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Data Assimilation as Synchronization of Truth and Model: Experiments with the Three-Variable Lorenz System*
Abstract The potential use of chaos synchronization techniques in data assimilation for numerical weather prediction models is explored by coupling a Lorenz three-variable system that representsExpand
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Stability of model performance and parameter values on two catchments facing changes in climatic conditions
Abstract Hydrological models are often used for studying the hydrological effects of climate change; however, the stability of model performance and parameter values under changing climate conditionsExpand
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Numerically Stable Algorithms for Inversion of Block Tridiagonal and Banded Matrices
We provide a new representation for the inverse of block tridiagonal and banded matrices. The new representation is shown to be numerically stable over a variety of block tridiagonal matrices, inExpand
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A reduced FVE formulation based on POD method and error analysis for two-dimensional viscoelastic problem☆
Abstract Proper orthogonal decomposition (POD) method has been successfully used in the reduced-order modeling of complex systems. In this paper, we extend the applications of POD method, i.e.,Expand
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Univariate and Multivariate Assimilation of AIRS Humidity Retrievals with the Local Ensemble Transform Kalman Filter
Abstract This study uses the local ensemble transform Kalman filter to assimilate Atmospheric Infrared Sounder (AIRS) specific humidity retrievals with pseudo relative humidity (pseudo-RH) as theExpand
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Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM
This paper compares the performance of the Local Ensemble Transform Kalman Filter (LETKF) with the Physical-Space Statistical Analysis System (PSAS) under a perfect model scenario. PSAS is a 3D-VarExpand
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TWO-FIELD MODELS OF DARK ENERGY WITH EQUATION OF STATE ACROSS -1
In this paper, we study the possibility of building two-field models of dark energy with equation of state across -1. Specifically we will consider two classes of models: one consists of two scalarExpand
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Modelling runoff and its components in Himalayan basins
The hydrology of Himalayan basins is not well understood due to the complexities in the climate and geography, and the scarcity of data. The objective of this study is to quantitatively assess theExpand
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The Choice of Sample Size for Mortality Forecasting: A Bayesian Learning Approach
Forecasted mortality rates using mortality models proposed in the recent literature are sensitive to the sample size. In this paper we propose a method based on Bayesian learning to determineExpand
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