Chris Snyder
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A Hybrid Four‐Dimensional Variational Data Assimilation System for the Model for Prediction Across Scales (MPAS‐Atmosphere): Leveraging the Joint Effort for Data Assimilation Integration (JEDI) Open
A global Four‐Dimensional Ensemble Variational (4DEnVar) data assimilation system for the Atmospheric component of the Model for Prediction Across Scales (MPAS‐A) is presented that uses the Joint Effort for Data assimilation Integration (J…
All-sky AMSU-A radiance data assimilation using the gain-form of Local Ensemble Transform Kalman filter within MPAS-JEDI-2.1.0: implementation, tuning, and evaluation Open
The Gain-form of Local Ensemble Transform Kalman Filter (LGETKF) has been implemented in the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales – Atmosphere (MPAS-A) (i.e., MPAS-JEDI). LGETKF …
All-sky AMSU-A radiance data assimilation using the gain-form of Local Ensemble Transform Kalman filter within MPAS-JEDI-2.1.0: implementation, tuning, and evaluation Open
The Gain-form of Local Ensemble Transform Kalman Filter (LGETKF) has been implemented in the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales – Atmosphere (MPAS-A) (i.e., MPAS-JEDI). LGETKF …
Sampling error in the ensemble Kalman filter for small ensembles and high-dimensional states Open
Sampling error is a fundamental limitation of assimilation schemes, such as the EnKF, that employ the sample covariance from an ensemble of forecasts. Despite the fact that the EnKF is typically applied in situations where the ensemble siz…
Conformal Prediction and Large Language Models for Medical Coding Open
The assignment of current procedure terminology (CPT) codes to medical events is a highly cumbersome, logistic challenge for many healthcare organizations, as well as a significant contributor to medical expenses. Improvement in the alloca…
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta) Open
This paper describes the three-dimensional variational (3D-Var) data assimilation (DA) system for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS). Its core element is …
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations Open
An ensemble of 3D ensemble-variational (En-3DEnVar) data assimilations is demonstrated with the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales – Atmosphere (MPAS-A) (i.e., JEDI-MPAS). Basi…
Comment on gmd-2023-131 Open
Abstract. This paper describes the three-dimensional variational (3DVar) data assimilation (DA) system for the Model for Prediction Across Scales-Atmosphere with the Joint Effort for data Assimilation Integration (JEDI-MPAS). Its core elem…
Comment on gmd-2023-131 Open
Abstract. This paper describes the three-dimensional variational (3DVar) data assimilation (DA) system for the Model for Prediction Across Scales-Atmosphere with the Joint Effort for data Assimilation Integration (JEDI-MPAS). Its core elem…
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales–Atmosphere with the Joint Effort for data Assimilation Integration (JEDI-MPAS 2.0.0-beta) Open
This paper describes the three-dimensional variational (3DVar) data assimilation (DA) system for the Model for Prediction Across Scales-Atmosphere with the Joint Effort for data Assimilation Integration (JEDI-MPAS). Its core element is a m…
Comment on gmd-2023-54 Open
Abstract. An ensemble of three-dimensional ensemble-variational (En-3DEnVar) data assimilations is demonstrated with the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales – Atmosphere (MPAS-A…
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations Open
An ensemble of three-dimensional ensemble-variational (En-3DEnVar) data assimilations is demonstrated with the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales – Atmosphere (MPAS-A) (i.e., J…
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation Open
On 24 September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales – Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JEDI) was public…
Calculating the Costs and Benefits of Advance Preparations for Future Pandemics Open
While Covid-19 vaccines were developed and deployed with unprecedented speed, their widespread introduction could have been accelerated-saving millions of lives and trillions of dollars-had more vaccine capacity been available prior to the…
Comment on gmd-2022-133 Open
Abstract. On 24 September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales â Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JE…
Comment on gmd-2022-133 Open
Abstract. On 24 September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales â Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JE…
Data Assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation Open
On 24th September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales – Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JEDI), was pub…
Expanding Capacity for Vaccines Against Covid-19 and Future Pandemics: A Review of Economic Issues Open
We review economic arguments for using public policy to accelerate vaccine supply during a pandemic.Rapidly vaccinating a large share of the global population helps avoid economic, mortality, and social losses, which in the case of Covid-1…
An Optimal Linear Transformation for Data Assimilation Open
Linear transformations are widely used in data assimilation for covariance modeling, for reducing dimensionality (such as averaging dense observations to form “superobs”), and for managing sampling error in ensemble data assimilation. Here…
Subseasonal Forecast Skill Improvement From Strongly Coupled Data Assimilation With a Linear Inverse Model Open
Strongly coupled data assimilation (SCDA), such as using atmospheric observations to update ocean analyses, is critical for properly initializing Earth System models to predict subseasonal to decadal timescales. We show that a Kalman filte…
Evaluating the response of medical emergency teams to operating room code events in a children’s hospital Open
Introduction: Medical emergency response teams (MET), also known as code teams, consist of health care providers who respond to life-threatening clinical changes in hospitalized patients.The study objective was to determine whether the uti…
Eigenvector-spatial localisation Open
We present a new multiscale covariance localisation method for ensemble data assimilation that is based on the estimation of eigenvectors and subsequent projections, together with traditional spatial localisation applied with a range of lo…
Optimal Vaccine Subsidies for Endemic and Epidemic Diseases Open
Vaccines exert a positive externality, reducing spread of disease from the consumer to others, providing a rationale for subsidies.We study how optimal subsidies vary with disease characteristics by integrating a standard epidemiological m…
Vertical Resolution Requirements in Atmospheric Simulation Open
The role of vertical mesh spacing in the convergence of full-physics global atmospheric model solutions is examined for synoptic, mesoscale, and convective-scale horizontal resolutions. Using the MPAS-Atmosphere model, convergence is evalu…