Rajesh Vaishnav, Christoph Jacobi, Erik Schmölter, Hanna Dühnen
{"title":"Influence of Lower Atmospheric Variability: An Investigation of Delayed Ionospheric Response to Solar Activity","authors":"Rajesh Vaishnav, Christoph Jacobi, Erik Schmölter, Hanna Dühnen","doi":"10.1029/2024JA032999","DOIUrl":null,"url":null,"abstract":"<p>This study aims to examine the impact of lower atmospheric forcing on upper atmospheric variability using the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM). We conducted numerical experiments comparing induced variability due to Hough Mode Extension (HME) tides constrained by winds and temperatures from Ionospheric Connection Explorer-Michelson Interferometer for Global High-Resolution Thermospheric Imaging (ICON-MIGHTI) observations. Our model comparisons focus on the changes in the composition of the thermosphere-ionosphere and the delayed ionospheric response to the 27-day solar EUV flux variations during periods of low solar activity. We report the results of model simulations with and without tidal forcing at the approximate 97 km lower boundary of the TIEGCM. The differences led to changes in thermosphere-ionosphere parameters such as electron density, peak electron density, and the <span></span><math>\n <semantics>\n <mrow>\n <mi>O</mi>\n <mo>/</mo>\n <msub>\n <mi>N</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation> $O/{N}_{2}$</annotation>\n </semantics></math> ratio. The results show that the impact of tidal forcing is mainly observed in the low- and mid-latitude regions, affecting the correlation between <span></span><math>\n <semantics>\n <mrow>\n <mi>O</mi>\n <mo>/</mo>\n <msub>\n <mi>N</mi>\n <mn>2</mn>\n </msub>\n </mrow>\n <annotation> $O/{N}_{2}$</annotation>\n </semantics></math> and NmF2. This change in correlation affects the amount of ionospheric delay. When tidal forcing is included, the modeled delay improves compared to the observed delay during low solar activity. The spatial variation of ionospheric delay due to induced tidal effects highlights the importance of understanding lower atmospheric forcing in thermosphere-ionosphere models. This is crucial for predicting and understanding the ionospheric response to solar flux.</p>","PeriodicalId":15894,"journal":{"name":"Journal of Geophysical Research: Space Physics","volume":"129 11","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JA032999","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Space Physics","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024JA032999","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to examine the impact of lower atmospheric forcing on upper atmospheric variability using the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM). We conducted numerical experiments comparing induced variability due to Hough Mode Extension (HME) tides constrained by winds and temperatures from Ionospheric Connection Explorer-Michelson Interferometer for Global High-Resolution Thermospheric Imaging (ICON-MIGHTI) observations. Our model comparisons focus on the changes in the composition of the thermosphere-ionosphere and the delayed ionospheric response to the 27-day solar EUV flux variations during periods of low solar activity. We report the results of model simulations with and without tidal forcing at the approximate 97 km lower boundary of the TIEGCM. The differences led to changes in thermosphere-ionosphere parameters such as electron density, peak electron density, and the ratio. The results show that the impact of tidal forcing is mainly observed in the low- and mid-latitude regions, affecting the correlation between and NmF2. This change in correlation affects the amount of ionospheric delay. When tidal forcing is included, the modeled delay improves compared to the observed delay during low solar activity. The spatial variation of ionospheric delay due to induced tidal effects highlights the importance of understanding lower atmospheric forcing in thermosphere-ionosphere models. This is crucial for predicting and understanding the ionospheric response to solar flux.