Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

A Calibration and Data Assimilation Approach to Use GRACE, GRACE-FO and Swarm Accelerometer Measurements for Forecasting Global and Multi-level Thermospheric Neutral Density Fields

View through CrossRef
<p>An accurate simulation global thermospheric neutral density (TND) on various altitudes is important for geodetic and space weather applications. In addition, this is essential for designing the low-Earth-orbit (LEO) missions, predict their missions’ lifetime and performing a reliable attitude control. Although empirical and physics-based models typically simulate TND variations, the quality of these models is limited due to various structural simplifications and the uncertainty of inputs. Here, we present an ensemble Kalman filter (EnKF)-based calibration and data assimilation (C/DA) technique that updates the model's states and simultaneously calibrates its key parameters. The proposed approach provides the opportunity to improve the now-cast and forecast skills of the NRLMISISE-00 and NRMSIS-2.0 models through re-calibrating the model’s key parameters including those controlling the influence of solar radiation and geomagnetic activity as well as those related to the calculation of exospheric temperature.</p><p>In this research, TND estimates from on-board accelerometer measurements of GRACE, GRACE-FO and Swarm are ingested as observations into the NRLMSISE-00 and NRLMSIS-2.0 models based on the C/DA. The newly calibrated model, called here ‘C/DA-NRLMSISE’, is then used to simulate global maps of TND as well as individual neutral mass densities covering the altitudes of 300-600 km. Various investigations are performed to test the temporal and vertical consistency of the TND outputs from C/DA-NRLMSISE.</p>
Title: A Calibration and Data Assimilation Approach to Use GRACE, GRACE-FO and Swarm Accelerometer Measurements for Forecasting Global and Multi-level Thermospheric Neutral Density Fields
Description:
<p>An accurate simulation global thermospheric neutral density (TND) on various altitudes is important for geodetic and space weather applications.
In addition, this is essential for designing the low-Earth-orbit (LEO) missions, predict their missions’ lifetime and performing a reliable attitude control.
Although empirical and physics-based models typically simulate TND variations, the quality of these models is limited due to various structural simplifications and the uncertainty of inputs.
Here, we present an ensemble Kalman filter (EnKF)-based calibration and data assimilation (C/DA) technique that updates the model's states and simultaneously calibrates its key parameters.
The proposed approach provides the opportunity to improve the now-cast and forecast skills of the NRLMISISE-00 and NRMSIS-2.
0 models through re-calibrating the model’s key parameters including those controlling the influence of solar radiation and geomagnetic activity as well as those related to the calculation of exospheric temperature.
</p><p>In this research, TND estimates from on-board accelerometer measurements of GRACE, GRACE-FO and Swarm are ingested as observations into the NRLMSISE-00 and NRLMSIS-2.
0 models based on the C/DA.
The newly calibrated model, called here ‘C/DA-NRLMSISE’, is then used to simulate global maps of TND as well as individual neutral mass densities covering the altitudes of 300-600 km.
Various investigations are performed to test the temporal and vertical consistency of the TND outputs from C/DA-NRLMSISE.
</p>.

Related Results

(Invited) Strategies for Calibration Cost Reduction in Heterogeneous Chemical Sensor Arrays
(Invited) Strategies for Calibration Cost Reduction in Heterogeneous Chemical Sensor Arrays
Introduction Heterogeneous gas sensor arrays coupled with machine learning algorithms have been proposed for a wide range of applications. However, i...
Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
In recent years, the development of artificial intelligence has led to rapid advances in data-driven weather forecasting models, some of which rival or even surpass traditional met...
The Burden of Road Traffic Injuries: A Global Perspective
The Burden of Road Traffic Injuries: A Global Perspective
Introduction     Road Traffic Injury (RTI) pose a significant health challenge. It represents the eighth leading cause of death globally, prompting the UN to designate 2011-2020 as...
Global estimation of ionospheric drivers during extreme storms
Global estimation of ionospheric drivers during extreme storms
<p>During geomagnetic storms, the space environment can be drastically altered as the plasma in the upper atmosphere, or ionosphere, moves globally. This plasma redis...
Collective Cognition on Global Density in Dynamic Swarm
Collective Cognition on Global Density in Dynamic Swarm
Swarm density plays a key role in the performance of a robot swarm, which can be averagely measured by swarm size and the area of a workspace. In some scenarios, the swarm workspac...
Swarm A and C Accelerometer - data analysis and scientific outcome
Swarm A and C Accelerometer - data analysis and scientific outcome
The ESA Swarm mission was launched in November 2013, and it consists of a constellation of three identical satellites. The main mission objective is to model and analyze the geomag...

Back to Top