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Title:

A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model

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A method for assimilating remotely sensed snow covered area (SCA) into the snow subroutine of a grid distributed precipitation-runoff model (PRM) is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC), which relates that cell's SCA to its snow cover mass balance. The assimilation is based on...

A method for assimilating remotely sensed snow covered area (SCA) into the snow subroutine of a grid distributed precipitation-runoff model (PRM) is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC), which relates that cell's SCA to its snow cover mass balance. The assimilation is based on Bayes' theorem, which requires a joint prior distribution of the SDC variables in all the grid cells. In this paper we propose a spatial model for this prior distribution, and include similarities and dependencies among the grid cells. Used to represent the PRM simulated snow cover state, our joint prior model regards two elevation gradients and a degree-day factor as global variables, rather than describing their effect separately for each cell. This transformation results in smooth normalised surfaces for the two related mass balance variables, supporting a strong inter-cell dependency in their joint prior model. The global features and spatial interdependency in the prior model cause each SCA observation to provide information for many grid cells. The spatial approach similarly facilitates the utilisation of observed discharge. Assimilation of SCA data using the proposed spatial model is evaluated in a 2400 km 2 mountainous region in central Norway (61 N, 9 E), based on two Landsat 7 ETM+ images generalized to 1 km 2 resolution. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. These results are largely improved compared to a cell-by-cell independent assimilation routine previously reported. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not started and the snow coverage is close to unity. Caution is therefore required when using early images. Minimize

Publisher:

Copernicus GmbH

Year of Publication:

2006-01-01T00:00:00Z

Document Type:

article

Language:

English

Subjects:

LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Physical geography ; LCC:GB3-5030 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Geography ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-...

LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Physical geography ; LCC:GB3-5030 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Geography ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Physical geography ; LCC:GB3-5030 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Geography ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; LCC:Physical geography ; LCC:GB3-5030 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; LCC:Physical geography ; LCC:GB3-5030 ; LCC:Geography. Anthropology. Recreation ; LCC:G Minimize

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http://www.hydrol-earth-syst-sci.net/10/369/2006/hess-10-369-2006.pdf

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Title:

A modelling approach to assessing the timescale uncertainties in proxy series with chronological errors

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The paper proposes an approach to assessment of timescale errors in proxy-based series with chronological uncertainties. The method relies on approximation of the physical process(es) forming a proxy archive by a random Gamma process. Parameters of the process are partly data-driven and partly determined from prior assumptions. For a particular ...

The paper proposes an approach to assessment of timescale errors in proxy-based series with chronological uncertainties. The method relies on approximation of the physical process(es) forming a proxy archive by a random Gamma process. Parameters of the process are partly data-driven and partly determined from prior assumptions. For a particular case of a linear accumulation model and absolutely dated tie points an analytical solution is found suggesting the Beta-distributed probability density on age estimates along the length of a proxy archive. In a general situation of uncertainties in the ages of the tie points the proposed method employs MCMC simulations of age-depth profiles yielding empirical confidence intervals on the constructed piecewise linear best guess timescale. It is suggested that the approach can be further extended to a more general case of a time-varying expected accumulation between the tie points. The approach is illustrated by using two ice and two lake/marine sediment cores representing the typical examples of paleoproxy archives with age models based on tie points of mixed origin. Minimize

Publisher:

Copernicus GmbH

Year of Publication:

2012-01-01T00:00:00Z

Document Type:

article

Language:

English

Subjects:

LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sci...

LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; DOAJ:Environmental Sciences ; DOAJ:Earth and Environmental Sciences ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G ; LCC:Environmental sciences ; LCC:GE1-350 ; LCC:Geography. Anthropology. Recreation ; LCC:G Minimize

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333 Economics of land & energy *(computed)*

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http://www.clim-past-discuss.net/8/31/2012/cpd-8-31-2012.pdf

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Title:

Mechanizing Domain Theory

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. We describe an encoding of major parts of domain theory and fixedpoint theory in the Pvs extension of the simply-typed -calculus; these formalizations comprise the encoding of mathematical structures like complete partial orders (domains), domain constructions, the Knaster-Tarski fixed-point theorem for monotonic functions, and variations of f...

. We describe an encoding of major parts of domain theory and fixedpoint theory in the Pvs extension of the simply-typed -calculus; these formalizations comprise the encoding of mathematical structures like complete partial orders (domains), domain constructions, the Knaster-Tarski fixed-point theorem for monotonic functions, and variations of fixed-point induction. Altogether, these encodings form a conservative extension of the underlying Pvs logic. A major problem of embedding mathematical theories like domain theory lies in the fact that developing and working with those theories usually generates myriads of applicability and type-correctness conditions. Our approach to exploiting the Pvs devices of predicate subtypes and judgements to establish many applicability conditions behind the scenes leads to a considerable reduction in the number of the conditions that actually need to be proved. We illustrate the applicability of our encodings by means of simple examples including a mechanized fixed-point induction proof in the context of relating different semantics of imperative programming constructs. Key words: Domain Theory, Fixed-Point Theory, Mechanized Theorem Proving 1. Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2009-04-15

Source:

http://www.cwi.nl/~bartels/Papers/MechanizingDomainTheory/fixpoints-domains3.ps.gz

http://www.cwi.nl/~bartels/Papers/MechanizingDomainTheory/fixpoints-domains3.ps.gz Minimize

Document Type:

text

Language:

en

Subjects:

Key words ; Domain Theory ; Fixed-Point Theory ; Mechanized Theorem Proving

Key words ; Domain Theory ; Fixed-Point Theory ; Mechanized Theorem Proving Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Approximate Bayesian Inference for Survival Models

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Bayesian analysis of time-to-event data, usually called survival analysis, has received increasing attention in the last years. In Cox-type models it allows to use information from the full likelihood instead of from a partial likelihood, so that the baseline hazard function and the model parameters can be jointly estimated. In general, Bayesian...

Bayesian analysis of time-to-event data, usually called survival analysis, has received increasing attention in the last years. In Cox-type models it allows to use information from the full likelihood instead of from a partial likelihood, so that the baseline hazard function and the model parameters can be jointly estimated. In general, Bayesian methods permit a full and exact posterior inference for any parameter or predictive quantity of interest. On the other side, Bayesian inference often relies on Markov Chain Monte Carlo (MCMC) techniques which, from the user point of view, may appear slow at delivering answers. In this paper, we show how a new inferential tool named Integrated Nested Laplace approximations (INLA) can be adapted and applied to many survival models making Bayesian analysis both fast and accurate without having to rely on MCMC based inference. Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-01-30

Source:

http://www.math.ntnu.no/preprint/statistics/2010/S3-2010.pdf

http://www.math.ntnu.no/preprint/statistics/2010/S3-2010.pdf Minimize

Document Type:

text

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en

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Implementing Approximate Bayesian Inference for Survival Analysis using Integrated Nested Laplace Approximations

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In this report, we investigate the use of INLA, (Martino and Rue, 2008) to solve Bayesian inferential problems in Bayesisan Survival analsysis. In particular we consider the Exponential and Weibulldistributed lifetimes with and without censoring and frailty, and Cox-models with piecewise constant and piecewise linear baseline hazard. We demonstr...

In this report, we investigate the use of INLA, (Martino and Rue, 2008) to solve Bayesian inferential problems in Bayesisan Survival analsysis. In particular we consider the Exponential and Weibulldistributed lifetimes with and without censoring and frailty, and Cox-models with piecewise constant and piecewise linear baseline hazard. We demonstrate that all these models can (in most cases) be expressed as a latent Gaussian model (LGM) so that integrated nested Laplace approximations proposed by Rue et al. (2009) can be applied. We show comparison with the results obtained with INLA and those obtained with extensive runs with Markov chain Monte Carlo methods. The results obtained are again ”practically exact” and support the general experience of Rue et al. (2009). Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-01-30

Source:

http://www.math.ntnu.no/preprint/statistics/2010/S1-2010.pdf

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text

Language:

en

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Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

A toolbox for fitting complex spatial point process models using integrated Laplace transformation (INLA)

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-10-29

Source:

http://www.math.ntnu.no/preprint/statistics/2010/S6-2010.pdf

http://www.math.ntnu.no/preprint/statistics/2010/S6-2010.pdf Minimize

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text

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en

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Title:

observations in a gridded snow model

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A Bayesian spatial assimilation scheme for snow coverage

A Bayesian spatial assimilation scheme for snow coverage Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-10-28

Source:

http://hal.archives-ouvertes.fr/docs/00/30/48/60/PDF/hess-10-369-2006.pdf

http://hal.archives-ouvertes.fr/docs/00/30/48/60/PDF/hess-10-369-2006.pdf Minimize

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Title:

Sciences Discussions

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Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2008-08-14

Source:

http://www.hydrol-earth-syst-sci-discuss.net/2/1185/2005/hessd-2-1185-2005-print.pdf

http://www.hydrol-earth-syst-sci-discuss.net/2/1185/2005/hessd-2-1185-2005-print.pdf Minimize

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text

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en

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Title:

concentration through

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(will be inserted by the editor) Spatio-temporal modeling of particulate matter

(will be inserted by the editor) Spatio-temporal modeling of particulate matter Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2014-12-10

Source:

http://www.math.ntnu.no/inla/r-inla.org/case-studies/Cameletti2012/Cameletti_et_al_2012_acc.pdf

http://www.math.ntnu.no/inla/r-inla.org/case-studies/Cameletti2012/Cameletti_et_al_2012_acc.pdf Minimize

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text

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en

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Title:

Trondheim, Norway. Fitting a log Gaussian Cox process with temporally varying effects – a case study

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Fitting a log Gaussian Cox process with temporally varying effects a case study by

Fitting a log Gaussian Cox process with temporally varying effects a case study by Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2011-04-04

Source:

http://www.math.ntnu.no/preprint/statistics/2010/S17-2010.pdf

http://www.math.ntnu.no/preprint/statistics/2010/S17-2010.pdf Minimize

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text

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en

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