TY - JOUR
T1 - Long-Term Trend of Topside Ionospheric Electron Density Derived From DMSP Data During 1995–2017
AU - Cai, Yihui
AU - Yue, Xinan
AU - Wang, Wenbin
AU - Zhang, Shunrong
AU - Liu, Libo
AU - Liu, Huixin
AU - Wan, Weixing
N1 - Funding Information:
We acknowledge the support by the National Natural Science Foundation of China (41621063 and 41427901), the Open Research Project of Large Research Infrastructures (China)-?Study on the interaction between low-/middle-latitude atmosphere and ionosphere based on the Chinese Meridian Project,? and the Thousand Young Talents Program of China. Work at MIT Haystack Observatory is supported in part by cooperative agreement AGS-1762141 between the US NSF and MIT. This work is also supported in part by the US NSF Grant AGS-145-2309. The National Center for Atmospheric Research is sponsored by the National Science Foundation.
Funding Information:
We acknowledge the support by the National Natural Science Foundation of China (41621063 and 41427901), the Open Research Project of Large Research Infrastructures (China)‐“Study on the interaction between low‐/middle‐latitude atmosphere and ionosphere based on the Chinese Meridian Project,” and the Thousand Young Talents Program of China. Work at MIT Haystack Observatory is supported in part by cooperative agreement AGS‐1762141 between the US NSF and MIT. This work is also supported in part by the US NSF Grant AGS‐145‐2309. The National Center for Atmospheric Research is sponsored by the National Science Foundation. H. L. acknowledges support by JSPS KAKENHI Grants 18H01270, 18H04446, 17KK0095, and JRPs‐LEAD with DFG. This work is also part of the achievements of ISSI/ISSI‐BJ team on “Climate Change in the Upper Atmosphere” led by Zhang. We thank the NCAR/HAO team for the development and opening source of the NCAR‐TIEGCM ( https://www.hao.ucar.edu/modeling/tgcm/ ). The DMSP SSIES data were made by the Center for Space Sciences at University of Texas at Dallas and the US Air Force and accessed through the Madrigal database ( http://millstonehill.haystack.mit.edu/ ). The CO records from Mauna Loa were accessed from NOAA/ESRL ( https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html ). The IGRF coefficients were downloaded from NOAA/NGDC website https://www.ngdc.noaa.gov/IAGA/vmod/igrf.html . The and indices were taken from the NOAA FTP site ( ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP/ ). Simulation data presented in this paper can be publicly available from this site ( https://osf.io/rsgqt/ ). 2 F 10.7 A p
Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - In recent decades, significant efforts have been made to characterize and understand the global pattern of ionospheric long-term trend. However, little attention has been paid to the topside ionosphere trend. In this study, the unique in situ data measured by series Defense Meteorological Satellite Program (DMSP) satellites were utilized to derive the long-term trend of the topside ionosphere for the first time. We checked carefully data quality, gap, and consistency between different satellites for both electron density and ion temperature, and compared the techniques of artificial neuron network (ANN) and multiple linear regression methods for deriving the trend. The electron density (Ne) trend in the middle and low latitudes at ~860 km around 18 MLT was derived using the ANN method from 1995–2017. The trend from DMSP observations has a mean magnitude ranging from ~ − 2% to ~2% per decade, with clear seasonal, latitude and longitude variations. The derived trend was evaluated by directly comparing with the simulated trend at 500 km from the NCAR-TIEGCM driven by realistic changes of CO2 level and geomagnetic field. The observed and simulated trends have similar geographic distribution patterns at 18 MLT. The good agreement between the observed trend around 860 km and the simulated trend near 500 km implies that the physical processes controlling the Ne trends above the peak height might be identical. Further control simulations show that the geomagnetic field secular variation is the dominant factor of the electron density trend at around 500 km, rather than the CO2 long-term enhancement.
AB - In recent decades, significant efforts have been made to characterize and understand the global pattern of ionospheric long-term trend. However, little attention has been paid to the topside ionosphere trend. In this study, the unique in situ data measured by series Defense Meteorological Satellite Program (DMSP) satellites were utilized to derive the long-term trend of the topside ionosphere for the first time. We checked carefully data quality, gap, and consistency between different satellites for both electron density and ion temperature, and compared the techniques of artificial neuron network (ANN) and multiple linear regression methods for deriving the trend. The electron density (Ne) trend in the middle and low latitudes at ~860 km around 18 MLT was derived using the ANN method from 1995–2017. The trend from DMSP observations has a mean magnitude ranging from ~ − 2% to ~2% per decade, with clear seasonal, latitude and longitude variations. The derived trend was evaluated by directly comparing with the simulated trend at 500 km from the NCAR-TIEGCM driven by realistic changes of CO2 level and geomagnetic field. The observed and simulated trends have similar geographic distribution patterns at 18 MLT. The good agreement between the observed trend around 860 km and the simulated trend near 500 km implies that the physical processes controlling the Ne trends above the peak height might be identical. Further control simulations show that the geomagnetic field secular variation is the dominant factor of the electron density trend at around 500 km, rather than the CO2 long-term enhancement.
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U2 - 10.1029/2019JA027522
DO - 10.1029/2019JA027522
M3 - Article
AN - SCOPUS:85077877306
VL - 124
SP - 10708
EP - 10727
JO - Journal of Geophysical Research: Space Physics
JF - Journal of Geophysical Research: Space Physics
SN - 2169-9380
IS - 12
ER -