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 The impact of large scale ionospheric structure on radio occultation retrievals

2011 ◽  
Vol 4 (3) ◽  
pp. 2525-2565 ◽  
Author(s):  
A. J. Mannucci ◽  
C. O. Ao ◽  
X. Pi ◽  
B. A. Iijima
Keyword(s):  
Large Scale ◽  
Radio Occultation ◽  
Observation Strategy ◽  
Climatological Model ◽  
Ionospheric Data Assimilation ◽  
Using Data ◽  
Temperature Retrieval ◽  
The Impact ◽  
Retrieval Bias

Abstract. We study the impact of large-scale ionospheric structure on the accuracy of radio occultation (RO) retrievals of atmospheric parameters such as refractivity and temperature. We use a climatological model of the ionosphere as well as an ionospheric data assimilation model to compare quiet and geomagnetically disturbed conditions. The largest contributor to ionospheric bias is 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. The temperature retrieval bias under disturbed conditions varies from 1 K to 2 K between 20 and 32 km altitude, compared to 0.2–0.3 K during quiet conditions. 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 ionospheric conditions, 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 error. Satellites in higher altitude orbits (≧700 km) tend to have lower biases due to the tendency of the residual bending to cancel between the top and bottomside ionosphere. 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 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.

The Effects of the Expansion of For-Profit Colleges on Student Enrollments and Outcomes at Community Colleges

2018 ◽  
Vol 40 (4) ◽  
pp. 631-652 ◽  
Author(s):  
Adela Soliz
Keyword(s):  
Community College ◽  
Postsecondary Education ◽  
Large Scale ◽  
Higher Education System ◽  
For Profit ◽  
Education Data ◽  
Education Levels ◽  
Short And Long Term ◽  
Using Data ◽  
The Impact

This study is the first large-scale examination of the impact of for-profit colleges on the enrollment and outcomes of students at other postsecondary institutions. Using data primarily from the Integrated Postsecondary Education Data System (IPEDS) and a differences-in-differences approach, I estimate the effect of a new for-profit college opening on community college enrollments and degree completions, as well as county education levels. My results suggest that community college enrollments and degree completions do not decline when a new degree-granting for-profit college opens nearby. Furthermore, I find evidence that the county-level production of short- and long-term certificates increases after a new for-profit college opens, though the number of associate’s degrees does not increase. This evidence should serve to broaden conversations about the role of for-profit colleges in the larger landscape of the American higher education system.

scholarly journals A comparison of Galactic electron density models using PyGEDM

2021 ◽  
Vol 38 ◽  
Author(s):  
D. C. Price ◽  
C. Flynn ◽  
A. Deller
Keyword(s):  
Electron Density ◽  
Large Scale ◽  
Galactic Halo ◽  
Application Programming Interface ◽  
Dispersion Measure ◽  
Radio Pulsars ◽  
Distribution Models ◽  
Distance Measurements ◽  
Application Programming ◽  
The Impact

Abstract Galactic electron density distribution models are crucial tools for estimating the impact of the ionised interstellar medium on the impulsive signals from radio pulsars and fast radio bursts. The two prevailing Galactic electron density models (GEDMs) are YMW16 (Yao et al. 2017, ApJ, 835, 29) and NE2001 (Cordes & Lazio 2002, arXiv e-prints, pp astro–ph/0207156). Here, we introduce a software package PyGEDM which provides a unified application programming interface for these models and the YT20 (Yamasaki & Totani 2020, ApJ, 888, 105) model of the Galactic halo. We use PyGEDM to compute all-sky maps of Galactic dispersion measure (DM) for YMW16 and NE2001 and compare the large-scale differences between the two. In general, YMW16 predicts higher DM values towards the Galactic anticentre. YMW16 predicts higher DMs at low Galactic latitudes, but NE2001 predicts higher DMs in most other directions. We identify lines of sight for which the models are most discrepant, using pulsars with independent distance measurements. YMW16 performs better on average than NE2001, but both models show significant outliers. We suggest that future campaigns to determine pulsar distances should focus on targets where the models show large discrepancies, so future models can use those measurements to better estimate distances along those line of sight. We also suggest that the Galactic halo should be considered as a component in future GEDMs, to avoid overestimating the Galactic DM contribution for extragalactic sources such as FRBs.

scholarly journals Magnetism Science with the Square Kilometre Array

Galaxies ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 53
Author(s):  
George Heald ◽  
Sui Mao ◽  
Valentina Vacca ◽  
Takuya Akahori ◽  
Ancor Damas-Segovia ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Large Scale ◽  
Galactic Nuclei ◽  
Dark Matter Annihilation ◽  
New Techniques ◽  
Square Kilometre Array ◽  
New Radio ◽  
Recent Developments ◽  
Using Data ◽  
The Impact

The Square Kilometre Array (SKA) will answer fundamental questions about the origin, evolution, properties, and influence of magnetic fields throughout the Universe. Magnetic fields can illuminate and influence phenomena as diverse as star formation, galactic dynamics, fast radio bursts, active galactic nuclei, large-scale structure, and dark matter annihilation. Preparations for the SKA are swiftly continuing worldwide, and the community is making tremendous observational progress in the field of cosmic magnetism using data from a powerful international suite of SKA pathfinder and precursor telescopes. In this contribution, we revisit community plans for magnetism research using the SKA, in light of these recent rapid developments. We focus in particular on the impact that new radio telescope instrumentation is generating, thus advancing our understanding of key SKA magnetism science areas, as well as the new techniques that are required for processing and interpreting the data. We discuss these recent developments in the context of the ultimate scientific goals for the SKA era.

scholarly journals The Efficacy of Ethnic Stacking: Military Defection during Uprisings in Africa

2019 ◽  
Vol 5 (4) ◽  
pp. 695-702 ◽  
Author(s):  
Julien Morency-Laflamme ◽  
Theodore McLauchlin
Keyword(s):  
Large Scale ◽  
Armed Forces ◽  
Future Research ◽  
Group Loyalty ◽  
Limited Support ◽  
History Of ◽  
Group Members ◽  
Using Data ◽  
The Cost ◽  
The Impact

Abstract Does ethnic stacking in the armed forces help prevent military defection? Recent research, particularly in Africa and the Middle East, suggests so; by favoring in-groups, regimes can keep in-group soldiers loyal. In-group loyalty comes at the cost of antagonizing members of out-groups, but many regimes gladly run that risk. In this research note, we provide the first large-scale evidence on the impact of ethnic stacking on the incidence of military defection during uprisings from below, using data on fifty-seven popular uprisings in Africa since formal independence. We find clear evidence for the downside: ethnic stacking is associated with more frequent defection if out-group members are still dominant in the armed forces. We find more limited support for the hypothesized payoff. Ethnic stacking may reduce the risk of defection, but only in regimes without a recent history of coup attempts. Future research should therefore trace the solidification of ethnic stacking over time.

An Impact Assessment of GPS Radio Occultation Data on Prediction of a Rapidly Developing Cyclone over the Southern Ocean*

2014 ◽  
Vol 142 (11) ◽  
pp. 4187-4206 ◽  
Author(s):  
Shu-Ya Chen ◽  
Tae-Kwon Wee ◽  
Ying-Hwa Kuo ◽  
David H. Bromwich
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Large Scale ◽  
Radio Occultation ◽  
Three Dimensional ◽  
Wrf Model ◽  
The Other ◽  
Gps Radio Occultation ◽  
The Antarctic ◽  
The Impact

Abstract The impact of global positioning system (GPS) radio occultation (RO) data on an intense synoptic-scale storm that occurred over the Southern Ocean in December 2007 is evaluated, and a synoptic explanation of the assessed impact is offered. The impact is assessed by using the three-dimensional variational data assimilation scheme (3DVAR) of the Weather Research and Forecasting (WRF) Model Data Assimilation system (WRFDA), and by comparing two experiments: one with and the other without assimilating the refractivity data from four different RO missions. Verifications indicate significant positive impacts of the RO data in various measures and parameters as well as in the track and intensity of the Antarctic cyclone. The analysis of the atmospheric processes underlying the impact shows that the assimilation of the RO data yields substantial improvements in the large-scale circulations that in turn control the development of the Antarctic storm. For instance, the RO data enhanced the strength of a 500-hPa trough over the Southern Ocean and prevented the katabatic flow near the coast of East Antarctica from an overintensification. This greatly influenced two low pressure systems of a comparable intensity, which later merged together and evolved into the major storm. The dominance of one low over the other in the merger dramatically changed the track, intensity, and structure of the merged storm. The assimilation of GPS RO data swapped the dominant low, leading to a remarkable improvement in the subsequent storm’s prediction.

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