Immigrant Wage and Employment Assimilation: A Comparison of Methods We compare alternative methods for estimating immigrant wage and employment assimilation using unique panel data over 2001–2009 for a large, nationally-representative sample of immigrants. Previous assimilation estimates have been mainly based on crosssectional data and have therefore suffered from a range of potential biases. ...

Data assimilation using ensemble Kalman filters (EnKF) has led to significant improvements in atmospheric state estimation. The advantages of EnKF over common operational assimilation methods such as three-dimensional variational (3D-VAR) methods and its impressive performance in the assimilation of radar data at convective scales have led to its increasing popularity. While most previous studi...

This paper investigates the slowdown in earnings assimilation of recent immigrants to the U.S. I find that recent immigrant cohorts have experienced slower assimilation in terms of their occupational task requirements compared to past cohorts. This occupational task assimilation slowdown can explain a large portion of the slowdown in earnings assimilation. Furthermore, accounting for changing r...

This paper investigates the dynamics of immigrants’ employment assimilation in comparison with the standard static assimilation model. When the effect of past employment experience on current employment possibilities differs between immigrants and natives, then the static assimilation model might produce biased and unrealistic predictions of the relative employment probabilities of immigrants. ...

This manuscript is devoted to the attempts on the design of new nonlinear data assimilation schemes. The variational and sequential assimilation methods are reviewed with emphasis on their performances on dealing with nonlinearity and high dimension of the environmental dynamical systems. The nonlinear data assimilation is based on Bayesian formulation and its approximate solutions. Sequential ...

Many of the talks and posters during this year’s conference will discuss how both ensemble forecasting and atmospheric data assimilation can work synergistically together. We detail provide a brief description of the underlying theoretical basis for this research. The unifying idea is that the chaotic nature of the atmosphere can actually be put to use to improve data assimilation. Ensemble for...

We describe a sequential assimilation approach useful for assimilating tracer measurements into a threedimensional chemical transport model (CTM) of the stratosphere. The numerical code, developed largely according to Khattatov et al. (2000), uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonabl...

Modelling of terrestrial systems is continuously moving towards more integrated modelling approaches, where different terrestrial compartment models are combined in order to realise a more sophisticated physical description of water, energy and carbon fluxes across compartment boundaries and to provide a more integrated view on terrestrial processes. While such models can effectively reduce cer...

Data assimilation with a Numerical Weather Prediction (NWP) model using an observation system in regional area is becoming more prevalent for local weather forecasting activities to reduce the risk of disasters. In this study, we evaluated predictive capabilities multi-platform based on WRFDA (Weather Research and Forecasting data assimilation) 9 km grid spacing over Kong-Chi basin (KCB), where...

Fast and accurate numerical models are critical for the tracking, prediction, and control of fluid flows. Traditional grid-based modelling techniques, though highly accurate, are often too slow for these purposes. So-called reduced-order models—which track abstract flow structures, rather than the details of fluid velocities at every point—are much faster, but the inherent coarseness of their m...