scholarly journals The impact of severe storms on forecasting the Ionosphere-Thermosphere system through the assimilation of SWARM-derived neutral mass density into physics-based models

2021 ◽  
Author(s):  
Isabel Fernandez-Gomez ◽  
Andreas Goss ◽  
Michael Schmidt ◽  
Mona Kosary ◽  
Timothy Kodikara ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Electron Density ◽  
Mass Density ◽  
Data Driven ◽  
Ionospheric Electron Density ◽  
Density Estimates ◽  
True State ◽  
The Impact ◽  
Coupling Mechanisms ◽  
Swarm Mission

<p>The response of the Ionosphere - Thermosphere (IT) system to severe storm conditions is of great importance to fully understand its coupling mechanisms. The challenge to represent the governing processes of the upper atmosphere depends, to a large extent, on an accurate representation of the true state of the IT system, that we obtain by assimilating relevant measurements into physics-based models. Thermospheric Mass Density (TMD) is the summation of total neutral mass within the atmosphere that is derived from accelerometer measurements of satellite missions such as CHAMP, GOCE, GRACE(-FO) and Swarm. TMD estimates can be assimilated into physics-based models to modify the state of the processes within the IT system. Previous studies have shown that this modification can potentially improve the simulations and predictions of the ionospheric electron density. These differences could also be interpreted as an indicator of the ionosphere-thermosphere interaction. The research presented here, aims to quantify the impact of data satellite based TMD assimilation on numerical model results.</p><p>Subject of this study is the Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe) physics-based model in combination with the recently developed Thermosphere-Ionosphere Data Assimilation (TIDA) scheme. TMD estimates from the ESA’s Swarm mission are assimilated in CTIPe-TIDA during the 16 to the 20 of March 2015. This period was characterized by a strong geomagnetic storm that triggered significant changes in the IT system, the so-called St. Patrick day storm 2015. To assess the changes in the IT system during storm conditions due to data assimilation, the model results from assimilating SWARM mass density normalized to the altitude of 400 km are compared to independent thermospheric estimates like GRACE-TMDS. In order to evaluate the impact of the data assimilation on the ionosphere, the corresponding output of electron density is compared to high-quality electron density estimates derived from data-driven model of the DGFI-TUM.</p>

Global ionospheric electron density estimation based on multisource TEC data assimilation

GPS Solutions ◽  
2017 ◽  
Vol 21 (3) ◽  
pp. 1125-1137 ◽  
Author(s):  
Chengli She ◽  
Weixing Wan ◽  
Xinan Yue ◽  
Bo Xiong ◽  
You Yu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Electron Density ◽  
Density Estimation ◽  
Ionospheric Electron Density

scholarly journals The impact of large scale ionospheric structure on radio occultation retrievals

2011 ◽  
Vol 4 (12) ◽  
pp. 2837-2850 ◽  
Author(s):  
A. J. Mannucci ◽  
C. O. Ao ◽  
X. Pi ◽  
B. A. Iijima
Keyword(s):  
Electron Density ◽  
Large Scale ◽  
Radio Occultation ◽  
Quiet Time ◽  
Ionospheric Electron Density ◽  
Observation Strategy ◽  
Climatological Model ◽  
Ionospheric Data Assimilation ◽  
Using Data ◽  
The Impact

Abstract. We study the impact of large-scale ionospheric structure on the accuracy of radio occultation (RO) retrievals. We use a climatological model of the ionosphere as well as an ionospheric data assimilation model to compare quiet and geomagnetically disturbed conditions. The presence of ionospheric electron density gradients during disturbed conditions increases the physical separation of the two GPS frequencies as the GPS signal traverses the ionosphere and atmosphere. We analyze this effect in detail using ray-tracing and a full geophysical retrieval system. During quiet conditions, our results are similar to previously published studies. The impact of a major ionospheric storm is analyzed using data from the 30 October 2003 "Halloween" superstorm period. At 40 km altitude, the refractivity bias under disturbed conditions is approximately three times larger than quiet time. These results suggest the need for ionospheric monitoring as part of an RO-based climate observation strategy. We find that even during quiet conditions, the magnitude of retrieval bias depends critically on assumed ionospheric electron density structure, which may explain variations in previously published bias estimates that use a variety of assumptions regarding large scale ionospheric structure. We quantify the impact of spacecraft orbit altitude on the magnitude of bending angle and retrieval error. Satellites in higher altitude orbits (700+ km) tend to have lower residual biases due to the tendency of the residual bending to cancel between the top and bottomside ionosphere. Another factor affecting accuracy is the commonly-used assumption that refractive index is unity at the receiver. We conclude with remarks on the implications of this study for long-term climate monitoring using RO.

scholarly journals Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

2014 ◽  
Vol 7 (3) ◽  
pp. 2631-2661 ◽  
Author(s):  
C. Y. Lin ◽  
T. Matsuo ◽  
J. Y. Liu ◽  
C. H. Lin ◽  
H. F. Tsai ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Electron Density ◽  
Radio Occultation ◽  
Model Error ◽  
Background Model ◽  
Ionospheric Electron Density ◽  
Error Covariance ◽  
Ionospheric Data Assimilation ◽  
Stationary Location ◽  
Assimilation Model

Abstract. Ionospheric data assimilation is a powerful approach to reconstruct the 3-D distribution of the ionospheric electron density from various types of observations. We present a data assimilation model for the ionosphere, based on the Gauss–Markov Kalman filter with the International Reference Ionosphere (IRI) as the background model, to assimilate two different types of total electron content (TEC) observations from ground-based GPS and space-based FORMOSAT-3/COSMIC (F3/C) radio occultation. Covariance models for the background model error and observational error play important roles in data assimilation. The objective of this study is to investigate impacts of stationary (location-independent) and non-stationary (location-dependent) classes of the background model error covariance on the quality of assimilation analyses. Location-dependent correlations are modeled using empirical orthogonal functions computed from an ensemble of the IRI outputs, while location-independent correlations are modeled using a Gaussian function. Observing System Simulation Experiments suggest that assimilation of TEC data facilitated by the location-dependent background model error covariance yields considerably higher quality assimilation analyses. Results from assimilation of real ground-based GPS and F3/C radio occultation observations over the continental United States are presented as TEC and electron density profiles. Validation with the Millstone Hill incoherent scatter radar data and comparison with the Abel inversion results are also presented. Our new ionospheric data assimilation model that employs the location-dependent background model error covariance outperforms the earlier assimilation model with the location-independent background model error covariance, and can reconstruct the 3-D ionospheric electron density distribution satisfactorily from both ground- and space-based GPS observations.

scholarly journals Global 3-D ionospheric electron density reanalysis based on multisource data assimilation

2012 ◽  
Vol 117 (A9) ◽  
pp. n/a-n/a ◽  
Author(s):  
Xinan Yue ◽  
William S. Schreiner ◽  
Ying-Hwa Kuo ◽  
Douglas C. Hunt ◽  
Wenbin Wang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Electron Density ◽  
Ionospheric Electron Density

scholarly journals Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

2015 ◽  
Vol 8 (1) ◽  
pp. 171-182 ◽  
Author(s):  
C. Y. Lin ◽  
T. Matsuo ◽  
J. Y. Liu ◽  
C. H. Lin ◽  
H. F. Tsai ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Electron Density ◽  
Radio Occultation ◽  
Model Error ◽  
Background Model ◽  
Ionospheric Electron Density ◽  
Error Covariance ◽  
Ionospheric Data Assimilation ◽  
Stationary Location ◽  
Assimilation Model

Abstract. Ionospheric data assimilation is a powerful approach to reconstruct the 3-D distribution of the ionospheric electron density from various types of observations. We present a data assimilation model for the ionosphere, based on the Gauss–Markov Kalman filter with the International Reference Ionosphere (IRI) as the background model, to assimilate two different types of slant total electron content (TEC) observations from ground-based GPS and space-based FORMOSAT-3/COSMIC (F3/C) radio occultation. Covariance models for the background model error and observational error play important roles in data assimilation. The objective of this study is to investigate impacts of stationary (location-independent) and non-stationary (location-dependent) classes of the background model error covariance on the quality of assimilation analyses. Location-dependent correlations are modeled using empirical orthogonal functions computed from an ensemble of the IRI outputs, while location-independent correlations are modeled using a Gaussian function. Observing system simulation experiments suggest that assimilation of slant TEC data facilitated by the location-dependent background model error covariance yields considerably higher quality assimilation analyses. Results from assimilation of real ground-based GPS and F3/C radio occultation observations over the continental United States are presented as TEC and electron density profiles. Validation with the Millstone Hill incoherent scatter radar data and comparison with the Abel inversion results are also presented. Our new ionospheric data assimilation model that employs the location-dependent background model error covariance outperforms the earlier assimilation model with the location-independent background model error covariance, and can reconstruct the 3-D ionospheric electron density distribution satisfactorily from both ground- and space-based GPS observations.

scholarly journals The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data

2021 ◽  
Author(s):  
Timothy Kodikara ◽  
Kefei Zhang ◽  
Nicholas M. Pedatella ◽  
Claudia Borries
Keyword(s):  
Solar Activity ◽  
Electron Density ◽  
General Circulation ◽  
Solar Maximum ◽  
Mass Density ◽  
Circulation Model ◽  
Global Scale ◽  
Density State ◽  
The Impact ◽  
Assimilation Scheme

<p>We present a comprehensive comparison of the impact of solar activity on forecasting the ionosphere and thermosphere. Here we investigate the response of physics-based TIE-GCM (thermosphere-ionosphere-electrodynamics general circulation model) in a data assimilation scheme through assimilating radio occultation (RO)-derived electron density (Ne) using an ensemble Kalman filter (KF). Constellation observations of Ne profiles offer opportunities to assess the accuracy of the model forecasted state on a global scale. In this study, we emphasise the importance of understanding how the assimilation results vary with solar activity, which is one of the primary drivers of thermosphere-ionosphere dynamics.</p><p>We validate the assimilation results with independent RO-derived GRACE (Gravity Recovery and Climate Experiment mission) Ne data. The main result is that the forecast Ne agree best with data during the solar minimum compared to solar maximum. The results also show that the assimilation scheme significantly adjusts both the nowcast and forecast states during the two solar activity periods. The results show that TIE-GCM significantly underestimate Ne in low altitudes below 250 km and the assimilation of Ne is not as effective in these lower altitudes compared to higher altitudes. The results demonstrate that assimilation of Ne significantly impacts the neutral mass density estimates via the KF state vector. This impact is larger during solar maximum than solar minimum relative to a control run. The results also demonstrate that the impact of assimilation of Ne on neutral mass density state persists through to forecast state better during solar minimum compared to solar maximum. The results are useful to explain the inherent model bias, to understand the limitations of the data, and to demonstrate the capability of the assimilation technique.</p>

scholarly journals The influence of bone quality on radiological outcome in 50 consecutive acetabular fractures treated with a pre-contoured anatomic suprapectineal plate

2021 ◽  
Author(s):  
Maximilian J. Hartel ◽  
Tareq Naji ◽  
Florian Fensky ◽  
Frank O. Henes ◽  
Darius M. Thiesen ◽  
...  
Keyword(s):  
Total Hip Arthroplasty ◽  
Bone Mass ◽  
Bone Quality ◽  
Hip Arthroplasty ◽  
Mass Density ◽  
Acetabular Fractures ◽  
Bone Mass Density ◽  
Radiological Outcome ◽  
Total Hip ◽  
The Impact

Abstract Purpose To investigate the range of indications of an anatomical-preshaped three-dimensional suprapectineal plate and to assess the impact of the bone mass density on radiologic outcomes in different types of acetabular fractures. Patients and methods A consecutive case series of 50 acetabular fractures (patient age 69 ± 23 years) treated with suprapectineal anatomic plates were analyzed in a retrospective study. The analysis included: Mechanism of injury, fracture pattern, surgical approach, need for additional total hip arthroplasty, intra- or postoperative complications, as well as bone mass density and radiological outcome on postoperative computed tomography. Results Most frequently, anterior column fracture patterns with and without hemitransverse components as well as associated two column fractures were encountered. The anterior intrapelvic approach (AIP) was used in 98% (49/50) of the cases as primary approach with additional utilization of the first window of the ilioinguinal approach in 13/50 cases (26%). Determination of bone density revealed impaired bone quality in 70% (31/44). Postoperative steps and gaps were significantly greater in this subgroup (p < 0.05). Fracture reduction quality for postoperative steps revealed anatomic results in 92% if the bone quality was normal and in 46% if impaired (p < 0.05). In seven cases (14%), the plate was utilized in combination with acute primary arthroplasty. Conclusion A preshaped suprapectineal plate provides good radiological outcomes in a variety of indications in a predominantly geriatric cohort. Impaired bone quality has a significantly higher risk of poor reduction results. In cases with extensive joint destruction, the combination with total hip arthroplasty was a valuable option.

scholarly journals Effect of the Assimilation Frequency of Radar Reflectivity on Rain Storm Prediction by Using WRF-3DVAR

2021 ◽  
Vol 13 (11) ◽  
pp. 2103
Author(s):  
Yuchen Liu ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Wei Wang
Keyword(s):  
Data Assimilation ◽  
Northern China ◽  
Horizontal Resolution ◽  
Radar Reflectivity ◽  
Small Scale ◽  
Time Interval ◽  
Outer Domain ◽  
Storm Prediction ◽  
The Impact ◽  
Assimilation Time

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in the three-dimensional variational data assimilation (3DVAR) system of the Weather Research Forecast (WRF) model on rain storm prediction in Daqinghe basin of northern China. The aim of this study was to explore the potential effects of data assimilation frequency and to evaluate the outputs from different domain resolutions in improving the meso-scale NWP rainfall products. In this study, four numerical experiments (no assimilation, 1 and 6 h assimilation time interval with DWR and GTS at 1 km horizontal resolution, 6 h assimilation time interval with radar reflectivity, and GTS data at 3 km horizontal resolution) are carried out to evaluate the impact of data assimilation on prediction of convective rain storms. The results show that the assimilation of radar reflectivity and GTS data collectively enhanced the performance of the WRF-3DVAR system over the Beijing-Tianjin-Hebei region of northern China. It is indicated by the experimental results that the rapid update assimilation has a positive impact on the prediction of the location, tendency, and development of rain storms associated with the study area. In order to explore the influence of data assimilation in the outer domain on the output of the inner domain, the rainfall outputs of 3 and 1 km resolution are compared. The results show that the data assimilation in the outer domain has a positive effect on the output of the inner domain. Since the 3DVAR system is able to analyze certain small-scale and convective-scale features through the incorporation of radar observations, hourly assimilation time interval does not always significantly improve precipitation forecasts because of the inaccurate radar reflectivity observations. Therefore, before data assimilation, the validity of assimilation data should be judged as far as possible in advance, which can not only improve the prediction accuracy, but also improve the assimilation efficiency.

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