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View article: Effects of assimilating phytoplankton carbon in marine ecosystem modelling
Effects of assimilating phytoplankton carbon in marine ecosystem modelling Open
View article: Effects of assimilating phytoplankton carbon in marine ecosystem modelling
Effects of assimilating phytoplankton carbon in marine ecosystem modelling Open
View article: A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.2
A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.2 Open
Data assimilation (DA) is an essential component of numerical weather and climate prediction. Efficient implementation of DA algorithms benefits both research and operational prediction. Currently, a variety of DA software programs are ava…
View article: Spatially varying biogeochemical parameter estimation in a global ocean model
Spatially varying biogeochemical parameter estimation in a global ocean model Open
View article: Assimilation of carbon data into NEMO-MEDUSA
Assimilation of carbon data into NEMO-MEDUSA Open
View article: Ocean carbon sink assessment via temperature and salinity data assimilation into a global ocean biogeochemistry model
Ocean carbon sink assessment via temperature and salinity data assimilation into a global ocean biogeochemistry model Open
Global ocean biogeochemistry models are frequently used to derive a comprehensive estimate of the global ocean carbon uptake. These models are designed to represent the most important processes of the ocean carbon cycle, but the idealized …
View article: NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM <sub>2.5</sub> chemical components
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM <sub>2.5</sub> chemical components Open
Identifying PM2.5 chemical components is crucial for formulating emission strategies, estimating radiative forcing, and assessing human health effects. However, accurately describing spatiotemporal variations in PM2.5 chemical components r…
View article: Control of simulated ocean ecosystem indicators by biogeochemical observations
Control of simulated ocean ecosystem indicators by biogeochemical observations Open
View article: Assimilation of ground-based GNSS data using a local ensemble Kalman filter
Assimilation of ground-based GNSS data using a local ensemble Kalman filter Open
View article: Lessons From Transient Simulations of the Last Deglaciation With CLIMBER‐X: GLAC1D Versus PaleoMist
Lessons From Transient Simulations of the Last Deglaciation With CLIMBER‐X: GLAC1D Versus PaleoMist Open
The last deglaciation experienced the retreat of massive ice sheets and a transition from the cold Last Glacial Maximum to the warmer Holocene. Key simulation challenges for this period include the timing and extent of ice sheet decay and …
View article: EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters Open
Data assimilation (DA) in marine and freshwater systems combines numerical models and observations to deliver the best possible characterization of a waterbody's physical and biogeochemical state. DA underpins the widely used 3D ocean stat…
View article: Ocean carbon sink assessment via temperature and salinity data assimilation into a global ocean biogeochemistry model
Ocean carbon sink assessment via temperature and salinity data assimilation into a global ocean biogeochemistry model Open
Global ocean biogeochemistry models are frequently used to derive a comprehensive estimate of the global ocean carbon uptake. These models are designed to represent the most important processes of the ocean carbon cycle, but the idealized …
View article: A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.0
A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.0 Open
Data assimilation (DA) is an essential component of numerical weather and climate prediction. Efficient implementation of DA benefits both operational prediction and research. Currently, a variety of DA software programs are available. One…
View article: WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework Open
Data assimilation is a common technique employed to estimate the state and its associated uncertainties in numerical models. Ensemble-based methods are a prevalent choice, although they can be computationally expensive due to the required …
View article: NAQPMS-PDAF v2.0: A Novel Hybrid Nonlinear Data Assimilation System for Improved Simulation of PM <sub>2.5</sub> Chemical Components
NAQPMS-PDAF v2.0: A Novel Hybrid Nonlinear Data Assimilation System for Improved Simulation of PM <sub>2.5</sub> Chemical Components Open
PM2.5, a complex mixture with diverse chemical components, exerts significant impacts on the environment, human health, and climate change. However, precisely describing spatiotemporal variations of PM2.5 chemical components remains a diff…
View article: Supplementary material to "NAQPMS-PDAF v2.0: A Novel Hybrid Nonlinear Data Assimilation System for Improved Simulation of PM <sub>2.5</sub> Chemical Components"
Supplementary material to "NAQPMS-PDAF v2.0: A Novel Hybrid Nonlinear Data Assimilation System for Improved Simulation of PM <sub>2.5</sub> Chemical Components" Open
View article: HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model
HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model Open
This article describes a modular ensemble-based data assimilation (DA) system which is developed for an integrated surface–subsurface hydrological model. The software environment for DA is the Parallel Data Assimilation Framework (PDAF), w…
View article: Paleoclimate data assimilation with CLIMBER-X: An ensemble Kalman filter for the last deglaciation
Paleoclimate data assimilation with CLIMBER-X: An ensemble Kalman filter for the last deglaciation Open
Using the climate model CLIMBER-X, we present an efficient method for assimilating the temporal evolution of surface temperatures for the last deglaciation covering the period 22000 to 6500 years before the present. The data assimilation m…
View article: Improving daily-to-seasonal sea ice forecasts of the AWI coupled prediction system with sea-ice and ocean data assimilation and atmospheric large-scale wind nudging.
Improving daily-to-seasonal sea ice forecasts of the AWI coupled prediction system with sea-ice and ocean data assimilation and atmospheric large-scale wind nudging. Open
Predictive skills of coupled sea-ice/ocean and atmosphere models are limited by the chaotic nature of the atmosphere. Assimilation of observational information on ocean hydrography and sea ice allows to obtain a coupled-system state that p…
View article: Comment on gmd-2023-229
Comment on gmd-2023-229 Open
Abstract. This article describes a modular ensemble-based data assimilation (DA) system, which is developed for an integrated surface-subsurface hydrological model. The software environment for DA is the Parallel Data Assi…
View article: Comment on gmd-2023-238
Comment on gmd-2023-238 Open
Abstract. Data assimilation (DA) in marine and freshwater systems combines numerical models and observations to deliver the best possible characterisation of a water body’s physical and biogeochemical state. This underpins…
View article: The Impact of Profiles Data Assimilation on an Ideal Tropical Cyclone Case
The Impact of Profiles Data Assimilation on an Ideal Tropical Cyclone Case Open
Profile measurements play a crucial role in operational weather forecasting across diverse scales and latitudes. However, assimilating tropospheric wind and temperature profiles remains a challenging endeavor. This study assesses the influ…
View article: EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters
EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters Open
Data assimilation (DA) in marine and freshwater systems combines numerical models and observations to deliver the best possible characterisation of a water body’s physical and biogeochemical state. This underpins the widely used 3D ocean s…
View article: Comment on egusphere-2023-2311
Comment on egusphere-2023-2311 Open
Abstract. Data assimilation is a common technique employed to estimate the state and its associated uncertainties in numerical models. Ensemble-based methods are a prevalent choice, although they can be computationally exp…
View article: HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model
HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model Open
This article describes a modular ensemble-based data assimilation (DA) system, which is developed for an integrated surface-subsurface hydrological model. The software environment for DA is the Parallel Data Assimilation Framework (PDAF), …
View article: The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation
The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation Open
Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long‐term variability of Antarctic sea ice, and the limited attention given to model‐dependent parameters in c…
View article: WRF-PDAF v1.0: Implementation and Application of an Online Localized Ensemble Data Assimilation Framework
WRF-PDAF v1.0: Implementation and Application of an Online Localized Ensemble Data Assimilation Framework Open
Data assimilation is a common technique employed to estimate the state and its associated uncertainties in numerical models. Ensemble-based methods are a prevalent choice, although they can be computationally expensive due to the required …
View article: Global sensitivity analysis of a one-dimensional ocean biogeochemical model
Global sensitivity analysis of a one-dimensional ocean biogeochemical model Open
Ocean biogeochemical (BGC) models are a powerful tool for investigating ocean biogeochemistry and the global carbon cycle. The potential benefits emanating from BGC simulations and predictions are broad, with significant societal impacts f…
View article: The Antarctic sea ice reconstruction (CMST-South) based on the optimized Data Assimilation System for the Southern Ocean
The Antarctic sea ice reconstruction (CMST-South) based on the optimized Data Assimilation System for the Southern Ocean Open
The wealth of historical sea ice concentration (SIC) observations, coupled with their extensive spatial coverage, renders them indispensable for the reconstruction of long-term Antarctic sea ice variability. However, recent studies have po…
View article: The impacts of optimizing model-dependent parameters on the Antarctic sea ice data assimilation
The impacts of optimizing model-dependent parameters on the Antarctic sea ice data assimilation Open
Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long-term variability of Antarctic sea ice, and the limited attention given to model-dependent parameters in c…