhead Publishing Limited
ISBN 13 : 0081029411
Total Pages : 604 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Uncertainty Quantification in Multiscale Materials Modeling by : Yan Wang

Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing Limited. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.

Large-Scale Inverse Problems and Quantification of Uncertainty

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Publisher : John Wiley & Sons
ISBN 13 : 1119957583
Total Pages : 403 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Large-Scale Inverse Problems and Quantification of Uncertainty by : Lorenz Biegler

Download or read book Large-Scale Inverse Problems and Quantification of Uncertainty written by Lorenz Biegler and published by John Wiley & Sons. This book was released on 2011-06-24 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: Brings together the perspectives of researchers in areas of inverse problems and data assimilation. Assesses the current state-of-the-art and identify needs and opportunities for future research. Focuses on the computational methods used to analyze and simulate inverse problems. Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.