Browsing by Subject "data assimilation"
Now showing items 1-15 of 15
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A Combined Neural Network‐ and Physics‐Based Approach for Modeling Plasmasphere Dynamics
(Journal of Geophysical Research: Space Physics, 2021-03-16)In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network‐based models capture the large‐scale dynamics of ... -
Arctic ocean–sea ice reanalysis for the period 2007–2016 using the adjoint method
(Quarterly Journal of the Royal Meteorological Society, 2021-03-04)We present an Arctic ocean–sea ice reanalysis covering the period 2007–2016 based on the adjoint approach of the Estimating the Circulation and Climate of the Ocean (ECCO) consortium. The spatiotemporal variation of Arctic ... -
Are Ocean Reanalyses Useful for Earth Rotation Research?
(Earth and Space Science, 2023-02-28)Oceanic circulation and mass‐field variability play important roles in exciting Earth's wobbles and length‐of‐day changes (ΔΛ), on time scales from days to several years. Modern descriptions of these effects employ oceanic ... -
Assimilating synthetic land surface temperature in a coupled land–atmosphere model
(Quarterly Journal of the Royal Meteorological Society, 2020)A realistic simulation of the atmospheric boundary layer (ABL) depends on an accurate representation of the land–atmosphere coupling. Land surface temperature (LST) plays an important role in this context and the assimilation ... -
Assimilating visible satellite images for convective-scale numerical weather prediction: A case-study
(Quarterly Journal of the Royal Meteorological Society, 2020)Satellite images in the visible spectral range contain high-resolution cloud information, but have not been assimilated directly before. This paper presents a case-study on the assimilation of visible Meteosat SEVIRI images ... -
Assimilation of High-Resolution Soil Moisture Data Into an Integrated Terrestrial Model for a Small-Scale Head-Water Catchment
(Water Resources Research, 2019)Land surface-subsurface modeling combined with data assimilation was applied on the Rollesbroich hillslope (Germany). Dense information from a soil moisture sensor network was assimilated with the ensemble Kalman filter ... -
Deep Emulators for Differentiation, Forecasting, and Parametrization in Earth Science Simulators
(Journal of Advances in Modeling Earth Systems, 2021-06-28)To understand and predict large, complex, and chaotic systems, Earth scientists build simulators from physical laws. Simulators generalize better to new scenarios, require fewer tunable parameters, and are more interpretable ... -
Identifying Radiation Belt Electron Source and Loss Processes by Assimilating Spacecraft Data in a Three-Dimensional Diffusion Model
(Journal of Geophysical Research: Space Physics, 2020)Data assimilation aims to blend incomplete and inaccurate data with physics-based dynamical models. In the Earth's radiation belts, it is used to reconstruct electron phase space density, and it has become an increasingly ... -
Impacts of the Assimilation of Satellite Sea Surface Temperature Data on Volume and Heat Budget Estimates for the North Sea
(Journal of Geophysical Research: Oceans, 2021-05-03)Mechanisms controlling the heat budget of the North Sea are investigated based on a combination of satellite sea surface temperature measurements and numerical model simulations. Lateral heat fluxes across the shelf edge ... -
Improving the ocean and atmosphere in a coupled ocean–atmosphere model by assimilating satellite sea-surface temperature and subsurface profile data
(Quarterly Journal of the Royal Meteorological Society, 2020)An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to investigate the influence of assimilating different types of ocean observations on the ocean and atmosphere simulation. The ... -
Machine Learning‐Based Prediction of Spatiotemporal Uncertainties in Global Wind Velocity Reanalyses
(Journal of Advances in Modeling Earth Systems, 2020-05-13)The characterization of uncertainties in geophysical quantities is an important task with widespread applications for time series prediction, numerical modeling, and data assimilation. In this context, machine learning is ... -
Quantifying the Effects of EMIC Wave Scattering and Magnetopause Shadowing in the Outer Electron Radiation Belt by Means of Data Assimilation
(Journal of Geophysical Research: Space Physics, 2020)In this study we investigate two distinct loss mechanisms responsible for the rapid dropouts of radiation belt electrons by assimilating data from Van Allen Probes A and B and Geostationary Operational Environmental ... -
Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis
(Reviews of Geophysics, 2021-08-18)A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modeled processes and assimilation algorithms ... -
Targeted covariance inflation for 3D‐volume radar reflectivity assimilation with the LETKF
(Quarterly Journal of the Royal Meteorological Society, 2021-09-30)The local ensemble transform Kalman filter (LETKF) suggested by Hunt et al., 2007 is a very popular method for ensemble data assimilation. It is the operational method for convective‐scale data assimilation at Deutscher ... -
The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data
(Space Weather, 2021-05-20)This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)‐derived electron density (Ne) into a physics‐based model ...