Mark Buehner
YOU?
Author Swipe
View article: The Effect of Ensemble Size on the Mean Squared Error and Spread–Error Relationship
The Effect of Ensemble Size on the Mean Squared Error and Spread–Error Relationship Open
Most ensemble verification diagnostics are sensitive to ensemble size, complicating the evaluation of a system’s underlying quality and the comparison of different ensemble systems. This study examines how the mean squared error (MSE) of t…
View article: Leveraging Data-Driven Weather Forecasting for Improving Numerical Weather Prediction Skill Through Large-Scale Spectral Nudging
Leveraging Data-Driven Weather Forecasting for Improving Numerical Weather Prediction Skill Through Large-Scale Spectral Nudging Open
Operational weather forecasting has traditionally relied on physics-based numerical weather prediction (NWP) models, but the rise of AI-based weather emulators is reshaping this paradigm. However, most data-driven models for medium-range f…
View article: Idealized study of representing spatial and temporal variations in the error contribution of surface emissivity for assimilating surface‐sensitive microwave radiance observations over land
Idealized study of representing spatial and temporal variations in the error contribution of surface emissivity for assimilating surface‐sensitive microwave radiance observations over land Open
The assimilation of surface‐sensitive microwave radiance observations over land can improve numerical weather prediction accuracy at Environment and Climate Change Canada. However, the benefits of these observations are limited by large er…
View article: The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1) Open
The Modular and Integrated Data Assimilation System (MIDAS) software (version 3.9.1) is described in terms of its range of functionality, modular software design, parallelization strategy, and current uses within real-time operational and …
View article: Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging
Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging Open
This tar file contains the additional code for spectral nudging with version 5.3.0-a4 of the Global Environmental Multiscale (GEM) model. It also contains the model configuration files representing the optimal nudging configuration. In add…
View article: A new global daily sea‐surface temperature analysis system at Environment and Climate Change Canada
A new global daily sea‐surface temperature analysis system at Environment and Climate Change Canada Open
A new global daily sea‐surface temperature (SST) analysis system has been developed at Environment and Climate Change Canada (ECCC). All components of the new SST analysis system are implemented within the Modular and Integrated Data Assim…
View article: Comment on gmd-2024-55
Comment on gmd-2024-55 Open
Abstract. The Modular and Integrated Data Assimilation System (MIDAS) software (version 3.9.1) is described in terms of its range of functionality, modular software design, parallelization strategy, and current uses within real-time operat…
View article: The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1) Open
The Modular and Integrated Data Assimilation System (MIDAS) software (version 3.9.1) is described in terms of its range of functionality, modular software design, parallelization strategy, and current uses within real-time operational and …
View article: Assimilation of RCM data in the Canadian ice concentration analysis system
Assimilation of RCM data in the Canadian ice concentration analysis system Open
The sea and lake ice concentration pan-Arctic analysis system at Environment and Climate Change Canada (ECCC) initializes both the short-range Arctic sea ice forecasting models and numerical weather prediction tools. In this study, our pre…
View article: Multi-year and first-year ice from RCM for assimilation in ECCC ice type analysis system
Multi-year and first-year ice from RCM for assimilation in ECCC ice type analysis system Open
Arctic sea ice type information is essential for various operational and scientific applications including the support of marine users and guiding ice thickness retrieval algorithms operating with SMOS and CryoSat-2 data for improved sea i…
View article: Randomized Subensembles: An Approach to Reduce the Risk of Divergence in an Ensemble Kalman Filter Using Cross Validation
Randomized Subensembles: An Approach to Reduce the Risk of Divergence in an Ensemble Kalman Filter Using Cross Validation Open
In an ensemble Kalman filter, when the analysis update of an ensemble member is computed using error statistics estimated from an ensemble that includes the background of the member being updated, the spread of the resulting ensemble syste…
View article: Implementation of Scale-Dependent Background-Error Covariance Localization in the Canadian Global Deterministic Prediction System
Implementation of Scale-Dependent Background-Error Covariance Localization in the Canadian Global Deterministic Prediction System Open
The approach of applying different amounts of horizontal localization to different ranges of background-error covariance horizontal scales as proposed by Buehner and Shlyaeva was recently implemented in the four-dimensional ensemble–variat…
View article: Understanding sources of Northern Hemisphere uncertainty and forecast error in a medium‐range coupled ensemble sea‐ice prediction system
Understanding sources of Northern Hemisphere uncertainty and forecast error in a medium‐range coupled ensemble sea‐ice prediction system Open
The Global Ensemble Prediction System (GEPS) of Environment and Climate Change Canada was recently upgraded to a coupled atmosphere, ocean, and sea‐ice version from an uncoupled atmosphere‐only system. This has been operational since July …
View article: Toward All-Sky Assimilation of Microwave Temperature Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System
Toward All-Sky Assimilation of Microwave Temperature Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System Open
The all-sky assimilation of radiances from microwave instruments is developed in the 4D-EnVar analysis system at Environment and Climate Change Canada (ECCC). Assimilation of cloud-affected radiances from Advanced Microwave Sounding Unit-A…
View article: Implementation of Slant-Path Radiative Transfer in Environment Canada’s Global Deterministic Weather Prediction System
Implementation of Slant-Path Radiative Transfer in Environment Canada’s Global Deterministic Weather Prediction System Open
The standard approach for assimilating satellite radiance observations is to interpolate all vertical levels of the background state and analysis increment to the same horizontal location for input to the radiative transfer model. This can…
View article: Hybrid Background Error Covariances for a Limited-Area Deterministic Weather Prediction System
Hybrid Background Error Covariances for a Limited-Area Deterministic Weather Prediction System Open
This study introduces an experimental regional assimilation configuration for a 4D ensemble–variational (4D-EnVar) deterministic weather prediction system. A total of 16 assimilation experiments covering July 2014 are presented to assess b…
View article: Local Ensemble Transform Kalman Filter with Cross Validation
Local Ensemble Transform Kalman Filter with Cross Validation Open
Many ensemble data assimilation (DA) approaches suffer from the so-called inbreeding problem. As a consequence, there is an excessive reduction in ensemble spread by the DA procedure, causing the analysis ensemble spread to systematically …
View article: Weakly coupled atmosphere–ocean data assimilation in the Canadian global prediction system (v1)
Weakly coupled atmosphere–ocean data assimilation in the Canadian global prediction system (v1) Open
A fully coupled atmosphere–ocean–ice model has been used to produce global weather forecasts at Environment and Climate Change Canada (ECCC) since November 2017. Currently, the system relies on four uncoupled data assimilation (DA) compone…
View article: Non-Gaussian Deterministic Assimilation of Radar-Derived Precipitation Accumulations
Non-Gaussian Deterministic Assimilation of Radar-Derived Precipitation Accumulations Open
Data assimilation (DA) approaches currently used for operational numerical weather prediction (NWP) generally assume that errors in the background state are Gaussian. At the same time, approaches that make no assumptions regarding the back…
View article: A practical assimilation approach to extract smaller‐scale information from observations with spatially correlated errors: An idealized study
A practical assimilation approach to extract smaller‐scale information from observations with spatially correlated errors: An idealized study Open
It is still common to neglect the spatial error correlations of assimilated observations in numerical weather prediction systems because no practical approach is available to account for them when the number of observations with correlated…
View article: Weakly coupled atmospheric-ocean data assimilation in the Canadian global prediction system (v1)
Weakly coupled atmospheric-ocean data assimilation in the Canadian global prediction system (v1) Open
A fully coupled atmosphere-ocean-ice model has been used to produce global weather forecasts at Environment and Climate Change Canada (ECCC) since November 2017. Currently, the system relies on four uncoupled data assimilation (DA) compone…
View article: Improved Retrieval of Ice and Open Water From Sequential RADARSAT-2 Images
Improved Retrieval of Ice and Open Water From Sequential RADARSAT-2 Images Open
In this paper, we present a new technique for automated detection of ice and open water from sequential RADARSAT-2 ScanSAR dual-polarization HH-HV images. The technique is based on combining a previously developed approach to ice and water…
View article: Using the hybrid gain algorithm to sample data assimilation uncertainty
Using the hybrid gain algorithm to sample data assimilation uncertainty Open
At the Canadian Meteorological Centre (CMC), an ensemble variational (EnVar) data assimilation system is used for the global deterministic prediction system and an ensemble Kalman filter (EnKF) is used for the global ensemble prediction sy…
View article: Progress toward the Application of a Localized Particle Filter for Numerical Weather Prediction
Progress toward the Application of a Localized Particle Filter for Numerical Weather Prediction Open
A series of papers published recently by the first author introduce a nonlinear filter that operates effectively as a data assimilation method for large-scale geophysical applications. The method uses sequential Monte Carlo techniques adop…
View article: Impacts on sea ice analyses from the assumption of uncorrelated ice thickness observation errors: Experiments using a 1D toy model
Impacts on sea ice analyses from the assumption of uncorrelated ice thickness observation errors: Experiments using a 1D toy model Open
Sea ice prediction centres are moving toward the assimilation of ice thickness observations under the simplifying assumption that the observation errors are uncorrelated. The assumption of uncorrelated observation errors is attractive beca…