This paper describes a novel method to incorporate significantly time-lagged data into a sequential variational data assimilation framework. The proposed method can assimilate data that appear many assimilation window lengths in the future, providing a mechanism to gradually dynamically adjust the model towards those data. The method avoids the need for an adjoint model, significantly reducing ...

Data assimilation is the process of integrating observational data and model predictions to obtain an optimal representation of the state of the atmosphere. As more chemical observations in the troposphere are becoming available, chemical data assimilation is expected to play an essential role in air quality forecasting, similar to the role it has in numerical weather prediction. Considerable p...

In order to improve the soil temperature profile predictions in land-surface models, an assimilation scheme using the extended Kalman filter is developed. This formulation is based on the discretized diffusion equation of heat transfer through the soil column. The scheme is designed to incorporate the knowledge of the uncertainties in both the model and the measurement. Model uncertainty is est...

Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. Not all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and fo...

A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO2 concentration in state ...

CORIE is a pilot environmental observation and forecasting system (EOFS) for the Columbia River. The goal of CORIE is to characterize and predict complex circulation and mixing processes in a system encompassing the lower river, the estuary, and the near-ocean using a multi-scale data assimilation model. The challenge for scientists is to maintain the accuracy of their modeling system while min...

Data assimilation (DA) methods have been widely used to improve model state estimation by merging model outputs with observations. Traditionally, studies have focused on updating model state variables but recent studies have augmented model parameters alongside model state variables to improve the estimation procedure. The updated model ensemble members represent a compromised estimation betwee...

This study presents the theoretical framework for variational data assimilation of acoustic pressure observations into an acoustic propagation model, namely, the range dependent acoustic model (RAM). RAM uses the split-step Padé algorithm to solve the parabolic equation. The assimilation consists of minimizing a weighted least squares cost function that includes discrepancies between the model ...

This study examined how the phonetic details of the phonological systems for two different nativelanguage listener groups interact with their perception of the phonetic details of three nonnative consonant contrasts. Current theoretical models of cross-language and second language speech perception are evaluated by relating native Italian and native Danish listeners’ perceptual assimilation of ...

Native speech perception is generally assumed to be highly efficient and accurate. Very little research has, however, directly examined the limitations of native perception, especially for contrasts that are only minimally differentiated acoustically and articulatorily. Here, we demonstrate that native speech perception may indeed be more difficult than is often assumed, where phonemes are high...