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Associations between higher exposure to potentially morally injurious events and negative posttraumatic cognition trajectories throughout cognitive processing therapy

Journal of Traumatic Stress, EarlyView.
Abstract Individuals with higher potentially morally injurious event (PMIE) exposure often exhibit elevated levels of negative posttraumatic cognitions (NPCs). Researchers have argued that individuals with moral injury (MI) following PMIE exposure experience more prescriptive NPCs than those without MI.
Anusha M. Limdi, Daniel R. Szoke, Dale L. Smith, Sarah A. Pridgen, Philip Held   +4 more
wiley   +1 more source

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Sequential Data Assimilation Techniques for Data Assimilation

, 2020
The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques.
M. Khaki
semanticscholar   +3 more sources

Data Assimilation for Streamflow Forecasting Using Extreme Learning Machines and Multilayer Perceptrons

Water Resources Research, 2020
Data assimilation allows for updating state variables in a model to represent the initial condition of a catchment more accurately than the initial OpenLoop simulation. In hydrology, data assimilation is often a prerequisite for forecasting. According to
Marie-Amélie Boucher, J. Quilty, Jan Adamowski   +2 more
semanticscholar   +1 more source

Atmospheric Modeling, Data Assimilation and Predictability

, 2002
1. Historical overview 2. The continuous equations 3. Discretization of the equations 4. Introduction to the parameterizations of subgrid-scale physical processes 5. Data assimilation 6.
Eugenia Kalnay
semanticscholar   +1 more source

DiffDA: a diffusion model for weather-scale data assimilation

International Conference on Machine Learning
The generation of initial conditions via accurate data assimilation is crucial for weather forecasting and climate modeling. We propose DiffDA as a denoising diffusion model capable of assimilating atmospheric variables using predicted states and sparse ...
Langwen Huang, Lukas Gianinazzi, Yuejiang Yu, P. Dueben, Torsten Hoefler   +4 more
semanticscholar   +1 more source

Nonlinear Data Assimilation

2015
This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities.
Van Leeuwen, Peter Jan, Cheng, Yuan, Reich, Sebastian (Prof.)   +2 more
openaire   +2 more sources

Data Assimilation

2011
This chapter outlines the problem of predictability and the methods used to blend, in an optimal way, observations with model computations in order to guide the latter and to produce improved simulations of geophysical fluid phenomena. The methods invoke physical as well as statistical reasoning and rely on certain approximations that facilitate their ...
Jean-Marie Beckers, Benoit Cushman-Roisin   +1 more
openaire   +2 more sources