Title
Early Morning Equatorial Ionization Anomaly From GOLD Observations
Date Issued
01 July 2020
Access level
metadata only access
Resource Type
journal article
Author(s)
Laskar F.I.
Eastes R.W.
Martinis C.R.
Daniell R.E.
Pedatella N.M.
Burns A.G.
McClintock W.
Goncharenko L.P.
Coster A.
Wang W.
Valladares C.E.
Codrescu M.V.
Jicamarca Radio Observatory
Publisher(s)
Blackwell Publishing Ltd
Abstract
During geomagnetically quiet and solar minimum conditions, spatial variations of the early morning thermosphere-ionosphere (TI) system are expected to be mainly governed by wave dynamics. To study the postmidnight dynamical coupling, we investigated the early morning equatorial ionization anomaly (EIA) using Global-scale Observations of the Limb and Disk (GOLD) measurements of OI-135.6 nm nightglow emission and global navigation satellite system (GNSS)-based total electron content (TEC) maps. The EIA structures in the OI-135.6 nm emission over the American landmass resemble, spatially and temporally, those observed in the GNSS-TEC maps. The early morning EIA (EM-EIA) crests are well separated in latitude and mostly located over the middle of South America during October–November. In February–April the crests are less separated in latitude and predominantly located over the west coast sector of South America. Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (WACCMX) simulations with constant solar minimum and quiet-geomagnetic conditions show that EM-EIA can occur globally and shows properties similar to longitudinal Wave 4 pattern. Thus, we propose that EM-EIA is driven by dynamical changes associated with the lower atmospheric waves.
Volume
125
Issue
7
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas
Subjects
Scopus EID
2-s2.0-85088575519
PubMed ID
Source
Journal of Geophysical Research: Space Physics
ISSN of the container
21699380
Sponsor(s)
Computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. The Level 1Cdata used in this study are available at the GOLD Science Data Center ( https://gold.cs.ucf.edu/search/ ) and at NASA’s Space Physics Data Facility ( https://spdf.gsfc.nasa.gov/pub/data/gold/ ). GNSS TEC data productsand access through the Madrigal distributed data system are provided to the community ( https://cedar.openmadrigal.org ) by the Massachusetts Institute of Technology (MIT) under support from U.S. NationalScience Foundation Grant AGS‐1242204.
This research was supported by NASA Contract 80GSFC18C0061 to the University of Colorado, Boulder. This material is also based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation under Cooperative Agreement 1852977.
Sources of information:
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