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The MIGHTI Wind Retrieval Algorithm: Description and Verification

Overview of attention for article published in Space Science Reviews, April 2017
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Title
The MIGHTI Wind Retrieval Algorithm: Description and Verification
Published in
Space Science Reviews, April 2017
DOI 10.1007/s11214-017-0359-3
Pubmed ID
Authors

Brian J. Harding, Jonathan J. Makela, Christoph R. Englert, Kenneth D. Marr, John M. Harlander, Scott L. England, Thomas J. Immel

Abstract

We present an algorithm to retrieve thermospheric wind profiles from measurements by the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument on NASA's Ionospheric Connection Explorer (ICON) mission. MIGHTI measures interferometric limb images of the green and red atomic oxygen emissions at 557.7 nm and 630.0 nm, spanning 90-300 km. The Doppler shift of these emissions represents a remote measurement of the wind at the tangent point of the line of sight. Here we describe the algorithm which uses these images to retrieve altitude profiles of the line-of-sight wind. By combining the measurements from two MIGHTI sensors with perpendicular lines of sight, both components of the vector horizontal wind are retrieved. A comprehensive truth model simulation that is based on TIME-GCM winds and various airglow models is used to determine the accuracy and precision of the MIGHTI data product. Accuracy is limited primarily by spherical asymmetry of the atmosphere over the spatial scale of the limb observation, a fundamental limitation of space-based wind measurements. For 80% of the retrieved wind samples, the accuracy is found to be better than 5.8 m/s (green) and 3.5 m/s (red). As expected, significant errors are found near the day/night boundary and occasionally near the equatorial ionization anomaly, due to significant variations of wind and emission rate along the line of sight. The precision calculation includes pointing uncertainty and shot, read, and dark noise. For average solar minimum conditions, the expected precision meets requirements, ranging from 1.2 to 4.7 m/s.

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Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 24%
Researcher 3 9%
Student > Bachelor 2 6%
Other 2 6%
Student > Doctoral Student 2 6%
Other 1 3%
Unknown 15 45%
Readers by discipline Count As %
Physics and Astronomy 7 21%
Earth and Planetary Sciences 6 18%
Engineering 4 12%
Computer Science 2 6%
Business, Management and Accounting 1 3%
Other 1 3%
Unknown 12 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2023.
All research outputs
#6,493,633
of 23,025,074 outputs
Outputs from Space Science Reviews
#403
of 1,090 outputs
Outputs of similar age
#104,719
of 310,210 outputs
Outputs of similar age from Space Science Reviews
#12
of 19 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,090 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 310,210 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.